Impact of HR Analytics Powerful insight for real...

© 2013 Deloitte MCS Limited. Private and confidential.

Impact of HR AnalyticsPowerful insight for real performance


Introduction

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What we will cover today


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.


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

© 2013 Deloitte MCS Limited. Private and confidential.5 CPMO BP Workshop – Strategic change

Before rushing to prove the value of HR through analytics, you must follow

the basic rules of the road…


The current reality with HR AnalyticsWhere are people really at?

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* Bersin by Deloitte Research 2013


Rule #1 know your starting pointWhere are people really at?

7 * Bersin by Deloitte Research 2013


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?


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


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


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


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


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


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

© 2013 Deloitte MCS Limited. Private and confidential.15 CPMO BP Workshop – Strategic change

How to demonstrate the value of HR


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


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.

Email

Targets

Revenue

Orders

Salary

Benefits

Honours

Costs

Projects

Goals

Service

Volumes

Quality


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.


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…?


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


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.


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


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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This image cannot currently be displayed.

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


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


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


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


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


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


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

© 2013 Deloitte LLP. All rights reserved.

Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited (“DTTL”), a UK private company limited by guarantee, and its network of member firms, each of which is a legally separate and independent entity. Please see www.deloitte.co.uk/about for a detailed description of the legal structure of DTTL and its member firms.

Deloitte LLP is the United Kingdom member firm of DTTL.

This publication has been written in general terms and therefore cannot be relied on to cover specific situations; application of the principles set out will depend upon the particular circumstances involved and we recommend that you obtain professional advice before acting or refraining from acting on any of the contents of this publication. Deloitte LLP would be pleased to advise readers on how to apply the principles set out in this publication to their specific circumstances. Deloitte LLP accepts no duty of care or liability for any loss occasioned to any person acting or refraining from action as a result of any material in this publication.

Deloitte LLP is a limited liability partnership registered in England and Wales with registered number OC303675 and its registered office at 2 New Street Square, London EC4A 3BZ, United Kingdom. Tel: +44 (0) 20 7936 3000 Fax: +44 (0) 20 7583 1198.

© 2013 Deloitte LLP. All rights reserved.Member of Deloitte Touche Tohmatsu Limited33

Impact of HR Analytics Powerful insight for real...

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