Data managementRe-engineering retail structures, skills and strategies for a data culture

Produced in association with eClerx

Data Domain Delivery

Joseph Sursock HEAD OF THE EMEA BUSINESS, ECLERX

Laura Heywood SUPPLEMENTS EDITOR, RETAIL WEEK

In the modern connected world, one cannot es-cape the myriad references, questions and ideas around data management, big data, omnichannel and analytics. This report is taking a deeper look at the aspects of these as they transform the retail industry. The reader will discover what execu-tives, from both UK and international retailers, are thinking and plotting as they continue to build for the future and tackle the challenges where the rubber meets the road in their world.

Today’s consumer-driven use of technologies and devices has created new revenue opportuni-ties. According to Gartner Research, by 2020, customers will manage 85% of their product re-lationships without talking to a human.

Clearly, consumers have an ever-increasing set of choices available to them as they navi-gate their retail experiences. Retailers also have a number of choices in their quest to tackle the considerable headwinds while keep-ing pace in a competitive and hyper-connected world. The challenges include complex data types, drawing actionable insights, maintain-ing a consistent customer experience, bringing

more SKUs to market more quickly, managing highly segmented campaigns across multiple channels and regions, and rapidly responding to market changes.

Retailing is about people and products. While some firms may have enjoyed huge successes on the back of a relative few people’s understanding of fashion, market timing and consumer prefer-ences, today retailers cannot escape the need to better understand potential purchases and con-sumer needs through the use of increasingly vo-luminous data sets. The reader will discover how the lack of bandwidth in their respective teams is identified as the greatest obstacles in extrapolat-ing data. Finding staff that can respond to data management and data analytics challenges, set by the increasingly demanding management teams in retailing today, is tricky. Some of the answers lie in collaborations with specialists, exploring hybrid engagement models and focusing on market-leading service-level agreements that can drive the desired results.

Just like in the past, when successful retail-ers were born and many became large success-

ful firms over the years, today the secret sauce continues to be striking a balance between managing business risk and servicing consumers as closely as possible. Managing risk in today’s digital world can involve rigorous innovation, testing and validation of key assumptions and hypotheses – to keep pace within ever-decreasing timeframes.

Lastly, a common theme throughout this report continues to be the ever-closer servicing of the consumer. Unpicking the data and turning it into something useful in terms of usable, proactive insight-guided activity, is essential for customers to engage, purchase and to recommend - with an increasing emphasis on the quality of high-volume data rather than just quantity. We would whole-heartedly support that notion.

As consumers, we all leave behind a footprint whenever we engage with any digital technology. Whether it’s downloading music, emailing a friend or tweeting about our day, everything we do can be used to build up a picture of who we are and what we like.

If you’re not convinced by just how big a footprint you’re making, just consider this fact: on the eve of the new millennium, 25% of the world’s stored information was digital. Now in 2014, and just 2% is non-digital.

Whether we welcome it or not, the ability of re-tailers to tap into that information and personally target us is going to become more and more ad-vanced as sophisticated tools emerge to mine and interpret the data we’re creating 24/7.

And it won’t just be unstructured data, such as videos, emails, photos and, of course, social media updates, that retailers will be analysing minutely. Instead they will possess the ability to integrate that behavioural data with retail point-of-sale data from tills. Such meshing of data will give retailers the opportunity to understand how the way people feel about a brand translates into actual sales. Pre-

dicting trends and forecasting demand with near 100% accuracy could become common practice.

From that point on, the art of selling will be turned entirely on its head. Instead of products driving the business, customers will.

The possibilities for the future might be endless, but how are retailers preparing for a time when big data informs everything they do?

This report seeks to answer that question. It is based on interviews with a number of senior- level industry leaders, including chief executives, from a diverse range of businesses. From big-name fashion retailers and grocers, to leading pure-plays and high street chains, we have been granted exclusive insight into just how much the explosion of big data is changing retail organisations beyond recognition.

From siloed departments with individual responsibility for data analysis, suddenly entire business functions are uniting in their shared ownership of that data flood. Staff skill sets are being redrawn; relationships with expert outsources transformed and old strategies blown out the water.

But how far down the line are retailers in their quest to be entirely data driven? The following chap-ters provide a vital insight into the stage of the jour-ney the retail industry is on, and how it is preparing to enter a time when every piece of information a consumer leaves behind about themselves can be turned into actionable insight.

As this Data Management report states, “information is coming from everywhere – from sensors used to gather climate information and posts on social media sites, to purchase transac-tion records and mobile phone GPS signals – and it is coming all the time”. Retailers who have not only recognised this, but made strides to change their structures, skills and strategies accordingly, will be the ones who thrive in this new era of big data.

PARTNER FOREWORDFOREWORD

“THE MESHING OF DATA WILL GIVE RETAILERS THE OPPORTUNITY TO UNDERSTAND HOW THE WAY PEOPLE FEEL ABOUT A BRAND TRANSLATES INTO ACTUAL SALES”

“TODAY’S CONSUMER-DRIVEN USE OF TECHNOLOGIES AND DEVICES HAS CREATED NEW REVENUE OPPORTUNITIES”

Data Domain Delivery

eClerx provides critical business operations services to more than 30-plus global Fortune 500 clients, including many of the world’s leading financial services firms, online retail and distributors, interactive media and entertainment, high tech and industrial manufacturing, travel and leisure, and software vendors, through operational support, data management and analytics solutions.

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Big data is currently big news. There are few in retail that haven’t heard of it, but perhaps fewer still are making the best possible use of it. Perhaps that’s not surprising given the volumes of structured and unstructured data retailers are faced with on a daily basis.

IBM estimates that the world is generating 2.5 quintillion (18 zeros) bytes of data each day, more than 90% of which has been created in the past two years. At the turn of the century only 25% of the world’s stored information was digital. Fast forward to 2014 and just 2% is non-digital.

Myriad surveys have shown that companies want to embrace this data. This report digs deeper, capturing the views of a number of senior level industry leaders, including chief executives, from a diverse range of businesses, competing across a number of markets. It identifies the challenges they face, the opportunities they see and the changes they expect to make. It offers the most detailed picture of data analysis in retail to date.

For those that have become accustomed to using structured data and relatively small samples of behavioural data, big data has come as a bit of a shock. Information is coming from everywhere – from sensors used to gather climate information and posts on social media sites, to purchase transaction records and mobile phone GPS signals – and it is coming all the time.

The complexity of the data and the diversity of sources are therefore considerable obstacles

EXECUTIVE SUMMARY

to managing it effectively, according to almost half (45%) of those interviewed. Social media, for instance, has added a layer of unstructured, behavioural data to the structured data retailers have historically been comfortable with. “Hard- core transactional details are fact, but when you start to overlay them with some of our geo-demographic and profiling data it makes it quite confusing,” admits the chief executive of a major online retailer.

This explains why 80% of retailers feel their product data management is more advanced than that relating to their customers. Retail businesses (traditionally reliant on walk-in and/or walk-by traffic) are built around product segments and product categories, and this could have hindered progress.

Until now, that is. Many of those interviewed claim their knowledge is beginning to seesaw towards a more balanced appreciation of data, from which a new model could evolve which leads with customers and channels, rather than products. Going forwards, some retailers, at least, feel that customer data and predictive technology will be more important, with social media data perhaps even driving where their business will be relevant in the future.

Of course, few retailers are in that place yet. Asked how prepared they are to create a central hub of information to “bring the data alive for effective selling in today’s retail environment”, more than two thirds (66%) rate themselves as a five or six out of 10 (with 10 being fully prepared), while 14% feel they are below five. One in five feel they are better prepared than most, scoring their business readiness at seven or eight out of 10.

One of the most frequent reasons given for retailers seeing themselves as not quite as

prepared as they’d like to be – and hence the fairly low levels of preparedness – is a change in systems, skills and structure. Many have only recently recognised the need to implement systems to ensure data analysis is a core part of their business. Investment is now in the pipeline and expected to accelerate in the near future.

It must be noted that the interviewees represent a broad range of retail businesses, from fashion retailers and grocers to pure-plays and huge high street chains, but while marketing and IT appear to be the departments leading the responsibility for managing data (60% and 47% respectively), there is an ebb and flow of power.

Organisational structures are changing but there is little obvious consistency. What is apparent is that retailers believe that models where IT have stored and held the data are becoming outdated. IT clearly has a critical role to play in a data-driven business, but sharing the information is set to become the new norm. This will see more functions of every retail business guided by the data. Indeed, 13% of those interviewed believe that “every department should be responsible for data”.

Findings from a plethora of recent research shows that consumers are more willing to share their shopping data than any other kind. It seems

a similar movement is taking place internally in retail organisations.

Many retail bosses are aware that a surge of new data could “inundate and confuse” parts of the business. However, a controlled data push – in combination with what retailers note as a refreshing ‘pull’ from parts of the organisation demanding data – is where many are headed. Again, they are not there yet: a third (33%) want to encourage more cross-functional collaboration across departments on data management.

This research proves that many retailers are in a phase of ‘preparing’ rather than ‘prepared’ for using vast volumes of data, a mood perhaps best described by the chief operating officer of a clothing brand retailer: “We’re going through a tremendous change in terms of consumer behaviour. And the level of data capture that takes place, compared with just a couple of years ago, is huge. How to unpick the data and turn it into something useful in terms of usable proactive activity is the big question for retailers like us.”

Better data analysis is noted by 47% of those interviewed as the most critical factor that needs to change with regards to data management in their company. For the majority, the challenge is finding the people with a head for numbers and business acumen to turn information into insight. Two thirds (64%) say they are struggling with capacity in their team, while more than a third (36%) also complain of a lack of technical ability to analyse all data sources. The market has, according to the senior insight manager of a major retailer, been depleted because of an explosion of analytics companies.

A split in attitudes towards using external expertise (in this case 40% say they won’t

outsource, compared with 33% who want to) demonstrates the importance retailers are placing on big data. The ambition of a good proportion is to either develop talent internally, and attract those with enhanced statistical analysis skills, or outsource to companies who, as one IT and ecommerce director says, can quickly and efficiently “act as a catalyst to change”.

Get the right people and the pace is expected to quicken, with companies keen to move from data collection to comprehension. The aim: to understand customers better, refocus their businesses and allow data to guide them. The emphasis on ‘guide’ is critical.

There is a sense of perspective that is easy to spot among most of the interviews and responses. Data is creating a buzz thanks to the possibilities it brings in terms of prediction. But that won’t kill the art of retail – the gut instinct, the creativity. But there is little doubt that retail in the era of big data is a very different place.

Predicting future behaviour and trends is interesting, but also lucrative. Consultancy firm McKinsey has put a figure of $325bn (£197bn) on improved efficiency savings in manufacturing and retail should data analytics become mainstream.

Examples of what is possible may well be small now, but progress is expected to accelerate as more businesses realise the potential of the information now available to them. Attracting

Percentage of retailers that feel their product data manage-ment is more advanced than that relating to their customers

80%

“AT THE TURN OF THE CENTURY ONLY 25% OF THE WORLD’S STORED INFORMATION WAS DIGITAL. FAST FORWARD TO 2014 AND JUST 2% IS NON-DIGITAL”

“HOW TO UNPICK THE DATA AND TURN IT INTO SOMETHING USEFUL IN TERMS OF USABLE PROACTIVE ACTIVITY IS THE BIG QUESTION FOR RETAILERS LIKE US” Chief operating officer of a clothing brand retailer

data scientists to help them do this is proving a challenge, with some expecting external expertise to plug the gap.

“If you don’t have the skills in-house you have to outsource initially,” says the IT and ecommerce director of a clothing retailer. “And the great advantage [of that] is speed. At this stage the trick is finding the right partner – that partner will act as a catalyst to change process.”

The success of longer-term partnerships has certainly caught the eye of some; partnerships that have allowed some businesses to incorporate third-party data sets and external data feeds into their analyses, rather than rely on the operational data captured and stored in their back-end systems.

This is the future, and retailers are mindful that an inability to collect, mine, assess and use data will see them struggle to keep pace with the competition.

But technology can only take retailers so far – they need people to convert the data into relationships and insights. As retailers understand how to improve attitudes towards data throughout all retail functions, the business benefits that reorganisation will bring become abundantly clear.

With the right structures and skill sets to collect, analyse, share and use this new wave of information, the opportunities are endless.

Percentage of respondents that are struggling with capacity in their team with regards to data management

64%

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EXECUTIVE SUMMARY

CHAPTER 4A HEAD FOR NUMBERS: FINDING THE RIGHT SKILL SETO��A third of those responsible for data are struggling for

bandwidth in their teamO��More than a quarter complain of lack of technical expertise

among staff and potential recruitsO��There is a feeling of ‘preparing’ rather than ‘being prepared’

for data analyticsO��New types of data has changed skills retailers are recruiting for

CHAPTER 5COLLECTION TO COMPREHENSION: HOW TO USE DATAO��Massive transition taking place from collection to

comprehensionO��87% rate preparedness to use data as five out of 10 or moreO��Social data offers future insight – retailers must handle with careO��Emerging opportunity to combine point-of-sale data with

sentiment analysis from social mediaO��Gut instinct is still a part of retail when it comes to data analysis

CHAPTER 6 CONCLUSION: MORE DATA, MORE OPPORTUNITIESO��The board, staff and customers increasingly buying into the

concept of big dataO��Vast quantities of customer data will enable retailers to identify

new trends and adapt their offer accordinglyO��Willingness for organisational structure to change as data

infiltrates every part of the business O��High demand for the skill sets to collect, analyse, share and use

the new wave of informationO��New phase of internal data sharing and heightened

responsibilities for departments outside of IT

CHAPTER 1DATA EXPLOSION: WHAT’S OUT THERE?O��90% of all data has been created in the past two yearsO��Retailers are aware of big data and its potentialO��Quantity of data (especially unstructured data) is a headacheO��The challenge is finding relevant data in the sea of spreadsheetsO��Retailers such as Asos and Burberry show early signs

of progress

CHAPTER 2DEALING WITH THE CHALLENGES OF DATA COLLECTIONO��Board-level understanding of data management is a barrier

for only 7% of those interviewedO��80% of respondents say product data is still more advanced

than customer dataO��Customer data is becoming a big focus – retailers covet

behavioural dataO��Money is being spent on the customer rather than the

billboardO��Budgets are strong for many, with some expectation of extension

CHAPTER 3DATA OWNERSHIP IN RETAIL BUSINESSESO��60% say marketing takes a lead role, 47% say IT doesO��The power struggle between and IT and marketing

persists O��Teams work in siloes – confusion and duplication is

a concernO��Data sharing across departments will be the new normO��33% of respondents want more cross-functional collaboration

on translating dataO��Dissemination of data must be concise and easily understood

“WE HAVE LITERALLY TENS OF MILLIONS OF DATA POINTS THAT WE ARE MANAGING EVERY DAY. AND WE NOW HAVE TO MANAGE THAT HOUR BY HOUR”

“THE BUDGET FOR DATA COLLECTION, MAINTENANCE AND ANALYSIS IN MY TEAM WILL REACH 50%. DATA IS EVERYTHING. LOOK AT THE PURE-PLAYS; THEY MUST BE ABOVE THE 50% MARK ALREADY”

“THE MAIN CHALLENGE IS COMPETENCE, GETTING THE RIGHT PEOPLE TO ANALYSE YOUR DATA. AND INTELLIGENT USE OF IT WHEN IT IS ANALYSED”

“FRANKLY, I DON’T THINK WE ARE CLEAR ON HOW RESPONSIBILITY FOR DATA MANAGEMENT GROWTH IS ASSIGNED”

“STORAGE IS NOT A PROBLEM THESE DAYS. THE PROBLEM IS TO FIND INSIGHT FROM THE DATA”

“BIG DATA CHANGES THE COMPETENCE OF YOUR BUSINESS MODEL. BIG DATA IS ALL ABOUT EQUIPPING YOUR BUSINESS WITH THE RIGHT TOOLS SO THAT YOU CAN TRADE INTELLIGENTLY”

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DATA EXPLOSION: WHAT’S OUT THERE?

CHAPTER 1

For retailers accustomed to using relatively small amounts of data to run their businesses and understand their customers, such as samples from focus groups, the emergence of big data has come as both a shock and a saviour.

While the biggest names in retail are struggling with input overload, on the flipside, they are also realising the value that can be found in collecting, analysing and using it.

The challenges ahead are undoubtedly daunting, which makes this assessment of the attitudes of retailers towards data ownership in 2014 timely.

Are retailers really drowning in data? Do their boards understand the value held in their databases? Who has responsibility for data management in the business and how is this likely to change? Does the sector have the talent pool to mine the information and, critically, do customers want them to? And are the gains from effective data management over-played or, in fact, understated?

This research, based on in-depth interviews with senior directors across a range of functions, details where retailers are when it comes to arguably their biggest challenge and greatest opportunity to date. It will help them understand how to improve attitudes towards data and consider the benefits that reorganisation might bring.

HOW BIG IS BIG?Thanks to technology there is a lot more data floating around than ever before. IBM estimates that the world is generating 2.5 quintillion (18 zeros) bytes of data each day, more than 90% of which has been created in the past two years. This explosion – in

O 90% of all data has been created in the past two years

O Retailers are aware of big data and its potential

O Quantity of data (especially unstructured data) is a headache

O The challenge is finding relevant data in the sea of spreadsheets

O Retailers such as Asos and Burberry are showing early signs of progress

part thanks to the internet, which allows businesses, governments and society, to collect and share data more easily – is relatively new. At the turn of the century only 25% of the world’s stored information was digital. Fast-forward to 2014 and just 2% is non-digital. It’s hardly surprising that retailers might be struggling to cope.

The commercial services director at a supermarket chain explains what his team is faced with: “We have literally tens of millions of data points that we are managing every day. And we now have to manage that hour by hour because it is growing exponentially in terms of the granularity of the detail we get into.”

The chief executive of a home shopping business adds: “I think everybody in this industry feels to varying degrees that we have now come to a point of information overload.”

There is a suggestion that retailers have become ‘blinded’ by data – but not just in terms of volume and velocity. Social media has added a layer of unstructured, behavioural data to the structural, transactional data that retailers have historically been comfortable with. This can be a powerful tool, given that it provides retailers access to the ‘why’ as well as the ‘what’ of purchasing decisions. As one

respondent suggests, Facebook is like running 24/7 focus groups.

However, social media also makes for ‘messier’ data. In the past data was captured, often through sampling – a snapshot from which businesses could infer something about a wider customer group, for instance. Nowadays, the pool of data is almost endless – what statisticians refer to as ‘n = all’. As Kenneth Cukier, data editor of The Economist and Viktor Mayer-Schoenberger, professor of internet governance and regulation at the Oxford Internet Institute, explain in their 2013 essay The Rise of Big Data, by increasing the scale of the ‘samples’ by orders of magnitude “we might have to give up on clean, carefully curated data and tolerate some messiness”. This idea, of course, runs counter to how people have tried to work with data for centuries (see chapter 2). It can also lead retailers into the dangerous territory of prediction.

“WE HAVE LITERALLY TENS OF MILLIONS OF DATA POINTS THAT WE ARE MANAGING EVERY DAY. AND WE NOW HAVE TO MANAGE THAT HOUR BY HOUR”Commercial services director of a grocer

What is big data?

“Every day, we create 2.5 quintillion bytes of data – so much that 90% of the data in the world today has been created in the last two years alone.

“This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data.” IBM

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THE RULES OF PREDICTIONThe economic crisis of the late 2000s has, in some quarters, been blamed on a “catastrophic failure of prediction”.

In a comment piece for Retail-week.com, John Richards, former retail analyst and consultant at corporate finance adviser McQueen, joins the dots between what economists did, and what retailers might be tempted to do. “The fundamental mistake economists made was attempting to achieve respectability by treating economics as a natural science rather than a social science.

“The application of science, big data and the most powerful algorithms will not produce answers but mere probabilities. Retail falls into the same bag – it has to contend with consumer behaviour, which is rarely rational or predictable,” he says.

Many of those interviewed in this report are acutely aware of the limitations in behavioural data – and the risks of trying to second-guess their customers. “Looking at past behaviour and trying to analyse it to see if you can predict future behaviour is a very interesting science,” says one retail chief executive. “But, equally, if I could personalise this, I probably know most of what my wife has bought over the past 25 years but it doesn’t make it any easier to know what to buy her for her birthday.” (see chapter 5).

The use of customer data is fraught with risk, with retailers treading the fine line between personalised and creepy. The scope of the Tesco Clubcard, for example, was detailed in Andrew Simms’ book Tescopoly: “Tesco probably ends up knowing more about a cardholder’s comings and goings than the holder’s husband or wife,” he writes. Back then there were 10 million cards in active use; today there are 16 million.

But research has shown customers are willing

to share more data, provided it is used to improve targeting of particular products and services. In fact, effective data usage can engender trust and respect among customers (see chapter 2), while irrelevant communications can alienate them.

Ret a i lers apprec iate t h is a nd t heir acknowledgement is perhaps best captured by the chief executive at a premium fashion store, who says: “To win in this highly competitive environment we must have better targeted marketing and better information in terms of sales prediction in order to manage our inventory efficiently. In order to stay competitive we need more data and better analysis to enable us to make sharper and faster management decisions.”

BIG WINSThe benefits are already emerging in some cases. The chief executive at a specialist retailer believes a gap between those retailers who are data-aware and those who are not is beginning to emerge. He uses grocery as an example: “Poor management of data can be fatal to a company these days,” he says, claiming supermarkets with loyalty cards “are enjoying the richness of that data and the insights it gives”, while ones without are “data poor and paying the price”.

A recent example of data analysis in action involves Asos, the fashion retailer, which increased sales by a third in the four months to December 2013 through the use of real-time pricing software that pulls in data from across the web to inform its buying and merchandising decisions.

Meanwhile, coffee chains in the US are also targeting offers at customers while they are waiting in line for the morning pick-me-up. The difference is that it’s the customers using mobile payment kiosks that get the rewards. Upon placing their order, their data is processed, an offer generated and a coupon sent – all within two seconds. It is predicted this could mean people will buy 30% more than they would have ordinarily – and have them coming back for more.

Burberry is another retailer that some of those interviewed applaud for its use of consumer data.

Given the large numbers of Chinese and wealthy eastern customers it has, the brand has identified what sells well to ensure similar lines are available to tourists visiting its UK stores. The company’s outgoing chief executive, Angela Ahrendts, claimed recently that consumer data will be “the biggest differentiator in the next two to three years. Whoever unlocks the reams of data and uses it strategically will win”.

“IN ORDER TO STAY COMPETITIVE WE NEED MORE DATA AND BETTER ANALYSIS TO ENABLE US TO MAKE SHARPER AND FASTER MANAGEMENT DECISIONS”Chief executive of a premium fashion store

DEALING WITH THE CHALLENGES OF DATA COLLECTION

CHAPTER 2

The percentage of the world’s stored information that is digital in 2014

98%

NEXT STEPS

O��Don’t jump into complicated big data projects until you feel you are making good use of smaller, more structured data sets. If you can’t handle traditional data analysis, you will not yield positive results from big data projects.

O��Don’t be afraid to watch your competition and learn from them. In this rapidly-evolving space, you can’t afford to start from scratch. Apply the best approaches that you can find from peers/competitors, or even other industries, and grow from there.

O��There is a big opportunity to feed internal learning curves through simple pilots and proof of concepts. Education is key for that gradual understanding of the art of possible.

Data Domain Delivery

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12 13

In the past, retailers had to decide what data to collect and how it would be used. It was a costly process and the analysis was time-consuming. Much could still be inferred from these small data sets, but it is nothing compared with what is possible in today’s technical environment. Data collection has been turned on its head, with the problem no longer being what to collect, but what not to collect.

Big data is essentially a moniker for all the data and data sources that pertain to the selling activities of a company. That might be product data, customer data, sales data, competitor data and anything that results during the activity of a company trading.

In 2014, retailers are dealing with transactional as well as behavioural data. It is the latter they covet, but equally fear. “Hard-core transactional details are fact but when you start to overlay them with some of our geo-demographic and profiling data [for example from social media] it makes it quite confusing,” says the chief executive of an online retailer (see box on p13).

PRODUCTS VERSUS CONSUMERSHistorically, successful retailers have excelled through analysis of product data, interspersed with a degree of sampling and behavioural data. It is hardly surprising therefore that retailers feel their 2014 approach to product data is well ahead of their analysis of customer data. Some 40% claim their product data management is “much more” advanced than their management of customer data,

O�Board-level understanding of data management is a barrier for only 7% of those interviewed

O�80% of retailers say product data is still more advanced than customer data

O�Customer data is becoming a big focus – retailers covet behavioural data

O�Money is being spent on the customer rather than the billboard

O�Budgets for data analysis are strong for many retailers, with some expectation of extension

while another 40% say it is “slightly more” advanced (see chart 2.1 on p15).

The idea of ‘big data’ is a relatively new phenomenon (the majority admit they have only come across it in the past two years), so many brands are still grappling with the power and potential of data sourced from mobile channels, social media, customer feedback, GPS and the like. After all, retail businesses are built around product segments and product categories. But this model could be hindering progress.

“Long-standing retailers are still leading with product, then with channel and then with customer. And, consequently, they are standing still,” says Joseph Sursock, head of the EMEA business unit at eClerx. “New standing and growing retailers can lead with customer and channel, and then with product. Too few of the main retailers can do so. Yes – customer data and analytics is difficult, which is why they need help.”

A survey by analytics software provider AgilOne earlier this year found that European retailers are behind when it comes to setting up central customer data warehouses – only 36% have done so compared with 51% in the US. In the UK, change is definitely

on the cards: many of those interviewed in this report believe their knowledge is seesawing towards a more balanced appreciation of data.

“Although product data management is much more advanced at the moment, we believe that customer data management will catch up. Ideally we would like it to be 50/50,” says the IT business relationship manager of a high street retailer.

The brand and ecommerce director of a fashion retailer agrees to a certain extent: “I think that product data is a good way ahead. Customer data will catch up. But whether it will catch up completely I’m not sure. Product information is so critical when you are selling products – you can’t afford to drop a single ball. There is definitely a desire to do more customer data and we want to do the right thing by customers,” he says.

The bottom line is that big data could enable retailers to better understand customer segments – and the selections they make in their channels of choice. Offers can then be made more relevant and personal, thus generating sales. It is a premise that the corner shop used 50 years ago, as the senior insight manager of a major retailer alludes to: “The owner of the shop would know you by name and say, ‘I have a new product that I think you will like, based on what you buy. Do you want to try it, it’s on special offer?’ Management of big data just allows you to do that on a massive scale.”

Other retailers interviewed also notice a definite shift in business tactics. The IT and ecommerce director of a fashion retailer explains: “Historically,

“WE ARE ALL DATA-RICH AND INFORMATION-POOR BECAUSE WE CAN’T GET THE DATA OUT”IT business relationship manager of a high street retailer

data within a retail organisation has always been focused on product and location. But going forward customers are more important and predictive technology is more important. Sometimes you are using areas like social media to drive where you feel your business will be relevant in the future.

“So you might use social digital space to help launch new products, to test the market and to inform your business on how you are going to trade. So these are the things we have come to terms with culturally and intellectually and now we have to find and embrace the technical knowhow.”

THE BOARD IS CONVINCEDWhether the UK retail sector is ahead of the game in terms of its exploitation of data is hard to say. However, many feel that the country is entering a period of change, and this could drive the sector to new heights.

The chairman at a specialist retailer summarises: “I am on the board of a company overseas. And up until 18 months ago when I talked to them about the importance of the internet they laughed. It’s only in the last year that there has been an explosion of online [over there].

“We don’t realise how advanced we are in this country when it comes to ecommerce and using data to sell.”

At the very least, the sector has an appreciation of the potential of structured and unstructured data and from top to bottom there is a realisation that numbers matter. When asked what the attitude towards data and analytics is like in their firms, the consensus among the interviewees was optimistic. “I would say very positive,” says the marketing director of a specialist retailer. “If you are seen as an individual, or a department, to be referring to data and taking it seriously and using it to inform decisions, it is viewed as a positive thing and encouraged.”

A lead from the top certainly helps, and there appears to be little evidence of a generational gap to bridge at the board level. Only 7% of retailers interviewed feel that a better understanding at board level is one of the critical factors that needs to change in order for the firm to move forward on big

data. The levels of understanding within retail will be discussed in chapter 4, but at this point it’s worth noting the views of the chief technology officer at a specialist online retailer, who explains why he has only worked in places where the decision-makers are enthusiastic about the potential of interpreting data.

“I wouldn’t want to work in a company [where there wasn’t that enthusiasm] again. For most companies I would think the most critical factor that needs to change would be clearer plans for leveraging multi-source data because most companies are not using the depths of their data right now. At this point all of the boards will have heard about big data but most will not have the experience to make the right decisions about it. In the last few years I have been in the business of recruiting data scientists and they are in very short supply,” he says.

DECENT BUDGETSMany of those interviewed mention the pace of change in their businesses, and the subsequent

changes taking place (see chapter 3). Recognition from the board has been critical to progress, but that isn’t always easy: those pushing the power of data have to prove the business case before they have any real insights.

This, perhaps, explains why the budgets assigned to data collection, management, maintenance and analysis vary widely among respondents. Of those that know their budgets, more than half (57%) have budgets of less than 10% attributed to this area. Meanwhile, 22% are spending more than half their budget on big data management (see chart 2.2 on p15).

Of course, this must be caveated with the diverse range of senior directors within very different businesses interviewed for this research. As one marketing director comments regarding the 5% to 10% of his budget dedicated to data: “That is a reflection of where we are as a business. We are going through a transformation within our business, so that figure reflects the priority that this kind of stuff has. It also reflects well the fact that we are not currently capturing customer data for our store transactions, which is a big gap. So there really isn’t any point in spending a lot of money on something you are not really going to get the reward for.” (see chapter 5).

Few of those interviewed mention a desire to seek more financial backing. Somewhere around the 5% or 10% mark is seen as a “decent-sized chunk”. Some say they are hard-pressed to allocate

“WE ARE AT LAST SEEING THE POINT OF SOCIAL MEDIA. THE INTEGRATION OF SOCIAL WILL BE A STEP-CHANGE IN TERMS OF VOLUME OF DATA”Customer director of an online retailer

Hard to nail

“Say you are trying to tee up a generic profile for people living in the Southeast in an affluent post code. Information like that is hard to apply. People living there are not necessarily wealthy, they may not have a bean to spend or they may be the live-in help. So the actionable data is the hard- core sales data, which is why product information is always more important to a retailer than consumer data.

“Social data is very tricky. And what customers say on one day is not necessarily what they say on another. Social data is the hardest to nail. A lot of it is aspirational. They may say they love our products but that doesn’t mean they are going to buy any of them.” Chief executive of a fashion etailer

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14 15

any more because of their promotional spend. “Because of the absolutely massive spend I have on advertising and promotion [£100m], I have had to do a lot with under 5%,” remarks the chief executive of a specialist retail chain.

However, others are already planning a higher spend as their focus on marketing budget, in particular, shifts from the billboard to the customer. The IT and ecommerce director of a high street fashion brand explains: “[The budget for data collection] is high. It has to be 30% [of my team’s total budget]. Loyalty is huge in this company. I have a two million-plus loyalty database. It will reach 50%. It is going to drive everything we do. Data is everything. Look at the pure-plays; they must be above the 50% mark already. Asos and Amazon must be above 50%. And they are the companies we are competing with. We are paranoid about pure-plays because we know that they want our customer data.”

Others also see data as “everything”. The senior vice-president for digital marketing and ecommerce of a clothing brand store explains: “As everything is data, everything we spend is to make that data better and to make that data work more to our advantage. The advertising money that we spend is predominately spent on tools and platforms that allow us to target people and to understand who those people are and therefore to collect more data. A lot of our investment is going to be to make sure that all the dots are connected.”

CUSTOMERS ARE CONVINCEDKnowing your customer is the oldest and most important retail discipline. Big data is enabling retailers to do that on a massive scale; this is not mass email spamming, it’s combining the art of retail with the science of statistics to paint a single view of the customer and in turn personalise their experience.

That’s the concept, but it’s not necessarily the case yet. Some of those interviewed for the Retail

2014 report by Retail Week suggested that “we are wearing people down with irritating, inappropriate emails”. Understanding behavioural data could change that (see chapter 5).

To understand people and communicate better with them, retailers are reliant on their customers offering up information. This has them treading a fine line between invasion of privacy and personalisation of communications; meanwhile, the thought of a data breach will keep many of today’s top retail executives awake at night.

Take Neiman Marcus. The US-based speciality department store revealed in January that 1.1 million credit cards were infected with malware last summer, resulting in fraudulent use of cards. More than 110 million customers of fellow retailer Target also had their personal information exposed during a data breach late last year. A survey of more than 6,000 consumers from across the globe, published by advertising agency McCann in 2012, found that ‘erosion of personal

privacy’ came second (70%) only to the threat of a further financial crisis (78%) among their top concerns. Terrorism and climate change were third and fourth. In fact, 36% of people would rather have their homes broken into than have their bank details hacked.

Thankfully, cases of data breach are the exception rather than the rule. Contrary to some media reports, customers are willing to offer their personal data if retailers and brands then use it to provide the right offers, at the right time. Readers will take heart from McCann’s finding that people are more eager to share their shopping data than any other – 71% are comfortable with this, compared with 48% who will share location data and 39% who will offer personal data. Reports published by the Direct Marketing Association and Deloitte last year show a similar rise in willingness to offer a ‘fair exchange’ of data.

And more good news in a recent survey by data management firm Transactis shows how

In-depth insight: customer versus product data

“When you are talking about data, you have to be clear whether you are talking about customer data or product data because they are handled differently and both get you to a different place.

“So, product wise, the data is primarily driven by sales and we have a lot of it. We put in a new EPoS system about 12 months ago that is linked through to the back office systems and we have a business intelligence tool that the guys can all use. So there is a great deal of information that is collated on product and it informs all the decisions that we make. So product wise, we are in reasonable shape. But then, in line with other retailers, we have to decide what to do with that information and how to turn it into something useful. So we’re about seven out of 10 for product data.

“The customer data is managed in a slightly different place and at the moment we are migrating it across. It was held by the ecommerce team, but what I have done over the past six months is move the ownership of customer data over to the marketing team – they deal with customer insight so I wanted customer data in the same place. And I’m setting up a CRM function. That is all happening at the moment, but I would put customer data at only five out of 10.”Ecommerce director of a fashion retailer

effective use of data can engender trust and respect among consumers.

Many attribute the change in attitudes to the rise of social media, which has fundamentally altered the nature of what is private or public. Those interviewed for this report believe this freedom of expression and data exchange can provide retailers with a “360° view” of customers. “We are at last seeing the point of social media,” says the customer director of a multi-brand online retailer. “The integration of social will be a step-change in terms of volume of data. We need social to complete that 360° view of the customer.”

He adds: “We want to understand what sort of interactions are taking place on social [media] to get a more rounded picture of our customers. We want to know what they are talking about. For example, if one of our customers is on social about their impending house move, we can use that information to drive products that they may be interested in when they move.”

BASE: ALL RESPONDENTS

2.1 How advanced do you feel the approach to product data management is in your organisation, compared with the approach to customer data management?

Customer data management is much more advanced than product data management

Customer data management slightly more advanced than product data management

Both equally advanced

Both equally immature

0%

40%

13%

7%

0%

40%Product data management is much more advanced than customer data management

Product data management is slightly more advanced than custo-mer data management

BASE: ALL RESPONDENTS

2.2 In your individual function or team, how much of your budget do you predict will be invested in data management collection, maintenance and analysis this year?

0-5% 14%

5-10% 43%

10-15% 7%

15-20% 7%

25-50% 7%

More than 50% 22% £NEXT STEPS

O��Collecting data is relatively easy. Defining the problems you are attempting to solve – to then determine the data necessary to analyse those problems – is less so. Data storage is cheap. Storing the right data at the right level (of granularity) with the right period in mind is less obvious. To avoid countless hours in this area with unmanageable complexity, teams need very good top-down questions and discussions that will drive relevant hypothesis – both prerequisites for frequent data chasing.

Data Domain Delivery

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DATA OWNERSHIP IN RETAIL BUSINESSES

CHAPTER 3

The potential friction between teams working in IT and marketing has generated plenty of column inches. The former are concerned by creative types ‘moving on’ analytical roles, while the latter complain of roles becoming ‘too analytical’.

However, by working in synergy, marketing, IT and ecommerce teams can evaluate and expand the infrastructure, tools and processes needed to identify and implement new digital strategies to engage with customers on a more personal level. This will put them at a competitive advantage.

TAKING RESPONSIBILITY So, who has responsibility for data? It seems that marketing, IT and ecommerce have the power, currently at least. The results must be caveated with the fact that, in certain cases, some of the functions sat together – for example CRM within marketing.

Almost two thirds (60%) of those interviewed say staff in marketing (33%) and digital marketing functions (27%) are most responsible for managing big data, while 47% say IT. This is followed by CRM at 40% and consumer insight at 27% (see graph 3.1 on p19). Although this suggests responsibilities are spread across the business, 40% identify one business function as ‘most responsible’ for data management. Of those, a third have IT leading, a third have marketing leading and a third have customer insight teams leading.

Whoever is leading, there needs to be a

O 60% say marketing takes a lead role, 47% say IT does

O Power struggle between IT and marketing persists

O Teams working in siloes – confusion and duplication is a concern

O Data sharing across departments will be the new norm

O 33% want more cross-functional collaboration on translating data

O Dissemination of data must be concise and easily understood

plan, says David Nelson, practice lead for digital analytics at eClerx. “You need to know what you’re going to do with the data and what the consequences of that are. If not, you can waste a lot of time on brilliant statistical analysis that the marketing team [for instance] can’t use.”

Effective communication comes up time and again across the interviews (see box below). A minority (13%) believe that “every department should be responsible for data”.

“Most organisations have tended to work in siloes traditionally, but reporting of data across the business and utilising data from other areas and bringing that data together is something that we should be focused on,” explains the IT manager of a high street chain.

The IT and ecommerce director of a fashion retailer adds: “No one function is responsible. It’s holistic. It’s the whole business. I think if you just see it as a function-based responsibility you miss the whole point of it. Big data changes the competence of your business model.”

IT, for instance, is coming to the fore – a trend documented in previous research by Retail Week entitled Ignored to Enabler – the changing role of the IT director. For some, IT will be at the heart of their new business models, geared to take advantage of the data flood. “IT have become much more involved than they used to be,” says the insight manager at

“NO ONE FUNCTION IS RESPONSIBLE. IT’S HOLISTIC. I THINK IF YOU JUST SEE IT AS A FUNCTION-BASED RESPONSIBILITY YOU MISS THE WHOLE POINT OF IT”IT and ecommerce director of a fashion retailer

Working together“I don’t think we are at the top of the maturity curve but we are nowhere near the bottom. Our attitude towards data has been in a constant state of flux for the past 12 months. In the past 12 months there has been a real push towards trying to build synergy between disparate analytical groups within this business. And a push to give these groups a more cohesive feel and to generate a sharing of ideas and a sharing of the way you are going to do things. Just because you are working with a slightly different set of data shouldn’t really matter.”Insight manager of a major retailer

April 2014 |

1918

a major retailer. “This was to do with internal projects that we were going on at the time. But it also has to do with specific elements of the culture of this business.” Data has also been guarded by IT in the past, but this is expected to change too (see box below).

Will more be moving that way? When asked how the responsibilities and functions have changed in the past 12 months, 47% say not at all. For the rest there have either been gradual changes or huge shifts in the way data is managed. For some, a significant change has been the focus on consumer insight, which will be used to shape the strategic direction of the business going forward. For others there has been a shift in responsibilities from marketing to IT, but for some interviewed the flow has been in the opposite direction. It is safe to say that businesses are shaping their teams in many different ways. What is certain is that big data is forcing a re-think in structure, responsibility and access.

DATA SHARING: THE NEW NORMA clear trend is the desire to share more data, and right across the organisation. This is not an “opening of the floodgates”, rather a controlled data push. Indeed, many of those interviewed are aware that a data surge could “inundate and confuse”.

The supply chain director of a major grocer explains: “Traditionally data has been the province of the trading function and marketing. But the focus was switched to supply chain because it has become much more operational. That is because we

are looking not just at total sales at a company level, or by region, or by store; we are looking at it by store, by the hour. That is way beyond the level of detail that marketing and trading looked at.”

Controlling that data push – “pre-chewing it and pre-digesting it before releasing it” and “condensing it into the so what? And now what?” – is a major challenge for retailers (see chapters 4 and 5). Some are understandably reluctant to release too much. “For the moment we have managed to keep the data with the people who can understand and cope with it. We have not confused people down in the trenches with it and we won’t until we have a clear idea of our customer insights,” says the chief executive of a specialist retailer.

The IT and ecommerce director at a fashion retailer also explains how “confusion has reigned” in some companies he has worked for. “You have to generate it in a way that your people understand; it has to be tailored to your audience. You gradually build up the competence levels in the business and if people are confused or irritated it is a failure of leadership, not the individuals receiving the data.”

Regardless of this control over the push, there is sometimes an internal pull as more functions seek access to data. Marketing has led the charge, but others are close behind. “When I go and talk to

people in operations they are hungry for information and data. Now that is something new,” says the IT manager of a high street fashion retailer.

Yet cross-functional col laboration is not as advanced as many would like. “If you push me for the most critical change to data management needed, I would say cross-functional collaboration,” says the director of an online retailer. “I would like to see the ability of our organisation to share intelligence across the group. At the moment we have a number of different siloes that work in isolation. We are all accessing the same data but doing different things. And there is a lack of knowledge sharing. I am going to try to bring that together.”

This director is not alone. A third (33%) of those interviewed identify similar barriers, while the same number also think more holistic reporting of data

“IF YOU ARE SEEN AS AN INDIVIDUAL, OR A DEPARTMENT, TO BE REFERRING TO DATA AND TAKING IT SERIOUSLY AND USING IT TO INFORM DECISIONS, IT IS VIEWED AS A POSITIVE THING AND ENCOURAGED”Marketing director of a specialist retailer

across the business is a major challenge (see chart 3.2 right). Some point to how poor management of data internally can lead to “cannabilisation” of the business – if teams are working independently rather than to one vision the result is likely to be a disjointed customer brand experience. The single view of the customer goes out the window.

The technology officer of a health and beauty etailer concludes how he is trying to avoid such confusion and duplication. “We need more holistic views and reporting of data across the business because, typically, different teams have pursued their own agendas.

“And there is a great deal of confusion and duplication about which is right. What I am trying to do is build a culture that believes data analysis is integral to all business decisions. To sustain that culture you need to recruit people that are good at it. You also have to train people who don’t get it yet.”

IT switches on“Up until now IT has been dealing with fixed projects where they knew exactly what they were doing in advance. Now they are dealing with elements of big data where you load some big data, have a play with it and then see if you can pick up some insights. You then try to figure out how those insights can help the business. I think IT is just now coming around to that way of thinking.“I think in the future big data management will centralise within an IT function but I think the IT functions will look very different going forward than they have done traditionally. IT has always had a ‘them and us’ attitude. And they never shared information. I think what will happen now is that it will become much more integrated and there will be a lot more collaboration. There will be joint functional teams that move this forward.”Insight manager of a major retailer

The percentage of respondents that say marketing and digital marketing teams are most responsible for managing big data

60%

BASE: ALL RESPONDENTS

3.1 Which functions do you think are most responsible for managing big data in your business?

IT

Digital marketing

Consumer insight

CRM

Loyalty

Marketing

Supply chain

Sales

Procurement

Multichannel

Digital operationsOther (responses include: Triangle

between IT, marketing and multi-channel; Triangle between CRM,

loyalty and customer insight, bundled under ‘customer insight’ team)

47%

0%

0%

0%

7%

7%

33%

13%

40%

27%

27%

3%

BASE: ALL RESPONDENTS

3.2 What are the most critical factors that need to change with regards to data management in your company?

More responsibility for data management 7% More responsibility for data

quality 20% More cross-functional collaboration 33%

Better understanding at board level 7%

Greater individual understanding or training throughout the business 7%

Other 33% (responses include: Data access; Consolidation of data; Being confident of a return)

More holistic views/ reporting of data across the business 33%

Better data analysis 47%

Clearer plans for leveraging multi-source data 20%

NEXT STEPS

O��Creating a steering committee and governance process for managing big data projects is a good idea. Regardless of who the final decision makers are (marketing, IT or ecommerce), everyone should have a seat at the table to influence the direction of analytical projects.

O��If your organisation is not yet experienced in working with cross-functional teams, take proactive steps in moving in that direction. Executive-level sponsorship of big data projects may be necessary.

Data Domain Delivery

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A HEAD FOR NUMBERS: FINDING THE RIGHT SKILL SET

CHAPTER 4

There is huge value in understanding consumers better. That makes data a precious commodity. “Our database is the thing that is worth most in the company. There are three million people [on it],” explains the chief executive of an online retailer.

Equally precious are the skill sets required to mine the data and turn it into something tangible for retailers. This, presently, is a struggle.

In chapter 2, the gap between the understanding of product and customer data is detailed. In chapter 3, some of the changes businesses are undergoing from an organisational and functional perspective are discussed. Chapter 5 covers the analysis of data and the potential and peril of ‘living by statistics’, but first attention turns to the people who will carry out those changes, share data, mine data and use it to help retailers make predictions.

PREPARED OR PREPARING?When asked how prepared they are to create a central hub of information to “bring the data alive” for effective selling in today’s ever-changing retail environment, more than two thirds (66%) rate themselves as a five or six out of 10 (with 10 being fully prepared), while 14% admit they are below five on the scale (see graph 4.1 on p22).

One in five (20%) feel they are better prepared than most, scoring their business readiness at seven or eight out of 10. One of the most frequent reasons given for the current status is a change in systems and structure. Indeed, many feel they are ‘preparing’ rather than ‘prepared’, but there is little doubt that many are implementing systems to ensure they

O Third of those responsible for data are struggling for bandwidth in their team

O More than a quarter complain of lack of technical expertise among staff and potential recruits

O Feeling of ‘preparing’ rather than ‘prepared’ for data analytics

O New types of data have changed skills retailers are recruiting for

climb the scale. Some are investing (see chapter 2) and expect things to accelerate quickly.

In terms of technology it appears retailers are content, building databases to house the multi-source information ready for it to be mined. Whether they have the manpower, or indeed brain power, to turn that into something useful for the business is another matter.

A lack of bandwidth (or developed skill set) in their respective teams is identified as the greatest obstacles in managing data by 64% (see chart 4.3 on p23). Far fewer (36%) think a lack of technical solutions is a challenge. “I say bandwidth because

we have more data than we have time to address,” says the supply chain director of a major grocery chain, when asked what the biggest barrier for him is to manage this data.

“We would like to do a lot more with that surplus data but we don’t have the bandwidth to do it. I am really confident that there is another five years of optimisation in our business to go at – if we had the bandwidth to mine the data that we have already got. We need many more analysts but you have to operate within the constraints of the business.”

BIG DATA – SMALL POOLFinding those analysts isn’t easy. For many of those who see bandwidth as an issue in their team, there is often a convergent concern: a lack of technical expertise available to analyse all sources of data.

Indeed, some suggest that staff are ill-prepared for a world in which numbers will dominate. “The thing is you are either numbers driven or you are not

Outsourcing versus in-house“Because we are going through massive system changes, I would like to outsource some areas where we lack knowledge and experience. There are some fantastic outsourcing partners who can utilise fragmented data and turn that into something usable. But the board has decided to spend money growing our own team of analysts mainly because all the exposures in terms of data are going to get more, not less, challenging.”Chief operating officer of an apparel retailer

The percentage of respondents that say a lack of bandwidth is the greatest obstacle in managing data

64%

April 2014 |

2322

and so the difficult thing is getting people who are not, to appreciate how the numbers and the data can inform their day-to-day business decisions,” says the chief executive of an etailer.

Big data has certainly shed new light on the skills retailers are recruiting for. The supply chain head of a major grocer explains: “There is definitely a requirement for enhanced statistical analysis and most retailers are grown with no statisticians in them. That is why we have recruited some relatively deep statistical resources to make sure we are analysing the data in the right way. That is not a skill set retailers would normally have recruited for.”

Retailers therefore have a challenge ahead: how to attract the brightest talent to bring their data to life? A combination of business nous and statistical expertise is in demand. “We will be hiring more people but it is more re-purposing,” says the chief executive of a home shopping retailer. “The overall size of our IT team is not going to grow, but there will certainly be more data specialists and there will be fewer in the legacy area. So the skill set will change.”

Research published by Retail Week last year showed that IT graduates primarily want to work with a technology start-up. Almost half (49%) listed this as their preferred career option if given the choice – a legacy of the ‘Apple effect’ no doubt. What is surprising is how far down the list retail languished – just 4% named it as their first-choice sector.

In this report, some retailers confirm that “good people are really hard to come by”. The senior insight manager at a major retailer expands: “There is an explosion of companies who are starting to do analytics and they need all the functions from data preparation to insight analysis.” First rate analysts looking for work are therefore difficult to find.

So, is outsourcing an option for him? “When it comes to the choice between outsourcing and bringing senior analysts in-house, I think that, because this is such a new area, you need to grow

your own intellectual property within a business. You can outsource to an extent but I wouldn’t be a fan of outsourcing an entire function and losing that intellectual property in that generation and also losing the driving of ideas.”

OUTSOURCE OR IN-HOUSE?Throughout the interviews it becomes clear that retailers at different stages of maturity with their digital marketing services and multichannel data management are addressing gaps in their arsenal of tools and skills in diverging ways. Some are focusing on ramping up capability quickly through a partner, and then over time rebalancing what they do in-house and what they outsource.

Alternatively, some retailers favour the collaborative nature of in-house teams and outsourced teams working together, and are reaping the long-term benefits. By outsourcing certain executional activities, the in-house teams are freed to generate actionable insights and

the retailer benefits from better productivity, quality management and operational agility.

The results of the in-depth interviews show retailers are weighing up the benefits of capturing knowledge in-house compared with the benefits of outsourcing more data management (see box on p21). Overall, 40% say they will not outsource, compared with 33% who want to or are already doing so. The remainder (27%) might consider it at some point, but probably only in the short term (see chart 4.2 below).

For this 27%, working with specialist outsources for a limited period is essential when a project requires speed of execution, specialist knowledge of data types and particular analytics skills. Such relationships would normally run on a project-by-project basis, normally for two to six months per project, and are reliant on the partners’ understanding of various data sets in the given sector of retailing.

With a skills gap emerging, many retailers want to be sure they are the ones developing the intellectual

property. The ecommerce head of a fashion brand sums up his position on outsourcing: “Short term, yes. Long term, absolutely not.” He elaborates: “The easiest and the fastest way to start is by outsourcing but, over time, I think that any outsourcer worth their salt understands that if a company is serious about data, at some point in the future they are going to start in-sourcing those outsourced activities. That understanding of the data itself needs to permeate throughout the organisation so a lot of that is going to be permanent.

“We’re never going to get away from data. And even when people are done with teaching and instructing how to read through the tealeaves, they will remain as champions and thought leaders in that space. So, if anything, the data gurus in the company are only going to grow in numbers.”

Those who provide external expertise argue that there is an opportunity around education of retailers. Indeed, big data analytics is one of the most potent, but potentially problematic, techniques in business today. This has left some retailers “with little progress in this area”, says Joseph Sursock, head of the EMEA business unit at eClerx. “The pace of analytics and the leveraging process of multiple data sources to understand your customer’s changing behaviour and preferences, is so high that many companies are reviewing their options. The teams who do not want to be left with a costly high-churn scenario of in-house senior analysts (that are in high demand by many firms today) are relying on third parties

‘Slowed down by people’“A few years ago we only had a consumer insight department. We didn’t have a CRM system; that only came about a year ago. I decided to have a CRM department because we had a rich history of about 25 years of customers’ names and addresses. The beauty of my business is that we actually go into people’s homes and make measurements and so on. And I realised that I had never exploited that data. I had a massive opportunity but not the internal capability.

“I had previously recognised it as an opportunity but when you are delivering a four-year strategic agenda you just have to prioritise which are the big prizes you take in which order. When we got to the point of being ready to do it, I was slowed down by not having the right people. So I was very keen to employ the right experts and I wanted a CRM specialist who was used to analysing data. It took me a long time to find someone I thought was strong enough to be head of our CRM.”Chief executive of a specialist retailer

“WE ARE NEVER GOING TO GET AWAY FROM DATA. AND EVEN WHEN PEOPLE ARE DONE WITH TEACHING AND INSTRUCTING HOW TO READ THROUGH THE TEALEAVES, THEY WILL REMAIN AS CHAMPIONS AND THOUGHT LEADERS IN THAT SPACE”Ecommerce director of a fashion brand

BASE: ALL RESPONDENTS

4.1 On a scale of one to 10, how prepared is your organisation for creating a central hub of information to bring the data alive for effective selling in a changing and multichannel retail environment? One being basic and 10 being fully prepared

0% 0%0% 0%

7% 7%

26%

40%

7%

13%

1 2 3 4 5 6 7 8 9 10

BASE: ALL RESPONDENTS

4.3 What are your greatest obstacles in managing data?

Complexity of data

Lack of technical ability to analyse all sources

Lack of technical solutions

Cost of continuous maintenance

Diversity of data sources

Bandwidth in my team, while running the business

18%

36%

36%

0%

27%

64%

BASE: ALL RESPONDENTS

4.2 Would you consider outsourcing portions of data management?

Yes 33%

No 40%

Possibly 27%

| April 2014 April 2014 |

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COLLECTION TO COMPREHENSION: HOW TO USE DATA

CHAPTER 5

to craft hybrid engagements that can be in production in weeks.”

According to Sursock, working with a third party on parts of businesses’ data analytics can yield positive results given how much data needs to be managed when focusing over and above just product and categories. “Fundamentally retailers need to evolve beyond product segments, product categories and large customer segmentation. All of which will inf luence much of their day-to-day operations,” he says, claiming a detailed focus on consumer behaviour and channel engagement analysis, as well as product and categories, is critical.

The issue of cost also splits the survey. Some are concerned by high costs, while others view outsourcing as a cost saving. Speed – again as a result

of the retail skills gap – also makes outsourcing an attractive option for some. “At this stage the trick is to find the right partner because if you get the right partner, that partner will act as a catalyst to change process. If you try to do that internally it takes you too long,” says the IT and ecommerce director of a high street fashion retailer.

In this case, attention turns to examples; Tesco’s partnership with Dunnhumby is the obvious one. Experts at eClerx ponder if other retailers had instigated the same kind of data management capacity in the mid-90s then “they would not be sitting where they are today in fourth, fifth or sixth on the leader board”. It cannot be ignored that those often seen as working best with data to date – such as Tesco and Walmart – are those that have sought expertise externally.

NEXT STEPS

O��Invest in at least one true data scientist who can perform advanced modelling and analytics. Beyond that, the bulk of the work will be performed by a combination of teams. They will help to define the objectives of the big data problem, including third-party providers, which can typically perform the time-intensive data gathering and cleansing necessary to perform analyses.

O��Look outside of retailing. There are other industries equally highly geared in multichannel, such as travel and leisure and online gaming, that operate on different ‘clocks’. Their view of frequency, reporting analytics, correlations, funnels, cause and effect, multi-touch, management dashboards and KPIs, can bring valuable additions to your strategy.

Data Domain Delivery

BASE: ALL RESPONDENTS

4.4 What percentage of staff responsible for data insight is temporary?

0-5%

86% 5-10%

7% 10-15%

0%

More than 50%

0% 25-50%

0% 15-20%

7%

| April 2014

2726

people through our stores and although a scattergun approach can work you are not optimising your potential.”

It is actually in the store where some retailers are struggling to initiate this data flow from and to their customers. There are early pioneers around – the Swiss fashion brand Heidi is using technology in store to provide staff with instant access to customer histories when they ‘check in’ at the entrance. As detailed in chapter 2, this is treading the fine line between big brother and something that’s exciting and consumers want more of.

The emergence of mobile wallets, for one, is also likely to provide the ability to recognise customers as they enter the store, offer real-time rewards as they search and browse and then deliver bonuses as they swipe the device (as in the US coffee chain example in chapter 1).

This use of customer information is harder for some. The marketing director of a high street retailer explains his struggle: “I think the challenge that we have in our sector is that it is dominated by transactional information and we don’t do a lot of work at the moment in terms of marrying up the transactional information with the customer information. It is not helped by the fact that in our sector it is quite a low basket.

“If you have a high basket there is a much better opportunity to capture customer data – the frequency is lower but the transaction is much more significant.”

For those keen to leverage insight, including that from social media, there are huge benefits. But many seem acutely aware of the pitfalls too. The customer director of a digital retailer is striving for a “360° view” of his customers, from where he can push relevant data back out, but that can have hidden dangers. “For example, if a customer emails a complaint about a product, we need to make sure we don’t try to push that product by email to that customer who has just had a bad experience with it,” he says.

The commercial services director of a major retailer adds: “The worst that can happen if there is poor management of data is that customers become very frustrated.

“They can’t understand why we can’t see them as individuals irrespective of how they are interacting with us, whether it is online or offline. My job is to make our internal connections invisible to the customer.”

TREND SPOTTINGOne of the elements that makes big data ‘big’ is the less structured data f lying around. Videos, emails, photos and, of course, social media updates. Retailers believe that they are now seeing ‘the point’ of social media. Many brands are already using this data to help them micro-segment customers, but the next step is a much bigger one to take: it involves using social media sites to access data for sentiment analysis, which can then be integrated with retail point-of-sale data from tills to better understand how the way people feel about the brand translates into actual sales.

The results of the survey relating to management of product data versus customer data shows that this is clearly an area where retailers can improve – 80% feel they have a better handle on product data (see chapter 2). This will change but, as yet, there are few concrete examples of this meshing of data in action – at least in terms of sales uplift.

A market where a lot of work is going on is fashion. Talking about how she hopes to revitalise Harvey Nichols recently, incoming chief executive and former Burberry finance director Stacey Cartwright said it’s about “staying ahead of the

curve, anticipating what the customer might get excited by next”.

Prediction is invaluable. Given that data is the key to tracking any sort of trend, could it be used to predict fashion trends?

“Think about how we have historically traded as clothing retailers,” says the IT and ecommerce director of a clothing and accessories retailer. “We have managed our business around fashion risk. We didn’t actually know how successful a fashion range would be until we launched it. We have always been susceptible to range failure. What big data gives us is an opportunity to minimise that risk while still delivering newness in fashion retail.”

Some have already started. London-based software builder Editd collects and analyses retail sales numbers (transactional data) and overlays it with catwalk photographs and ‘fashion buzz’ from social media (behavioural data) to inform retail buyers about what’s hot and what’s not.

Input includes more than 2,000 blogs and 600 million opinions, plus 50 million SKUs. The potential is described in a recent blog: “Every runway image passes through our colour recognition software to build seasonal palettes visualising the exact weighting designers give to each colour trend across a season. Sometimes the fashion news headlines latch on to the most newsworthy shades, but in reality they weren’t the most-used, nor will they be the largest commercial tones. Instead, our retailers rely on factual information around colour.”

Input to insight“Storage is not a problem these days. The problem is to find insight from the data. And we are as guilty as most retailers in that we issue a large number of reports but many of those reports don’t have insight. It is my responsibility and my function to put a stop to that. But it’s a big task because this is a business that loves data and tables and the user is left to his own devices to extract what he wants from it. This should not happen. There should be experts defining what is important and what isn’t and what the insight is. What I want to do is turn the whole system around so that our data actually drives intelligence automatically out to key stakeholders. So the questions a business head may have will automatically be answered as part of the standard reports that we generate.”Chief operating officer of a fashion retailer

In the past retailers have worked with small amounts of data, relatively speaking. In 2014 the data set has been extended to what statisticians call ‘n=all’ – in other words, all the data. This volume of data comes with its own challenges, as discussed in previous chapters, but it also paves the way to digging much deeper. Big data can provide retailers with customer insight, allowing them to shape the direction of the business, the products it sells, when, to whom, how and, even, for how much.

For retailers, big data is providing customer knowledge and, in time, perhaps the power to predict.

Many argue that big data – in particular the use of personal data – is simply the modern-day equivalent of good customer service on a massive scale (see chapter 2).

The IT and ecommerce director of a fashion retailer explains: “Product continues to drive this business. And I can’t see that changing. But customer insight is increasing in importance because customers are using multiple touch points. In a bricks-and-mortar environment you could control your environment, but not anymore. Now it is a very complicated customer journey and you need a massive amount of data to interpret it.”

So where are retailers when it comes to using the data to offer the seamless, multichannel customer experience they are striving for?

O Massive transition taking place from collection to comprehension

O 87% rate preparedness to use data as five out of 10 or more

O Social data can offer future insight – but retailers must handle with care

O�Emerging opportunity to combine point-of-sale data with sentiment analysis from social media

O Gut instinct still a part of retail when it comes to data analysis

COLLECTION TO COMPREHENSIONThe first thing to note is that a massive transition is taking place: with regards to data, retailers are moving from collection to comprehension; some 87% rate their preparedness for this at five out of 10 or more (with 10 being completely prepared, see chapter 4). This has included a measure of spring-cleaning data. “There is a lot of data coming out, too much for many to cope with, and the art now is in constricting the amount of data that comes out so that only the really important and relevant data is released. So we are turning from data mining to data insight,” says the ecommerce director of a fashion retailer.

The chief operating officer of a clothing-brand retailer expands on this theme: “We’re going through a tremendous change in terms of consumer behaviour. And the level of data capture that takes place, compared with just a couple of years ago, is huge.

“We have to work out what to do with it and how to use it effectively to understand consumer

behaviour. How we do that is the next big question for retailers like us. Unpicking the data and turning it into something useful in terms of usable proactive activity is essential for retailers like us.”

There is a realisation that quality rather than quantity is the next stage to harnessing the power of big data for the retail sector. Many, like those examples above, have been “chopping stuff out” and “thinning data down”. This has made it easier to get at.

The chief executive of a pure-play retailer explains how a data warehouse has allowed all the information they have to be fed into one central depository “that we can then interrogate on a customer level”. This will, he believes, “make everything more palatable and accessible”.

GETTING UP CLOSE AND PERSONALFew would question the benefits of understanding customers better. It often takes significant investment to attract new customers and big data offers the potential to help retailers keep them by building a personal relationship with them.

As the senior vice-president for digital marketing and ecommerce at a clothing retailer suggests: “One thing we keep stressing to our teams is that data is at the centre of everything and if you don’t understand your business through that data [and] if you don’t understand your consumers through that data, then you will not be able to sell properly. We get a lot of

“WITH BIG DATA YOU ARE MAKING DECISIONS BASED ON WHAT HAS HAPPENED IN THE PAST. RETAIL IS THE ART OF KNOWING WHAT IS GOING TO HAPPEN IN THE FUTURE. YOU NEED PEOPLE WHO ARE LOOKING FORWARD”Commercial services director of a major retailer

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CONCLUSION: MORE DATA, MORE OPPORTUNITIES

CHAPTER 6

“WE HAVE HISTORICALLY MANAGED OUR BUSINESS AROUND FASHION RISK. WE DIDN’T KNOW HOW SUCCESSFUL A FASHION RANGE WOULD BE UNTIL WE LAUNCHED IT. BIG DATA GIVES US AN OPPORTUNITY TO MINIMISE THAT RISK”IT and ecommerce director of a fashion retailer

STATISTICS VERSUS ARTOf course, using data for prediction comes with a health warning – just ask a weatherman or the US credit rating agencies.

“Data-driven predictions can succeed – and they can fail,” writes the renowned statistician Nate Silver in his book The Signal and the Noise – the Art of Science and Prediction, which covers a number of prediction failures and possible solutions. Silver argues that predictions may be more prone to failure in the era of big data.

“With information and processing power increasing at exponential rates, it may be time to develop a healthier attitude toward computers and what they might accomplish for us.

“Technology is beneficial as a labour-saving device, but we should not expect machines to do our thinking for us.”

Retailers tend to agree that the rush to use predictive analytics to drive personalised solutions is not a panacea. “With big data you are making decisions based on what has happened in the past,” says the commercial services director of a major retailer. “Retail is the art of knowing what is going to happen in the future. You need people who are looking forward into the future. They can also make informed decisions but based on the art of retailing.”

The human touch is also a focus of an essay by Oxford professor and The Economist data editor Cukier and Mayer-Schoenberger: “In a world where data shapes decisions more and more, what purpose will remain for people, or for intuition, or for going against the facts?” they write, before proposing a “space” for common sense and intuition. This is certainly the case for retail.

Retailers interviewed for this report are also keen for gut instinct to remain core to their business decisions. The chief executive of a pure-play discounter explains: “We don’t want to get to the stage where gut feel, intuition and common sense are lost to us completely.

“What people do today is not necessarily an indicator of what they are going to do tomorrow. If I buy a pair of jeans today it doesn’t necessarily mean I love buying jeans – the jeans might be the only pair of jeans I buy in my whole life. So I don’t make decisions on data alone but the data informs my decisions.”

Social media can, of course, be a powerful tool in trying to second-guess customers. But most predictive models begin with history. Facebook and Twitter are relatively new, and the collection and analysis of data from them even more so. The data is also changing as fast as retailers are recording it which, as Silver recently noted, makes the whole process “a little bit trickier”.

That doesn’t mean it’s not worth trying. “We know who bought what and when but we don’t understand why. And that is the area we want to fill through the likes of social media, media data and surveying our own customers to find out reasons for purchase,” says the customer director of a digital retailer.

So, where does that leave retailers? The brand and ecommerce director of a fashion retailer perhaps best summarises it: “There is a lot of data but that means, one way or another, that you learn more about doing the right thing for your customers. It is important that data analysis is integral to every business decision but it also goes back to balance.

“I would worry if we became totally data obsessed because I know a lot of my best decisions have been on gut feel. And data was later there to

validate them. Some decisions should be made based on data but others on intuition especially for someone like me who is responsible for creative vision as well as ecommerce.”

He adds: “We do have cross-functional teams. For example we put a team together for Christmas. And that is a very good example of where intuition and data meet because in that team is someone from finance, who is data driven and understands the mistakes we have made in the past, and people who are totally creative.”

NEXT STEPS

O��Plan to take full advantage of all the staffing options available to you; leveraging consultants to learn best practices and recommend processes for your analytics projects; and leveraging combinations of in-house analysts and third-party partners to maximise velocity and agility.

O��An area many organisations struggle with over time is the implementation of agility. Our recommendation here to maximise results is for teams to invest in validation processes. In any given year, teams undertake the creation of segments, analytical explorations, quality initiatives, testing of client behaviours and expectations, engagement funnels, KPI definitions, etc, while these are rarely re-validated in the medium term – until it is too late and the window of opportunity has often already lapsed.

Data Domain Delivery

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this shift is already taking place in some businesses, with mention of ‘customers’ and ‘prediction’ replacing ‘products’ and ‘location’ as the most important drivers for retail profitability.

The big challenge now is how to turn information into insight. In fact, in 2014 retailers are not necessarily confused or inundated by data; rather they don’t have the tools, skills and capacity to turn it into something useful.

The particular function taking the lead in data management varies across retailers. In some cases IT is responsible, whereas in others it is marketing. For some, there is a mix and for a few every department is being made responsible for understanding and using that data.

What is clear, however, is that retailers want every part of their business to understand the opportunity that big data presents – from customer intimacy and product innovation to operational efficiency. For this reason, there is willingness for data to infiltrate every part of the business and guide how it works – but much like for customers, the data flow internally must be relevant and targeted.

This new phase of internal data sharing and heightened responsibilities for departments outside of IT, perhaps marks the precursor to retailers identifying entirely new business models that have customers rather than products at their heart.

Of course, in a world where numbers rule, the skill sets being recruited are also evolving. Technology can only take retailers so far – they need people to convert the data into relationships and insights. This could make retail a more attractive, dynamic career path for the new generation of data scientists – people with advanced statistical and mathematical as well as business knowledge. These experts are hard to find, which is why retailers are looking externally.

Outsourcing is an option that is being considered. The success some of the pioneers of customer data insight have enjoyed thanks to early partnerships with data houses is appealing. Sainsbury’s and Tesco are touted as examples of what can be achieved in data-driven businesses. Unsurprisingly there are also those who are reluctant to outsource.

Whichever way retailers turn, all see ignorance of translating data as business suicide.

Big data is creating more than a buzz; it is widely appreciated as an opportunity for retailers to understand their customers and their own companies better. It might even offer a glimpse of the future.

In trying to summarise where retailers are, and how big data will change the way they work, one particular observation from the IT and ecommerce director of a clothing and accessories retailer comes to mind.

“Big data changes the competence of your business model. Think how we have historically

Have a clear planOne in five retailers feel that clearer plans for leveraging multi-source data is the most critical thing that needs to change in their business with regards to data management.

“If you have to start with one [factor to change] it would be a clear plan of how you are going to deal with the data. Once you have a clear plan you will be able to educate people about understanding and utilising data, which leads to better data analysis, which leads to better cross-functional collaboration and more responsibility across the board for data management quality. And ultimately better understanding at board level.

“You see everybody these days understands the importance of data and using data, but it’s a bit like a hound trying to pick up a scent and looking in all directions and unsure where to go. You have to create a vision, a goal, a north star that everybody can get behind. It is only once you have done that, that you can set the wheels in motion.”Ecommerce director of a fashion retailer

traded as clothing retailers: we have managed our business around fashion risk. We didn’t actually know how successful a fashion range would be until we launched it. We have always been susceptible to range failure.

“What big data gives us is an opportunity to minimise that risk while still delivering newness. Pushing stock out, using your margin to protect you from fashion risk doesn’t work anymore. That model is no longer sustainable. Big data is all about equipping your business with the right tools so that you can trade intelligently.

“If you don’t have the skills in-house you have to outsource initially. And the great advantage [to that] is speed. At this stage the trick is finding the right partner – that partner will act as a catalyst to change process,” he says.

Big data is clearly a big priority for today’s retailers. Tomorrow will undoubtedly bring more data and more challenges, but with the right structures and skill sets to collect, analyse, share and use this new wave of information, the opportunities are endless.

Big data is coming at retailers from all angles, at increasing speeds, 24 hours a day. Their biggest challenge is how to sort what’s relevant to their businesses and their customers from everything else. It’s what Nate Silver, the US statistician and prediction expert, refers to as distinguishing “the signal” from “the noise”. This report has, to some extent, the same ambition.

Of course, when attempting to summarise the thoughts of leaders in retail from companies of substantially different sizes, at differing stages of development and competing in different markets, “signals” can be hard to spot. But they are there.

First to note is that this is new to retailers. New data. New ideas. New technology. New structures. New potential. Big data is much more than a “hype cycle”.

Retailers might be swimming in a sea of spreadsheets, but the attitudes towards data remain positive, with the board, staff and customers increasingly buying into the concept. Only 7% of those interviewed for this report, for example, feel that a better understanding at board level is one of the critical factors that needs to change in order for the firm to move forward on big data.

The retailers by and large are at similar stages,

O The board, staff and customers increasingly buying into the concept of big data

O Customer data will enable retailers to identify new trends and adapt offer accordingly

O Willingness for organisational structure to change as data infiltrates every part of the business

O High demand for the skill sets to collect, analyse, share and use this new wave of information

O New phase of internal data sharing and heightened responsibilities for departments outside of IT

with most at ‘preparing’ rather than ‘prepared’ for a new era of retail, driven by this new type of data. The volume of data is one of the reasons for steady rather than swift progress, with businesses grappling with a mix of structured and unstructured data. Some appear to be content with the technology and structures they have in place to pool the data, but very few are yet in a position to mine that data effectively.

Analysis paralysis has become synonymous with big data, and there are clearly challenges ahead for retailers, not least when it comes to customer data. The majority of retailers believe their approach to product data management is far ahead of that in respect of customer data. This isn’t surprising, and yet it is the customer data that could unlock the true potential of big data for their businesses.

Retailers are clearly excited by the prospect of understanding the habits of their customers, through their posts on Facebook, Twitter and through feedback and reviews. One retail executive mentions the example of a customer that is tweeting about moving house, opening up the possibility of targeting him with relevant products and services. This is tempered with perspective, given that what a customer says, likes

or does one day, might be very different the next. And tomorrow of course brings more data.

The mining of all this data won’t just open the door to more targeted marketing though – this could turn the way retailers have operated in the past on its head. Instead of products driving the business, customers will.

Vast quantities of customer data will enable retailers to identify new trends and adapt their offer accordingly. In other words, big data can make retail more reactive and personal – those that don’t use it effectively are also considered to be the ones that will fail going forward.

It seems that retailers are evolving from basic and anticipatory analytics to more predictive analysis. While the former provides a historic view, including what happened, where and how many times, the latter can help retailers identify causes and future trends. This shift in how data is used in business is creating a change in retail structure and, eventually, their business models.

Not many retailers appear to be at this stage yet – they are grappling with the nature of the customer data.

However, the majority think customer data is becoming at least as important as product data. There are even indications that

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Produced in association with eClerx

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