Deloitte Analytics: Moving beyond data rich knowledge poor in hr

Deloitte AnalyticsMoving beyond “datarich, knowledge poor”in Human Resources

Bring workforce intelligence into sharper focuswith advanced analytics What if:

• you could predict who was going to resign from yourorganisation and why… months before theytendered their resignation. Would it change thegame on how you manage and retain your highperformers?

• you could triage your CVs and score them on the flyas to who has the highest probability of being a highperformer, allowing you to deploy your limitedrecruiting assets to the highest return on investment.Would it change the perception of your recruitingorganisation from a reactive to a proactiveorganisation?

• you could manage your workforce costs on a daily/weekly basis and run different scenarios as the marketplace changes around you. And once youset a plan, monitor pay periods against key workforceperformance and business value metrics. Would itchange the conversation in the boardroom?

Senior executives are, in essence, flying blind todaywhen it comes to one of the largest expense items inthe P&L – the workforce – and the many relatedcorporate resources that support it.

Think about it. In many companies, the workforce is themost prolific user of real estate, information technology,and other key corporate resources. Between 40 percentand 70 percent of most companies’ operating expensesgo toward meeting compensation, benefits, and otheremployee-related expenses1. Yet beyond basic costfigures and employee demographics, senior executivesusually have little or no insight into how these expensesand resources relate to broader corporate issues.

In many companies, virtually every other area of theenterprise has been wired to “business intelligence”software and dashboards that help executives makecritical operational decisions about cash flow,manufacturing, supply chain, and financial reporting. So why is there such a giant blind spot when it comesto the workforce? How much more effectively couldexecutives manage the major assets of the business if they had visibility, at a very granular level, intoworkforce trends, performance, and needs?

A key challenge that forward-thinking executives faceas they try to elevate HR’s strategic value to theenterprise is this: although a wealth of workforce-relateddata resides in ERP systems, HR “point solutions,” andother repositories, businesses often don’t adequatelyconsider what to measure in order to link workforceactivities to broader business strategies, problems, andopportunities. The result is a gaping divide betweenpetabytes of possibly relevant data and the businessissues to which it might be applied.

Deloitte believes a way to bridge this gap – and tomake a gigantic leap forward in overall strategicplanning – is to adopt a top-down approach to“workforce intelligence.” Such an approach can helpyou focus first on identifying specific business issuesand then use advanced analytics to convert workforcedata and other inputs into actionable business information.

1 2008 Deloitte Consultingresearch based on multiple sources.

This approach could be as productive today relative toworkforce management as broader business intelligencehas been in the past decade. It can equip executiveswith a whole new dimension of decision-making power– a capability that addresses many of last century’slingering human capital challenges with 21st centuryspeed, adaptability, and focus on shareholder value.

New expectations, old challenges For the better part of a decade, organisations haveinvested heavily in large-scale enterprise systems topromote data-driven, strategic, and operational decisionmaking. In that time, the enterprise has re-engineeredcustomer relationship management, product design,manufacturing, and supply chain operations to gainefficiency and promote deeper analysis of corporatedata. Along the way, companies have learned ways tocapture and measure data at many layers of granularityto help guide decision making and identify areas inwhich higher performance can be achieved.

One area that has eluded such analysis andmeasurement in many companies, however, is humancapital. People-related costs can be one of the singlelargest line items of the P&L, yet the greatestrefinements in the HR function have been in itsadministrative activities, such as compensation andbenefits, on-boarding, and training.

Not surprisingly, an area that represents such a largepercentage of the P&L should attract the attention ofbusiness leaders and raise the question: How can weuse human capital more effectively in addressing ourcompany’s most pressing business issues today,including new product development, market expansion,and mergers and acquisitions?

We believe the answer to this question lies in theconvergence of several recent trends:

• A shift in HR leadership, both in terms of thebackground and expectations of its leaders. Often today’s HR executives have operationalbackgrounds and understand the need to better align staff-related functions such as recruiting,compensation, and employee development withcritical business activities.

• How technology is being deployed and leveraged,both in HR and across the enterprise. IT departmentshave spent years consolidating data repositories,thereby making much more data available tomanagement now than ever before – the questionoften left hanging in the air is how to use it most effectively.

• Increased use of advanced analytics tools and models.In the past five years we have seen exponentialgrowth in the use of advanced analytics to mine vastdata sets and identify previously unseen relationships.

From an HR and workforce perspective, a sizeable gapis created when the IT department announces that thiswealth of enterprise data about the workforce isavailable. The problem is that few managers across theenterprise are trained to mine this data for workforceintelligence – certainly not likely in the same way theyare for financial and operational data.

If, instead, senior executives were to identify specificworkforce-related issues that are critical to the business– we offer several examples in the following section –and then managers were trained in fundamentalanalytics so they could mine the available data moreeffectively, they could produce insights that should helpleadership with decision making. In this way, companiesmay very well see the same type of performanceimprovement rigour in HR that businesses have becomeaccustomed to in other areas of the enterprise.

Applying advanced analytics to the HR realm Traditional availability and uses of HR data (or lackthereof) make it difficult to distinguish betweenindividual employees or identify opportunities – forexample to enhance employee retention, coaching,and recruiting (see Figure 1 and examples that follow).

• Commercial

• Employed for 4 years

• Achieved 3 rating last year

• Achieved 3 rating 2 years ago

• Glasgow

Figure 1. Limited data and analytics limited HR decision making

Harry

• Retail




• Birmingham

Mary

• Corporate




• London

Sue

Key questions

• Who is most likely to refer a high performing

experienced hire next year? Why?

• Who is most likely to benefit from coaching?

Why?

• Who is most likely to voluntarily leave next year?

Why?

Traditional HR data sources and analytical capabilities limit the amount and granularity of information available to corporate leadership.

But by applying advanced analytics, the organisation can more effectively use available internal and external data to better understand and then more accurately predict future events at the customer or employee level (Figure 2). The concept creates value for the business by focusing resources on the right employees at the right time, to improve the outcomes (Figure 3).

• Promoted 2 years ago

• Worked 1,975 hours last year

• Worked 2,184 hours prior year

• 20 vacation days taken last year

• 19 vacation days taken prior year

• Supervisor achieved 2 rating

last year

• Medium supervisor turnover

• One past new employee referral

• Commute >25 miles

• Medium regional turnover last year

• Low regional economic growth

• Received recognition award

3 years ago

Harry

• Promoted last year






last year

• High supervisor turnover

• No past new employee referrals

• Commute 15-19 miles

• High regional turnover last year

• High regional economic growth


2 years ago

Mary

• Promoted last year






last year

• Low supervisor turnover

• Four past new employee referrals

• Commute <5 miles

• Low regional turnover last year

• Medium regional economic growth


last year

Sue

Figure 2. Expanded data sources and advanced analytics can improve management insight into workforce data

Predictive models built from many different types of data elements can quantify the likelihood of, and predict reasons for, futureindividual employee events.

Key Insight

• 25% more likely to benefit from

coaching

Top 3 Reason

• Static Rating

• Long commute

• Medium supervisor turnover

New action and benefits

• HR proactively calls supervisor

• Supervisor and Harry determine

coaching would be beneficial

• Coaching increases Harry’s future

value to company by > £60k

Harry

Key Insight

• 40% more likely to leave company

next year

Top 3 Reason

• Hours worked “above average” for

the last two years

• Supervisor’s past retention rate is

low

• High regional turnover rate


• HR proactively calls Mary

• Meets with regional manager

• Transfers to a different department

with new supervisor; Mary is now

only 10% more likely to leave,

resulting in > £30k benefit

Mary

Key Insight

• 75% more likely to refer successful

new hires

Top 3 Reason

• High number of past referrals

• Supervisor’s past retention rate is

high

• Hours worked “average” last two

years


• HR proactively calls Sue

• Sue is placed on company

recruiting committee

• Sue identifies three additional people

who are recruited into the company,

resulting in > £120k benefit

Sue

Figure 3. Greater insight can lead to new strategies for workforce development and retention

Though the three employees are similar in some ways, a closer look brings to the surface the different strategies managers can applyto engage these employees in new ways to bring greater value to the company.

Implementing a top-down approach, powered byadvanced analytics, can help corporate executives betterplan and forecast in core HR-related areas such as:talent retention, recruiting, workforce planning, mergersand acquisitions, safety, and span of control. Following are three examples of how advancedanalytics can fuel business-driven decisions in the HR space.

Staff retention A large retailer wants to improve its store profitability.Among the options the company considers are a newproduct mix, pricing changes, or updated stores. But after some analysis, the executive team discoversthat what differentiates the most-profitable stores fromthe least profitable is management turnover.

Further analysis shows that by reducing store managerturnover by just three percent, the enterprise can see asignificant increase in store profitability and, ultimately,earnings per share. Backed by this data, the retailerturns its attention toward a new goal: reducing storemanager turnover. Based on this goal, the organisationcan turn its attention to identifying factors thatinfluence turnover and how, then, those factors can be controlled.

Recruiting When online career sites became the job-searchresource of choice in the late 1990s, they revolutionisedcorporate recruiting. Web sites were soon followed by online systems that automated the applicant trackingprocess within human resources. But nearly 10 yearslater, most CVs submitted online must still be reviewedmanually by recruiters to capture the essence of anapplicant’s qualifications.

Much of this time could be used for other higher valueactivities. Moreover, faster review could help identifyhigh-potential candidates faster, possibly avoiding theloss of that candidate to a faster-moving company. By adding workforce intelligence modules to the frontend of automated systems, you can create a verydifferent approach to recruiting.

Take, for example, an open position for sales managerat a high-tech firm. If you apply advanced analytics to the firm’s performance management system touncover the attributes of the highest-performing salesmanagers based on your firm’s definition of and criteriafor “high performance.” Backed by data to support themakeup of a strong sales manager for this particularbusiness, you can apply it to the front end of therecruiting process.

When a CV arrives, advanced analytics systems cantriage them automatically, searching for those attributesyou’ve identified and showing recruiters whichcandidates have the highest probability to be effectivesales managers at the firm. What’s more, this advancedanalysis flags the candidates with attributes thatbalance the future needs of the company with whathas worked well from a talent perspective in the past.

Workforce planning A common challenge facing organisations is how to align revenue forecasts and product demand withworkforce planning. Given the cost pressures of the global economy, it’s even more essential to knowthe company’s true workforce costs down to the person and the activity. Because information inmany companies is still largely siloed by function, talentdecisions are often made without considering thoseforecasts – long or short-term. Advanced analytics canpair those pieces of information to help the enterprisemeet its financial goals.

You can use analytics for workforce planning inresponse to the ebb and flow of regional economicconditions. For example, a company might find that it has a surplus of managers in the Northeast but a deficit in the Southeast. A traditional response to thisscenario would be to ramp-up recruiting in the Southeastand hire more people. The costs of this approach aren’tmeasured solely in economic terms. The cost of hiringand onboarding, and the standard six-monthassimilation process takes a budgetary toll. Meanwhile,in the Northeast, employees in the same job family arebeing laid off. This process comes at a cost as well,including severance and outplacement expenses.

If the enterprise had better visibility into regionaleconomic forecasts, demand planning, and workforcedata, the planning process could be improvedconsiderably by moving surplus staff to the region withthe greatest need. Using advanced analytics, yourenterprise can better understand and predict not onlywhat the open positions are, but who should be inthose positions – and when.

Take the next step: identify burning issues thatHR can help address Facing the current trends in workforce demographics,growing skills shortages, and increasing competition for talent around the world, senior executives todayneed a better understanding of workforce dynamics.What is the likely make-up of our company from ademographic perspective in the next three to five yearsto keep the business competitive? Where will thosepeople need to be deployed?

What corporate resources will be needed to supportthem? How will those dynamics change over time, andin what ways can the business prepare to adapt?

If corporate leadership cannot readily answer thesecritical questions, they are effectively operating withblinkers on when it comes to this crucial area of the enterprise. The challenge is deciding whatworkforce issues need to be measured and thenbridging the gap between the vast stores of enterprisedata that may be available – especially that whichrelates to your workforce – and the strategic businessissues that your executive team needs to address.

By taking a more strategic approach to decision makingand using advanced analytics to turn HR data intoactionable business intelligence, companies can leveragetheir existing ERP systems, data warehouses, andsmaller-scale HR point solutions for critical insights intothe workforce. These insights, in turn can help guidedecisions that are critical as the business confronts arange of issues. We believe this capability is not a “nice to have” – it’s a “must have” going forward.

In many organisations, the first step toward thiscapability has already been taken: reinforcing andupgrading their IT infrastructure and then consolidatingand standardising data sources across the enterprise.

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The key to turning this infrastructure and the data it produces into workforce intelligence is the next stepthat companies need to take: implementing a strategicapproach by which senior executives ask the rightquestions involving HR and the workforce, and thenapplying advanced analytics to the data to find theanswers. Such an approach requires:

• Understanding and quantifying the human capitalcomponents of your company’s most pressingbusiness issues today.

• Formulating the key, strategic workforce-relatedquestions relating to these issues.

• Mapping these questions to your enterprise datasources – as well as external, third-party informationas necessary – to determine whether you have the information needed to find answers.

• Using advanced analytics to explore scenarios thatanswer the questions and address the risks andopportunities associated with the issues.

• Examining issues cross-functionally rather than bytraditional silos.

We believe that this aggressive, yet measured, approachcan help transform your HR function from “data rich,knowledge poor” into an indispensable part of yourenterprise that delivers powerful, actionable workforceintelligence to support growth, innovation and profitability.

Contacts

Richard HammellPartner, Deloitte Analytics020 7303 [email protected]

Howard McMinnPartner, Human Capital020 7007 [email protected]

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Deloitte Analytics: Moving beyond data rich knowledge poor in hr