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What Your Workforce Can Tell You About Your Bottom Line

by Anke Doerzapf | SAPinsider

April 1, 2005

Many companies are not yet fully aware of what the data in your HR system can tell you about the health and well-being of your company’s performance. Learn how, with workforce modeling along with a more effective use of mySAP ERP HCM and SAP’s reporting capabilities, you can identify the specific workforce factors that are the better predictors of business performance.
 

Business analytics already plays an established and strategic role in business planning. But workforce analytics? That's another question entirely.

Many companies aren't fully aware of the wealth of data in their HR systems — and what it can tell you about the health of your business overall. But by asking the right questions, your workforce data can tell you plenty about profitability, innovation, ROI, sales, customer satisfaction, and efficiency. For many companies, achieving more comprehensive workforce analytics is the next challenge for a successful human capital management (HCM) strategy and deriving further value from their HR systems.

SAP customers working with HCM modules1 already have plenty of powerful, versatile reporting technology at their fingertips:

  • Predefined SAP standard reports and ad hoc queries, included in the HCM modules delivered by SAP, provide more tactical reporting capabilities

  • A robust and scalable data warehouse for strategic analysis and business statistics, SAP Business Information Warehouse (SAP BW), which, as part of SAP NetWeaver, forms the foundation of the SAP Business Intelligence solution

  • Additional warehouse management tools from SAP Business Intelligence (SAP BI) that let you integrate and store data from various sources throughout the organization and beyond — sources that contribute to strategic analysis and decision making

In addition, mySAP ERP, which is powered by SAP NetWeaver, includes the technology to extract, consolidate, and analyze HCM data in many different ways. SAP BW also provides Web cockpits and alert functions that make data and analysis tools readily available to casual users.

But with all these offerings, many companies are still not yet at the point of transforming their reporting capabilities into good use when it comes to analysis of their HR and HCM data. Many are still far away from treating workforce data as critical to the formulation and execution of both business and HCM strategy. However, this vision is achievable — companies simply need more effective utilization of mySAP ERP HCM and the reporting capabilities that SAP offers. And they need to develop the professional skills to know what they're looking for.

Which Data Do You Really Need?

With the solutions and technology in place to gather and access HCM data, you can then look carefully at these questions:

  • Which workforce-related KPIs have real business impact?

  • Do your HCM results meet or exceed industry or market standard benchmarks?

  • How can you formulate an HCM strategy and supporting initiatives based on this analysis?

  • How do you get an accurate picture of the impact of your workforce initiatives?

To help companies cope with these challenges, SAP customers often work with business consulting partners that specialize in HCM-focused analytics.2 These partners can help you set up a successful model for workforce analytics and make strategic use of your HCM data.

While we could discuss many aspects of workforce analytics, in this article we address just two of these areas and how they can help you measure human capital needs and their impact on business performance. We'll also look at how workforce analytics can be supported with your current HCM solutions from SAP.

Two Examples of Workforce Modeling

Despite 30 years of talk about workforce modeling, it's still not a common enough enterprise practice. So what are companies missing out on?

  1. Modeling of Workforce Shifts to Predict Future Needs
    Workforce modeling — for example, Markov modeling (see sidebar) — allows companies to quickly see the cumulative impact of hire rates, termination rates, transfers, and promotions over a designated period of 1, 2, 5, and 10 years.

    The first step in this modeling approach is to capture the company's current workforce profile and assess the cumulative impact over the forecast period at the current calculated rate. Companies can then model the impact of changes in career flows within the company: increasing or decreasing termination rates, developing new career paths, etc. From this, companies can see the cumulative amount of recruitment, on-boarding, training, and development needed to support this projected level of workforce movement.

    So why don't more companies use workforce modeling? Often, they simply cannot aggregate their workforce data into a format that can be effectively loaded into an appropriate statistical process. After all, when a company is still debating headcount, full-time equivalents (FTE), and termination rates for a given point in time, workforce modeling seems unlikely! Without accurate, reliable, and accessible data, companies simply have not been in a position to undertake this type of modeling. However, recent advances in HR systems, including SAP's, have gone a long way to reduce these traditional problems with workforce data.

    With the SAP standard reports and query functionality, you can easily extract a wide range of data for any point of time in the past or the present. For more detailed analysis, you would use SAP BW for observation of information like termination rates. For example, you could take a closer look at termination rates:

    • Over a period of time (e.g., the last 12 months, quarters, or years)

    • By checking a combination of HCM key figures, such as headcount, FTE, entry rate, and termination rate, together with financial information such as revenue, number of units sold, etc.

    • With SAP BI's planning capability, to project data according to defined formulas (e.g., termination rate increase of 18% by the end of the year)

    You can then use this data to model workforce movement. In addition, recent advancements in workforce modeling will enhance companies' workforce planning by taking current data and using it to provide projections of future workforce needs under various scenarios — something we'll cover in the next section.

  2. Using Models to Predict Human Capital Impact on Future Business Performance

    The single most exciting area of workforce analytics is the capacity to link workforce data with business outcomes so that any company can identify the specific workforce factors that are predictive of business performance for a particular company, business unit, or division at a given point in time. These factors can then become the most important drivers in determining people priorities and HCM strategic initiatives. Modeling your human capital enables companies to develop a systematic framework that captures the interrelationship between HR practices, human capital processes, and organizational performance. While the focus of Markov analysis is to show the movement of the workforce through the company, strategic workforce modeling shows the effect of HCM performance on business impacts.

    To undertake a strategic workforce modeling exercise, you must be able to frame the HCM questions you want to investigate. This typically involves identifying a suite of potential drivers of organizational effectiveness — such as promotion rates or training investment per FTE — and then forming this into a question, such as "Which of these drivers predict increases in profit per FTE?"

    The first step is to identify those business outcomes you want to research. These can go beyond financial measures — such as profit, profit growth, margin, margin growth, sales, and sales growth — to include measures such as customer satisfaction, occupational health and safety (OH&S), and innovation. Other business outcomes can be more company-specific, including: average turnaround time for aircrafts within an airline, amount of ore mined and shipped, claims processed, units produced, etc. The flexibility and capability of SAP BW facilitates the combination of HCM key figures with information from any other area of mySAP ERP — or even data from another source — in one query. This allows you to, for example, interface industry benchmarks with SAP BW for comparison against internal data. End users can then personalize the reports or queries by using alert functions; that way they have an easy-to-use tool for ongoing data monitoring. Figure 2 is an example of one company's model of possible profitability drivers across its company sites. This model is being used to analyze profitability in terms of turnover and customer service measures, and controlling for some local factors.

    The technique used in this type of analysis is Structural Equation Modeling, a very powerful multivariate analysis technique used for causal modeling. With Structural Equation Modeling analysis, it is essential to start with the right hypothesis to be investigated. For companies undertaking this type of analysis for the first time, access to some specialist consulting support from an experienced firm is recommended. Figure 3 below shows an example of scoping this model across 7 factors: employee satisfaction/engagement, voluntary termination rate, organization tenure, customer service, hire rates, customer satisfaction, and profitability.

    In Figure 3 we see the potential to investigate measures that might have either an immediate or a lagged impact on financial performance. For example, an improvement in employees' discretionary effort is expected to immediately impact customer service. However, if we had a change in the level of employee satisfaction and/or engagement, it would be some time (e.g., 3-6 months) before this would be reflected in a change in voluntary termination rates. Those responsible for undertaking heavy-duty analysis must use their knowledge of HR to assess the likely impact of time lags for each variable being analyzed.

    These types of analytic assignments can lead to some dramatic results. For example, in one retail company, store manager company tenure (not necessarily the first analytic you'd consider!) was the human capital factor most predictive of store profitability. In another retailer, seven human capital measures were identified that significantly predicted store performance, accounting for 30% of the variability in profitability per store. The company determined that employee engagement impacted store profit through its effect on customer satisfaction and voluntary termination rates. What's more, this analysis was able to predict the potential increase in store profit that would result from a one-point increase in the average level of employee engagement.3

    Due to developments in data warehouses and an enhanced level of HCM analysis, the opportunity now exists for this type of research to be undertaken in a very cost-effective way in any company. Again, with SAP BW, you can combine key figures from within your ERP system with external data on employee satisfaction (using queries such as employee satisfaction, employee tenure, and profitability of a store) to analyze the drivers for your business results.
What Can You Learn from a Markov Model?

This model (Figure 1) maps the recruitment transfers, promotions, and terminations from a retail company over a one-year period.

Figure 1 Markov Analysis

Let's look at the Sales Associates at ABC Retail. The totals show that for the Sales Associate role, 10,828 employees who started the year in that role were still there at the end of the year. During the year, 45,999 employees left the company from that role, 4,920 were promoted to Shift Supervisor, 73,744 new staff were recruited into that role, and 644 elected to move from Shift Supervisor to a Sales Associate role or were demoted.

Note that while only 18% of sales staff remained in the same role for the full period, 87% of district managers stayed in the same role for the full year.

From this information on workforce movements at ABC Retail, we can draw the following conclusions:

  • The high cost of labor turnover and product training for Sales Associates becomes self-evident.

  • The very high loss rate of Trainee Managers (59%) indicates a low ROI for any training investment for Trainee Managers. ABC Retail needs to develop interventions to improve retention.

  • ABC Retail needs a stronger focus on the career path to becoming a Store Manager, as it recruits as many external candidates (751) as Assistant Managers (750) for this role.

  • Since District Managers have relatively high levels of stability (87%), strategies should be developed so that they coach and mentor both new Store Managers and new Assistant Managers.

Figure 2
Predictive Modeling Exercise

Figure 3
Structural Equation Model

Conclusion

Over the past decade there has been a radical improvement in the efficiency of Human Resource Information Systems (HRIS). For SAP customers, this has occurred through increased functionality and expanded self-services, as well as the related reengineering of HR functions and the transition to an HCM-oriented approach.

The next challenge is for customers to make full use of this technology— to move to a more strategic orientation through the more effective and strategic use of HCM data. Companies can do this with a range of approaches — for example, using transactional-based benchmarking, which allows functional and demographic-based benchmarking, and using traditional industry- and region-based benchmarks, to show more demonstrable links between HCM performance and business performance through predictive modeling techniques.

In all of these evolving applications, the insight is not in the new techniques — it's in knowing how to position the workforce data that's already available in your HCM solutions, and using it with reporting options to achieve these outcomes. HR-oriented consulting specialists can help you implement these techniques and identify these drivers; SAP BW and mySAP ERP can help you gather and access the data you need to make these connections.

For more information on the analytics available in mySAP ERP, SAP NetWeaver, and SAP Business Intelligence, please visit:


1 Either as part of mySAP.com, mySAP ERP, or mySAP Business Suite.

2 InfoHRM (www.infohrm.com) is such a firm, specializing in planning, measuring, and reporting on HCM.InfoHRML offers benchmarking and related analytics membership programs, including CLC Metrics, with its partner, the Washington, D.C.-based Corporate Leadership Council.

3 This type of research is similar to the employee satisfaction-custom satisfaction-store profitability value chain published in the Harvard Business Review in 1998. See Rucci, A.J., Kirn, S.P. & Quinn, R.T. (Ja-Feb 1998), "The Employee-Customer Profit Chain at Sears." Harvard Business Review, 83-97.


Anke Doerzapf is a solution manager for mySAP ERP focusing on HCM, based at SAP Labs LLC in Palo Alto, California. She has worked for SAP since 1996, and was a product manager responsible for Compensation Management in Waldorf for three years. In 2001, she moved to the US to join the North American HCM Solution Management group. Anke is currently responsible for Manager Self-Services. She has a bachelor's degree in Business Administration — Human Resource Management.
Peter Howes is the founder and CEO of InfoHRM, a consulting firm specializing in planning, measuring, and reporting on HCM. InfoHRM has been conducting an HCM reporting and analytics membership program in Australia since 1991, as well as providing consulting services in HCM analytics and workforce planning since 1981. In 2002, InfoHRM formed a partnership with the Washington, D.C.-based Corporate Leadership Council (CLC) to offer this program on a global basis. Currently, InfoHRM and CLC Metrics have over 180 members globally. In 2005, InfoHRM and CLC Metrics are working with SAP to offer this program to the SAP community; this will include business consulting services to help customers make better use of their HCM data in an SAP environment. Peter has a business degree and an MBA, and is a Fellow of the Australian Human Resource Institute (FAHRI). He can be contacted at peter.howes@infohrm.com.

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