impact of hr analytics powerful insight for real...
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© 2013 Deloitte MCS Limited. Private and confidential.
Impact of HR AnalyticsPowerful insight for real performance
© 2013 Deloitte MCS Limited. Private and confidential.
Introduction
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What we will cover today
© 2013 Deloitte MCS Limited. Private and confidential.
Business challenges which make Analytics a hot topicSeveral mega‐trends are driving the current focus on Analytics and Big Data and changing the landscape around decision making
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Profitable Growth - The need to remain competitive compels investment in Analytics and the tools to improve insight into financial, economic, environmental and market information. The goal? - more informed and responsive decisions.
Regulations – Regulators are demanding deeper insight into risk, exposure, and public responsiveness from financial, health care, and many other sectors requiring integrated data across the enterprise.
Hidden Insight - The growing complexity of global business has raised the stakes at all levels of decision-making. Facing more information than humans can possibly process, decision makers need more powerful tools for uncovering hidden patterns that may go undetected.
New Signals - Holistic signal detection from traditional internal and external structured and unstructured data plus voice, e-mails, social networks, sensor enabled facilities, products, instruments must be integrated and monitored for real time operational insight and decision-making.
Data Volumes, Velocity and Variety – Global data volumes continue to grow exponentially. New data sources, including social media and other “big data” types, provide an opportunity to gain additional insight and drive a need for new IT strategies, processes and tools.
Technology - Both a significant driver and important enabler. Rise of social computing, mobility, cloud and in-memory computing require new approaches. The good news, today’s computing capacity and analytical tools can meet the challenges.
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ACTIVITY 1What is your understanding and appetite for HR Analytics?
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App
etite
to u
se A
naly
tics
Understanding of Analytics
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Before rushing to prove the value of HR through analytics, you must follow
the basic rules of the road…
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The current reality with HR AnalyticsWhere are people really at?
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* Bersin by Deloitte Research 2013
© 2013 Deloitte MCS Limited. Private and confidential.
Rule #1 know your starting pointWhere are people really at?
7 * Bersin by Deloitte Research 2013
© 2013 Deloitte MCS Limited. Private and confidential.
Rule #2 – know what you want to analyseDepending on what needs to be decided or understood then different approaches are needed
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REVEAL ENHANCE MODEL
Descriptive statistics and visualisation
Predictive statistical models
and analysis
HR data
Enhance analysis with additional
internal or external data sets
Other internal data (eg finance)
3rd party data
(eg Open Data)
What is happening?
Why is it happening?
What will or could happen?
© 2013 Deloitte MCS Limited. Private and confidential.
ACTIVITY 2Are you aware of how mature your foundational elements are?
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Stage 1: Non-existent Stage 2: Developing Stage 3: Defined Stage 4: Advanced Stage 5: Leading
Enabler Capability Definition Questions to ask yourselves
Strategy & culture
Business strategy Identification and alignment of analytics functions to business and HR strategy and prioritisation of investments so that analytics is an integral part of informing business decisions
How is workforce analytics aligned to the business objectives of the organisation? How is analytics used to inform a business decision or approach business challenges?
Culture
HR strategy
Stakeholder engagement
Senior stakeholder management
The level to which senior and key stakeholders are engaged in the value of using data and insight to inform business decisions
Do C-suite level executives understand and value workforce analytics? How do other analytics or data driven functions coincide with workforce analytics?
Cross functional integration
Stakeholder engagement
Techniques
Data & reporting
Standards and management
Management and delivery of the data necessary to enable analytics decision support tools
What data do we need? How do we catalogue, manage and organise our data assets?
Metrics
Sources
Business case
Process & controls
Standards and documentationExecution of analytic decisions through the governance of business processes and controls
By which processes and controls should our analytics functions conduct business/Service level agreements
Project management
Technology & infrastructure
InfrastructureDelivery of replicable analytic process solutions using tools and technologies
What technologies and tools do we need to support our analytic capability?Integration
Tools
Capability
Internal communications
Attracting, retaining, structuring and communicating to an analytic organisation
How do we hire, retain, communicate and organise our analytic talent?
Talent sourcing
Capability development
Talent
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Foundation #3 ‐ Know and love your data
Workforce data is often not available. Business drivers do not dictate what data is collected and how.
Data sits in multiple repositories. It is not translated into a useful business format and does not correlate with critical business drivers.
Relevant, real-time workforce data needed to make informed decisions.
GAP
Market pressures
ProfitabilityCredit crunch
Customer demographic shiftsTechnological change
Globalization
Cost containmentGrowthShrinking workforceEvolving workplaceRisk and regulatory compliance
Company’s data repository
Translating data into a useful format
Having relevant data to inform decision making
Often there is a gap between available data and information required to address key business issues. A structured approach to data analysis can bridge the gap between data and business problems by providing a repeatable framework for achieving resolutions
Using data to enable better business decision making
Predetermined Workforce Solution Sets incorporate leading-practice lessons to provide leaders with the information they need to take action.
Existing internal and external data can be leveraged for relevant workforce data to populate the predetermined Workforce Solution Sets.
A top-down approach determines that business drivers dictate which workforce metrics are necessary to make informed decisions.
Workforce Solution Sets
Workforce planning and optimization
Recruiting
Workforce transition
Organization design and modeling
Training & learning
Leadershipdevelopment
Retention
Workforce productivity
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Rule #3 ‐ Know and love your data
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How can you successfully govern a vast amount of data?
How can you check the business has access to all the information it requires at the right time?
How can you ensure good quality data?
How should you manage long term storage of structured and unstructured records, whether electronic or physical?
How can you ensure security of personal data?
How to interpret complex and diverse international laws and regulations on handling personal information and complying with Privacy and Data Protection
How to enable effective data usage
What legal and regulatory frameworks apply to the storage and archiving of records?
What is master data management and how can this be applied to an organisation?
How can you migrate data successfully?
How to ensure accuracy and completeness of data?
Data Security
Information Exploitation
Data Integration & Migration
Data QualityData
suitable for Analytics
Data Governance
Master Data Management
The barriers to data governance and management
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Rule #3 ‐ Know and love your dataThe benefits of data governance and management
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• All data items have a business owner who monitors and polices quality• All data items have agreed definitions and standards communicated and
understood across the businessData governance
• Data quality standards are agreed and enforced• Improving the quality of data improves the Analytics ROI• Information and analyses are kite marked and trusted by the business
Data quality assurance
• Single view of diverse data sets available and integrated across systems• Redundant data storage is minimised, reducing cost and risk of corrupted
dataData integration & migration
• Data is available to right individuals in the right format in a timely manner• Access to information is self service based where required, quick and
very intuitiveInformation usage & exploitation
• The data is kept secure and access happens on a need to know basis• The organisation complies with all relevant regulation and can be positive
to keep their customers’ and company confidential information secureData security
• There is a full audit trail of all data manipulations• The organisation complies with all relevant retention regulation
Master data management –retention and archiving
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Rule #4 – Know how your culture will respondThe success of HR analytics within an organisation will depend upon the extent to which individuals commit to the idea of trusting in, and being aided by, analytics insight
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Is data considered an asset by leadership?
Does the organisation recognise the value of analytically driven
insight?
Do the organisation’s processes explicitly accommodate analytics?
Does the organisation invest in good quality data and analysis?
Are senior leaders well connected with analytical resources?
Are senior leaders advocates of analytics or sceptics?
To truly embed analytics, focus is required in 5 key areas:
1. Leadership for Analytics ensures visible senior executive sponsorship. Alignment and advocacy of analytics is critical to the success of change programmes.
2. Capability development involves identifying analytics capability requirements and devising a development strategy
3. Designing an analytics organisation to foster development, collaboration and innovation with the right balance of centralisation and proximity the business
4. Recognising analytical talent as a distinct talent segment and managing them in accordance with their growing importance with a distinct career model
5. Deploying a structured approach to manage change to ensure the success of any analytics programme or transformation, including a strategy for communications
The role of the HR Business Partner is to embed analytic principles into business
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Rule #5 – Bring it all togetherWhat are the factors driving an analytics approach?
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What outputs are required?What insights will drive value for
the organisation?
Are shared services the norm?
To what extent does organisation favour centralisation vs.
federation
Data management through to statistical modelling?
What roles will be undertaken under the banner of analytics?
Are management believers in the power of data?
To what extent do the organisation’s processes consider data insights?
Functional remit of
analytics team
Org Structure: Control vs. federation
Maturity of Data-Driven
Culture
Skills / team shape
Data architecture
Tools
Processes
Business requirements / value drivers
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How to demonstrate the value of HR
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Oil & Gas Major ‐ Ensured HR Business Partners understood analyticsHow well have you defined the role of your Business Partners?HR Business Partners must drive and protect value:
• Lead from the front
• Deliver strong end-to-end analytical support to influence decisions
• Integrate the Enterprise and drive tradeoffs
• Develop talent to create future business leader capabilities
• Manage risk using scenario planning, modelling and simulation
• Be the guardian of integrity and values
• Drive and protect value
• Innovate and educate
Challenging
Storytelling
Influencing
InnovativePro-active
Fast
Insight
Strategic perspective
Involved
Foresight
Intimacy x Credibility x Commitment = TRUSTRisk
ANALYTICS
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They realised the most important Big Data “V” is Value
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Info
rmat
ion
Dem
and
Info
rmat
ion
Supp
ly
Value-driven Strategies
Value Chain Execution
InformationAssets
Data Warehouse
Insights, Analytics &Measurement
Value Drivers
Improvement Levers
Data Sources
Decisions
Governance & Management
Manage Workforce Planning
Attract & Grow Future Talent Manage Mobility
Drive Employee Engagement
Manage Reward Mechanisms
Critical Workforce Segments
Demand Levels
Learning Portfolio
Performance Objectives
Assignee Criteria
Proposition Elements
Incentive Levels
Hiring Learning Survey SalesOrg D Comms Reward Planning HR Ops
Source
CV
On‐board
Skills
Courses
Scores
Culture
Engage
Comms Spans
Layers
ONA
Social M.
Targets
Revenue
Orders
Salary
Benefits
Honours
Costs
Projects
Goals
Service
Volumes
Quality
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Awareness Understanding Adoption Support Advocate Business Owner
• Senior Leader interviews to discuss priorities and objectives for rollout of the Analytics Academy in their part of the business
• Sponsor identified ‐ project objectives and vision for the project discussed
• Stakeholder mapping and assessment completed, working with business leads to identify the right managers to target for phase 1 of the Analytics Academy
• Sponsor signs off of the approach to be adopted and managers to be involved in the first cohorts
• Sponsor launches the Analytics Academy, driving interest in it, explaining the purpose and plan. Also explain how delegates have been selected and when others will have the opportunity to get involved
• Sponsor email to Line Managers explaining what the Analytics Academy is and what it aims to achieve. Email requests for them to speak to any of their teams involved in the first cohorts
• Invitations sent to the first cohort with request for pre‐work
• Materials developed for the immersive 2 day training session which include interactive sessions related to the pre‐work, external expert speakers, analytics trainers, and a structured case study which will inspire the development of individual development plans and pilot project idea generation
• Training materials aligned with content made available on the Digital Platform
• Buddies matched half way through the second day and supported with coaching
• Digital platform developed in alignment with the 2 day training session. Content will include: best practice analytics projects, tools and techniques for developing new analytics projects; and approaches to encourage and drive team engagement and interest in pilot projects.
• The Digital Platform will provide interactive portals and team forums to build on the cohort community developed on the training course
• Buddies encouraged to meet regularly and share progress
• Shell leaders provided with an opportunity to promote and role model the value of analytics to support data‐driven decision making, by presenting at the Analytics Academy Review and Reunion.
• Analytics Champion briefing and support materials provided via the Digital Platform
• Ideas and guidance provided for setting up seminars, Analytics Champion events and giving people visible opportunities to put new ways of working to practice
Corresponding communications & engagement activities to ensure understanding and drive new behaviour
… And then built…The Analytics Academy Leadership Experience
Inform Educate Commit
1. Identifying the right people to involve
John has been working at the company for 8 years and is confident in using the current reporting tools. He manages a couple of others to produce regular reports for the business.
2. Invitation to Analytics Academy
John is identified to join the first tranche of Analytics Academy delegates. His Line Manager explains what the Academy is aiming to achieve and that it’s a great opportunity for John to get involved with this new business initiative early on.
John feels excited about the learning opportunity but a little unsure about juggling the time commitment required of him. He is interested in what more he can learn about using analytics as he believes his team already does a fair amount of work in this area.
4. Adoption of the Digital Platform
Back in his day job, John enthusiastically describes his Academy training experience to his colleagues. He agrees a small pilot project with his Line Manager which will allow him to test a new approach in one of his monthly reports. He follows up the invitation to use the Analytics Academy Digital Platform and finds best practice examples, case studies and a forum to discuss his idea with others across the business. He keeps in touch with his buddy each month to share progress.
John, an upstream Operations Director
6. Sharing the knowledge with others
John uses discussion boards and forums on the Digital Platform in his role as an ‘Analytics Champion’. He finds that analytics has helped him make his day to day work more impactful and insightful. He attends regular Analytics seminars and is well known in his team for being the ‘go‐to’ person on analytic techniques.
• New Analytics community developed to create a buzz around the new ways of working
• Lessons learned exercises completed, including training session surveys and some focus groups as appropriate
• Positive reinforcing loops put in place to sustain behaviours and give managers the opportunity to practice and secure their new knowledge and experiences
• Leaders provided with opportunities to celebrate success with their teams
“I think my team are reasonably ahead compared to other teams in the company when it comes to
using analytics and making informed data‐driven decisions. We produce many reports which include lots of business data”
3. Training and relationship with Analytics buddy
John attends the 2 day Academy training course held in the iZone at Deloitte. He meets the other Managers in his cohort and together they challenge what analytics means for XYZLtd, where they are now (as individuals, teams & an organisation) and where they need to get to. They hear from experts, try new tools as part of a case study, and learn that targeted data interventions drive more meaningful results . They discuss how to drive better take up of Analytics and data driven decisions in their teams. They develop individual and team plans to pursue their pilot project ideas, and are matched with a ‘buddy’ to develop plans.
5. Six month Analytics Academy review & reunion session
John meets up with his buddy for a coffee before they are reunited with their Academy training cohort. The group share their stories, talk about what they have achieved against their plan from 6 months ago and what they have achieved in their pilot projects. They hear a XYZLtdleader talk about the value she has found in Analytics and are invited by her to become ‘Analytics Champions’, in their business areas, promoting the value of analytics for XYZLtd, sharing tools, best practice and approaches. John feels confident about working with others in his team to introduce more analytic led approaches to day to day decision making.
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A leading charity…challenged HR to think againThinking strategically about their responsibilities to support the wider business and leadership in making decisions, contributes to successfully executing the organisations strategy
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Customer / stakeholder expectations
Your role & responsibilities
Successful execution of analytical tasks
Preparing to Succeed Data Intelligence Decisions &
Actions Outcomes Strategy Execution
Situation and context
Strategic thinkers take a ‘broader view’ of the situation and context - seeming to look from
an ‘elevated position’ at the task in hand
Strategic thinkers put themselves in the shoes of their customers and stakeholders – to understand what they need to succeed
Strategic thinkers hold the
challenges of execution of
organisational strategy at the front of their
mindsStrategic thinkers influence and
support the decisions and actions that lead to successful outcomes
Strategic thinkers work towards meaningful and
impactful strategic outcomes
Strategic thinkers obtain and use data and intelligence as evidence
to influence and justify action
Strategic thinkers
consider how their role can contribute to
strategy execution
So how do we describe a strategic thinker…?
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Consideration needs to be paid to the overall business context, expectations from key stakeholders and the analytics practitioner’s responsibilities in preparing for successful strategy execution
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1. How does the task fit into the broader situation & context?• Organisational and business strategy• Trends (P.E.S.T.)• Evidence of current priorities for the business• Similar historical instances
2. What are the expectations of the task (& outcome)?• Role of the business stakeholder and how they will use the analytics findings• Level of responsibility and ability to make decisions of business stakeholder• Clarifying expectations from you and next steps based on your
recommendations
3. What is your role in relation to the task (and others’ roles)?• Understanding your role and the insights you can provide with the analytics findings• Understanding the support opportunities you have from other teams• Mapping dependencies• Clarifying governance / escalation paths
…and focussed on building the capability to analyse
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A Learning Provider Linked measures to monitoring capabilityOrganisations increasingly need to see data in a more real‐time format
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Spreadsheets are no longer sufficient — we need colour, shape, movement in space and time.
Tools and techniques have improved and put the data into the hands of the business user – The goal is to bring the analysis closer to the decision makers.
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Activity 3 ‐ Creating analytics dashboardsOur experience has led to the blueprint for success to create a best practice and fit for purpose dashboard
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1Start somewhere
4Information
overload
6Plumbing required
5Looks are important
2One size does
not fit all
3Begin with the
end in mind
Blueprint for
success
1Start somewhere
4Information
overload
6Plumbing required
5Looks are important
2One size does
not fit all
3Begin with the
end in mind
Blueprint for
success
Assess technology needs
Avoid analysis paralysis
Plan on multiple versions and
phases
Have a vision and a strategy
Present the right metrics and data
Visual design impacts a dashboard’s effectiveness
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A Retail Bank decided it had to put a ROI on talentThe availability and use of data to prove the relationship between HR initiatives and business outcomes enables greater measurement of value and ROI.
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How a Self Organising Map (SOM) model segmented the population of Relationship Managers
Distribution of High Performers (Top 25% Performers ‐ #)
Distribution of Low Performers (Bottom 25% Performers ‐ #)
Distribution of all RMs
Red/Orange: High Performers Yellow/Orange: Mid Performers
Blue: Bottom Performers
Scale:: Performance :RCS+CES Nov’11 Sample population: RMs N: 120
• Shortest tenured RMs, majority between the age of 21‐30 with a high representation in the VIC/TAS region.
• This group also has the second highest percentage of RMs that have previously worked in FS with a majority of them coming from the branch/retail network.
• The lowest number of relationships within a portfolio, and a lower level of total footings (ranked 4th) but slightly above average avg. footings/relationship.
• They have a reasonably low level of customer migration in and out of the portfolio indicating low levels of new business and a very mature client portfolio.
• They are self‐motivated and very driven. They value individual success more than team success.
• They are more customer focused, emphasising customer relationships and satisfaction, as well as farming, as a main priority.
• In terms of culture, they have the largest gap between the expected focus on the customer as well as the perceived culture and focus on product sales.
• Furthermore, their emphasis on their own work individuality is seen through their low satisfaction rankings on colleagues, but high rankings in regards to professional development and financial rewards.
• RMs are on‐par with the average level of engagement. They are motivated by professional development, financial rewards, career opportunities and their colleagues.
Example:Profile of Segment 2 ‘ Individual Success’
The bank went for segmentation ahead of major restructure
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Each segment profile was translated into a tracking dashboard that allowed HR to monitor how the performance of each segment improved following the introduction of tailored initiatives and programmes
Case Study: Segmentation ahead of major restructure
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26CPMO BP Workshop – Strategic change
Other examples of how to use data insights for current or future business
need
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ACTIVITY 4Analytics and the impact on HR value creation
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Leve
l of H
R v
alue
cre
atio
n
Analytical Capabilities
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The compass of analytic activityDifferent types of data insight can bring about many benefits to an organisation
28 Historic Future Focused
Summary of historic data visualised to support
discussion and evaluation relating to past performance
Accurate forecasting and modelling of key
components across the HR
scorecard
Continuous process of scanning data to
understand and prompt significant
changes in the current status
Understanding the intrinsic and extrinsic attributes of current
workforce to optimise impact of resource
management
Mat
ch
ForeseePresent
Prom
pt
Monitoring Services
ReportingMetrics
Profiling Workforce
Predictive Modelling
Business Engagement
Valuefrom
Insight
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Case example – Reporting metricsA global financial services organisation wanted to leverage their data, accelerate their access to analytics and report on their people to understand the potential organisational savings they could make
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Benefits• Enabled quick, dynamic and rigorous organisational as is assessment, for identifying
organisational issues & informing OD design
• Showed the organisational structure over time, attrition and allowed customised peer analysis of structures between different countries and business units
Headcount visualisation by geography
Customisable peer analysis of country headcount by grade
Tool was also accessible via iPad
Although designed to be intuitive, a user guide was provided to explain some of the more complex features
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Case example – Profiling workforceA global mining company predicted clusters of employees most likely to suffer safety events
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Benefits
• Identification of which employees were most likely to suffer a safety event down to area, location, shift, demographic and time
• Reduction in safety events through targeted interventions
6 times more likely to suffer a
safety event
Male 25% older than average
Appears to have lost
work satisfaction
Accidents are
expensive
Almost 300% more severe
Often happens on 7th day of a 7-day roster
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Case example – Monitoring servicesFollowing $56m investment in leadership training, an organisation wanted to measure the effectiveness and business impact of training
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• Combined and analysed a broad set of existing workforce and operational data
• Quantified relationships between training spend and business outcomes
• Identified capability gaps in the organisation and which training programmes would most effectively tackle those gaps
• Enabled re-direction of training spend to areas which would have the greatest impact on business outcomes
Benefits• Secure executive sponsorship through ‘hard’ evidence and dispel myths in the business
• Inform Training demand planning based on business risk, rather than appetite
• Redirection of £30m spend to areas where it will have the most impact
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Case example – Predictive modellingA multinational oil and gas services company applied predictive capabilities to identify leading indicators of voluntary turnover for identified talent segments
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Benefits• Can proactively focus on individuals 1.5 – 3x more likely to leave in the future
• The predictive model can be used to understand risk segments across the globe
• Can be used to target both individuals and pivotal groups e.g. staff across departments
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