implementing an analytics capability in a business context · 2019-01-19 · insight driven...

Implementing an analytics capability in a business context

Presentation to IRMAC

Tom Peters, Partner, Deloitte LLP, January 16, 2018

© Deloitte LLP and affiliated entities.

Opening Remarks – Deloitte’s Transformation

What’s the challenge: The Insight-Driven Organization (IDO) – (start with the video)

– The five key Building Blocks of an IDO

– The Analytics Maturity Curve – Towards IDO Status

– Results from the 2018 Canada/US Survey on Analytics Maturity

Where do businesses continue to struggle: Building capabilities in Analytics

From Small Data to AI: Where to from here – some trends/considerations.

Agenda for Today

Implementing an analytics capability in a business context | PAGE 2


Deloitte AnalyticsWe pride ourselves on being able to ‘disrupt’ ourselves…

Deloitte’s continues to grow professional services into emerging technologies

Real timeCustomer apps

Customer ExperienceM2M

Internet of Things(IoT)

Exponential Technologies

Artificial IntelligenceCloud for real-time application developmentProcess automation & RoboticsCyber securityDesign thinkingData Ecosystem

Applied Advanced AnalyticsBig Data ApplicationsCustomer InsightsPerformance MarketingFinancial EngineeringAnalytics Strategy - Insight Driven Organization

Omnia AI

DeloitteDigital

Analytics Applications

Strategy

Gartner Magic Quadrant*

Deloitte Analytics Canada started 2010 –Now over 500+

Omnia AI – launched June 2018. Started with over 300 professionals

Deloitte is a recognized leader by Gartner for last 3 years on ability to execute

Deloitte Digital Dedicated practice in Digital Transformation

* Source: “Magic Quadrant for Data and Analytics Service Providers, Worldwide”, Gartner (February, 2018)


Removed for contract compliance


The Insight-Driven OrganizationEmbedding Analytics into the business


Using data to solve business problems is not new

What’s new is the growing exhaust of seeming “real-time” data and the advance in technology (infrastructure and methodology) available – and it has changed the game!

Investments in building an analytics program/function within an organization will fail if care is not taken to understand why it matters and where in your business that you can show value quickly

Science experiments will just not do!

Implementing an analytics capability in a business context

The Challenge

The challenge is – Where to start?



Deloitte’s Point-of-View

Becoming an Insight Driven Organization (IDO)

IDOs have a defined vision of how data, analytics and digital can be used to add value throughout the business



What is an Insight Driven Organization?

Becoming an IDO relies on the fundamental building blocks of Strategy, People, Process, Data and Technology…

PROCESS

TECHNOLOGY

DATA

STRATEGY


PEOPLE


Each building block represents an action or subset of actions to address the business challenges highlighted in the themes.

The essential five building blocks for your IDO journey

Becoming an Insight Driven Organization

Process Demand &Prioritisation

ProcessRe-engineering

Agility & Scalability Governance Benefits

Realisation

Technology SolutionArchitecture

Vendor Management

Sandboxing&

Industrializing

Cloud vs. On Premise

Security, Reliability &Continuity

DataData Quality

&Management

InformationModel &

Data Sources

Regulation &Compliance

Ethics & Sharing

Data Monetization

People Talent

Change Journey & Decision Process

Leadership Knowledge Management

Organization Design

Strategy StakeholderManagement

Analytics Vision Innovation

Value Drivers &

Business Case

Operating Model



The journey to becoming an Insight Driven Organization passes through 5 stages

Insight Driven Organization Maturity Curve

Most organizations are between stages 1-3 A handful are beginning to reach stage 5

Aware of analytics, but little to no infrastructure and poorly defined analytics strategy

Adopting analytics, building capability and articulating an analytics strategy in silos

Expanding ad-hoc analytical capabilities beyond silos and into mainstream business functions

Transforminganalytics to streamline decision making across all business functions

Data Driven Insight Driven

Stage 1

Analytically Impaired

Stage 2

Localised Analytics

Stage 4

Analytical Companies

Stage 3

Analytical Aspirations

Stage 5

Insight-Driven Organization


Industrializinganalytics to aggregate & combine data from broad sources into meaningful content and new ideas


Data-driven companies have seen tremendous returns to shareholders

Increased Value of Data-driven Companies


Source: S&P Capital IQ, “Top 10 Companies with Highest Market Capitalization Worldwide” (https://www.bcg.com/en-in/publications/2017/digital-transformation-transformation-data-driven-transformation.aspx)

NOTE: Market capitalization figures have been rounded and are in $Billions

RANK APRIL 2017 Q4 2011 Q4 2006

1 Apple: 741 Exxon Mobil: 406 Exxon Mobil: 447

2 Alphabet: 585 Apple: 376 General Electric: 384

3 Microsoft: 505 PetroChina: 277 Microsoft: 294

4 Amazon 432 Royal Dutch Shell: 237 Citigroup: 274

5 Facebook: 408 ICBC: 228 Gazprom: 271

6 Berkshire Hathaway: 404 Microsoft: 218 ICBC: 255

7 Exxon Mobil: 344 IBM: 217 Toyota: 241

8 Johnson & Johnson: 330 Chevron: 212 Bank of America: 240

9 JP Morgan Chase: 303 Walmart: 205 Royal Dutch Shell: 226

10 Alibaba Group: 278 China Mobile: 196 BP: 219 Data-driven company

COMPANY MARKET CAPITALIZATION

https://www.bcg.com/en-in/publications/2017/digital-transformation-transformation-data-driven-transformation.aspx


Who’s winning on Analytics?Findings from the IDO Maturity Survey


We surveyed executives and senior managers from 200 organizations across the US and Canada. We used our IDO framework as the basis of the research.

Harnessing analytics goes well beyond technology

The IDO Maturity Survey

85% of analytically mature organizations exceeded their corporate goals in thepast 12 months, compared to 67% of less mature organizations.

Only 1 in 20 Canadian organizations consider themselves Insight Driven Organizations –well below the US (17%).

Our survey found that business analytics is the most important business priority over the next few years for organizations in Canada.

Approximately 50% of Canadian Organizations have started their journey….

Retailers and FSIs lead the way in terms ofanalytic maturity among Canadian organizations.



Canadian organizations are investing in the pillars and moving up the maturity curve, but it’s a slow process…

IDO Survey Findings within Pillar: Tracking Canadian Results 2017 & 2018

2017

2018

65%

56%

Canadian Organizations that lack dedicated analytics team

Process

14%

17%

Canadian Organizations that have a centralized innovation hub

Technology

92%

82%

Lack overall data governance capabilities within their organization

Data

63%

Canadian organizations that lack a formal C-Suite level analytics leadership

53%

People

20%

30%

Stakeholders are aligned on the vision for analytics and supportive of the journey to become insight-driven

Strategy



A Case Study in Mid-market Retail

Becoming an IDO takes time and experimentation: Be Agile

Value Delivered

Estimated $6M annual savings during Phase I

Automated forecasting increased team efficiency and reduced forecast error by 50%.

Flyer development cycle increase to 14 weeks out from 4

Provided the foundation for a future analytic roadmap

Approach & Solution

Phase I: ROI analysis at SKU level across three years of historical data

Phase II: Build and Pilot a flyer forecasting system

Phase III: Launch Web-based forecasting solution for flyer optimization

Company Situation Company had a mandate to

increase profitability They spent +$77MM to fund flyer

promotions with no ROI measure

Lack of analytics capabilities

Forecasting was based on “what they did last year”

Challenges to overcome: Align management on value of a

data driven approach - Marketing, Sales, and Finance

Adopt a new flyer development process

Improve data architecture

Phase I: Proof of Concept

Phase II: Forecasting Pilot

Phase III: Managed Solution



Biggest Pain Points?Building capabilities – People, Process, Leadership


To become an IDO, organizations need to take a hard look at the

four levers that can accelerate the

development of sustainable analytics

capabilities

Where the rubber hits the road….

Building Capabilities


LEADERSHIP

More than 37% of US organizations indicate that they have a formally mandated leader.

Only 22% of Canadian organizations have same.

OPERATING MODEL

27% of US organizations

9% of Canadian organizations view analytics as a living eco-system or

operating model.

CULTURE & CHANGE MANAGEMENT

US organizations are 3x more likely than Canadian organizations to indicate they have invested in cultural change management to a new way of working using analytics.

TALENT & CAPABILITY DEVELOPMENT

34% of US organizations and

20% of Canadian Organizations view analytics skills as essential from

the board room to the front office.


Chief Analytics & Data officers are now seen as key players in transforming their businesses into insight driven organizations.

Chief Financial Officer

Chief Executive

Officer

Chief Operating

Officer

Chief Risk Officer

Chief HR Officer

Chief Marketing

Officer

Chief Analytics Officer

Chief Data Officer

Chief Information

Officer

Chief Digital Officer

Leadership and the Boardroom of the future


Data, analytics and digital expertise make their debuts at the boardroom table…


Or at least some…63%of Canadian companies do not have C-level Analytics Leadership


Analytics Leaders need to be…

Transformation-savvy executive sponsors who are influencers capable of leading by example and who hail from key business functions that are driving growth and profitability

Leadership matters…


Reality Check:

Despite years of investment in technology and data, organizations that select sponsors primarily for their technical/analytical skills do not become IDOs, or fail altogether.



Purple Teams

Business & Communication

Technology Alignment

Macro-Perspective

Business Knowledge

Business Commentary

Soft Skills

Technical Capability

Testing & Validation

SQL querying

Data Modelling

Data Analysis

Reporting Software

Success also hinges on an organization’s ability to create Purple teams

Red skills: technically-savvy people + Blue skills: seasoned business communicators

Combining STEM and Business Acumen

The skills and capabilities of your people



Business Analytics CapabilitiesDelta between mature and less mature organizations

Macro-Perspective and Business Acumen 30%

Demand Generation and Strategic Thinking 26%

Insight Activation 25%

Project Management 24%

Business Commentary / Storytelling 20%

Insight Assessment 8%

Data and Technology Literacy 7%

Technical Analytics CapabilitiesDelta between mature and less mature organizations

Data Quality Assurance 23%

Data Analysis 22%

Technology Solution Development 20%

Data Modelling 17%

Data Engineering 15%

Visualization & Design 14%

Data Discovery 5%

3.65 / 5 3.58 / 5

Capability Levels

5 = Leading

4 = Advanced

3 = Defined

2 = Developing

1 = Non existent

Source: Deloitte 2018 IDO Survey Results

The biggest capability gaps between mature and less mature organizations reside with blue capabilities

Analytically mature organizations have well balanced Red and Blue teams.

IDOs build balanced teams with slightly stronger blue capabilities



Functional Centre of Excellence

ConsultingDe-centralized Centralized

Pros

Cons

Functions have complete control over needs

Resources concentrated where they are needed most

Resources remain close to business

Clear tracking and measurement of outcomes

Central management and deployment of resources

Limited enterprise collaboration

Limited ability to expand and scale in other functions

CoE may not be able to control decentralized staff

Results dependent on who can pay vs. needs

Potential for gaps in understanding of business needs

There is a spectrum of organizational models

Organizational Design – Sample Models

Sweet spot



Getting to insight is made easier when there is a deliberate process for asking the right questions, getting the right information, and having the right execution to drive to value

Analytics Process – Getting to Insights

Discovery

Data Preparation

Analysis Planning

Analysis Execution

Communicate Results

Operationalize


Identify value opportunity

Drive to Value


Netflix: A Mature IDO

The role of data and analytics for Netflix


https://www.youtube.com/watch?v=nsFqPYHpjdU


Starting the Journey: Lessons from best in class IDO’sGetting started is hard, but those who have started or even completed the journey would say that leadership needs to see ROI on analytics investments before it proceeds!

1. Start with your leadership…identify the core “crunchy business questions” challenging your business

Lastly, think like an IDO!

2. Establish a team and mandate to execute a proof of concept…key is to keep it small with fast turn around. Show value to quickly to gain alignment.

3. Agree on success metrics and governance mechanism to ensure consistency and clear interpretation of findings.

4. Have a communication strategy to socialize findings across company – this creates an imperative for cultural change – “all decisions are data driven”


From Small Data to AI…Where is this all going?


Technology drivers are democratizing Analytics and AI for business use…

The evolution of Analytics

Data mining

Visualization Tools

Managed Analytics

Natural Language Processing

Internet of Things

Machine Learning

Digital Enterprise

BI/Reporting

Telematics

Artificial Intelligence

Deep Learning

“small data” Analytics Era

Cloud computing

Big Data Era Artificial Intelligence Era

Open-source Predictive Analytics tools

Hadoop/MapReduce

Social Media Listening

Incr

ease

d Acc

essi

bilit

y by

Bus

ines

s

Inflection point on real-time data processing and

deployment


Marketing Research


My take on the trends emerging from the Big Data Fog….

Privacy and CyberSecurity

The explosion of data from online activity, personal mobile devices, and IoT sensor technology has challenged lawmakers to keep pace…the public is demanding action here.

Rise of Autonomous Things

Vehicles (not just cars), production lines, and AI-driven cloud-analytics and software development allowing some data science available on-demand for the masses.

Artificial intelligence

AI applications will be jet-fueled by research advances in Quantum computing, Reinforcement and Deep learning technology...and use cases and applications will grow at light speed

Digitally Connected and Enabled • Digital twins in the enterprise to facilitate

production maintenance and monitoring, • Immersive technology for consumer

marketing, and employee training, and • “Smart places” (home, work, enterprise)

Sources: Deloitte LLP, and CIODive, “Gartner's 10 technology trends for 2019 and beyond”, Oct 22, 2018


Let’s hear from the experts…

What is AI? Programs that can act, interact and understand using machine learning algorithms that improve over time

Reasoning(Pattern matching and optimizing)

Interacting (Communicating and sensing)


https://www.youtube.com/watch?v=YRzGSp_bO1M

Prediction Machines: The Simple Economics of Artificial IntelligenceAuthors: Ajay Agrawal, Joshua Gans, and Avi Goldfarb


Some progressive traditional companies are already embracing AI technologies – Financial Institutions and Retail are the most progressive.

IDO’s strive to embrace new technologies to allow them to become more prescriptive!

Where to from here…


Emerging companies are built on Analytics and AI foundations…decision automation differentiates their business

https://www.titanvest.com/

TechCrunch Headline – Oct 31, 2018:Scared to trade stocks? Titan algorithmically invests for you

https://youtu.be/YRzGSp_bO1M?t=4


Microsoft and Kroger to challenge Amazon and Whole Foods with futuristic retail technology

The companies today are unveiling new pilot stores near their respective headquarters in Redmond, Wash., and Monroe, Ohio, featuring smart shelves with digital displays that update prices dynamically and show personalized icons to help shoppers find items they’ve put on their shopping lists. The shelves will help also help workers identify items to fulfill curbside pickup orders. Geekwire, Jan 9, 2019.

AI and real-time data are changing consumerism forever…

Where to from here…


CPGs Leverage Digital to Fill Grocery Carts Online, In-StoreCPG companies and retailers have made significant strides in meeting consumers’ digital expectations, but the effort to become truly omnichannel is ongoing. “Consumers are shopping long before they enter the store,…Digital is a complement and not a substitute for in-store shopping.”

Abigail Slark, senior manager at Deloitte Consulting LLP; Wall Street Journal, Oct 15, 2018


The future of work…the Analytics talent war will continue

Final Thoughts: The impact of Advanced Analytics, ML, and AI on work…

McKinsey, 2017• Almost $15 trillion in wages related to job activities in

the global economy have the potential to be automated by adapting currently demonstrated technology…. While less than 5 percent of all occupations can be automated entirely using demonstrated technologies.

• Activities most susceptible to automation involve physical activities in highly structured and predictable environments, as well as the collection and processing of data.

https://www.mckinsey.com/featured-insights/employment-and-growth/technology-jobs-and-the-future-of-work


Other good reading:

Deloitte -https://www2.deloitte.com/insights/us/en/focus/technology-and-the-future-of-work.html

Brookings Institution -https://www.brookings.edu/book/the-automated-society/

https://www.mckinsey.com/featured-insights/employment-and-growth/technology-jobs-and-the-future-of-work

https://www2.deloitte.com/insights/us/en/focus/technology-and-the-future-of-work.html

https://www.brookings.edu/book/the-automated-society/

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implementing an analytics capability in a business context · 2019-01-19 · insight driven...

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