HR metrics is something a lot of practitioners struggle with, but proving HR’s worth in hard statistics is often the only thing to turn an executive’s head. Keith Rodgers looks at the evolution of HR metrics and how Workforce Business Impact can assist HR professionals in quantifying traditionally soft measures
HR metrics is something a lot of practitioners struggle with, but proving HR’s worth in hard statistics is often the only thing to turn an executive’s head. Keith Rodgers looks at the evolution of HR metrics and how Workforce Business Impact can assist HR professionals in quantifying traditionally soft measures
While most organisations are content with the way they handle the basics of HR measurement, many struggle to link those metrics to the wider business. A recent Webster Buchanan Research workforce intelligence survey of senior finance managers, however, found that they had a lot to say about the state of HR metrics.
Sixty per cent of respondents thought they were better than average at measuring absenteeism – but only a third could say the same about measuring the business impact of absenteeism, and another third confessed to being poor or even very poor at doing so.
An introduction to Workforce Business Impact
Establishing this link between traditional people-related metrics and broader business drivers is fundamental to any human capital management strategy. As the HR function strives to find a voice at board level, the ability to present workforce issues in a relevant context for CEOs is becoming increasingly important – a way of thrusting people-related issues to the top of the agenda and reinforcing HR’s business credentials. This combination of business context and board level relevance is what is termed ‘Workforce Business Impact’ analysis.
None of this is to demean the stature of classic HR reporting. Metrics such as days-to-hire are key indicators of HR operational efficiency, while absenteeism statistics and other collated data provide useful comparators, both to measure against historical performance and to compare with external benchmarks. But Workforce Business Impact analysis takes this kind of data to the next logical step and provides a deeper insight into the underlying trends and meaning. It doesn’t just measure absenteeism rates – it measures what absenteeism costs the business in terms of bottom line profit, employee morale, opportunity cost and so forth.
Much of this impact analysis rests on an organisation’s ability to tie together different pieces of information – information that they may already hold in-house. For example, most organisations retain data relating to employee performance, built around individual performance appraisals and group performance against departmental targets. Likewise, every organisation retains information about what salary, bonuses and benefits they pay each employee. The problem is, many struggle to link the two sets of data together to ensure that compensation is closely tied to individual and group performance. Part of the difficulty is cultural – but part of it is also down to basic data management. Too often data is held in disparate, unconnected systems or simply stored on paper.
Measuring the impact of voluntary employee turnover is a great example of how workforce intelligence can be investigated at multiple levels. In a high-turnover environment such as retail or call centres, single percentage point reductions in retention rates can have a significant impact on the bottom line and on other business priorities such as customer service. But if they’re able to measure turnover at all – and given the difficulty many large enterprises have in establishing current headcount, that shouldn’t be taken for granted – most organisations have tended to assess it in relation to historical patterns and industry norms. While it’s useful to know whether percentage rates are climbing or falling, this kind of information is really only an indicator of volume.
The next stage of analysis would set out to establish how much pain that absence is causing the business – whether it’s in the form of delays in product development, reduced coverage of the sales prospect base, longer wait times for customer service or any other business-critical metric. It should ultimately be possible, in broad terms, to start to establish what types of employee turnover are causing most problems for the business. This kind of information allows organisations to prioritise their investigations into the causes of absenteeism and introduce remedies.
With each of these kinds of analytical exercises, the aim is to provide indicators and parameters – it’s not necessary to do a comprehensive, detailed audit. While many in HR approach HCM analytics with trepidation, the reality is that Workforce Business Impact analysis is rooted firmly in logic and often guided by anecdotal evidence. Most organisations already have some understanding, for example, of where employee attrition is hitting them hardest, and that allows them to prioritise their initial analytical projects. As with so much in HCM, pragmatism is the watchword.
From an IT perspective, these analytical exercises rely on an organisation’s ability to collect, pool, analyse and distribute a wide range of data, both from HR itself and elsewhere in the business (such as finance and customer-facing departments). Historically, take-up of analytical technologies has been relatively low, especially in comparison to the finance department, but that’s starting to change. While some analytical applications, particularly in the field of modelling and forecasting, are still the domain of early adopters, there’s no doubting the fact that improved reporting and analytical capability is fast rising up the HCM agenda.
Prospective customers are now starting to look at what’s on offer from the supplier of their core HR Management Systems, and in some cases, are also checking out what specialist business intelligence vendors like SAS Institute and Business Objects have to offer in this space. Where organisations are deciding whether to upgrade or switch platforms, analytical capability is becoming an increasingly significant component in the decision-making process.
Reporting capability considerations
Broadly speaking, there are three levels of reporting capability to consider. Firstly, in terms of pure HR reporting, most suppliers bundle a wide range of reports with their core HR management systems, all of which feed off a central HR database. These tend to focus on traditional HR metrics such as absenteeism rates or turnover. The quality of data coming out of the applications will largely be determined by what goes in, so the level of process automation within the organisation will be important – the more that’s automated, the more electronic data will be generated. This data can be accessed and analysed in multiple ways, using standard reporting tools to run ad hoc queries and pre-built reporting templates that vendors provide with their applications.
From a product selection perspective, there are several differentiators in this field. Firstly, the breadth of pre-built reports will be important. Some high-end vendors offer hundreds of reports ‘out-of-the-box’, so it’s worth checking out what’s on offer and how closely they fit your needs. It’s also important to bear in mind that ‘out-of-the-box’ can be a misnomer –most reports will require some degree of configuration. The important factor here is ease-of-use – if that configuration work has to be handled by a product expert (or even the IT department) that can increase the cost of implementation.
The second level of reporting provides deeper, richer insight into HCM issues, sometimes provided in specialist applications that are purchased as separate add-ons. These provide a wide range of insights, including:
• Deeper insight into HR process efficiency.
• Analysis of core HCM drivers such as retention, designed to help organisations identify and track high-performing employees.
• Performance management applications, designed to align individual or group performance with corporate objectives. These include applications based on the principle of the balanced scorecard.
• Workforce planning applications, which help organisations to map current and future need for skills and competencies.
• Modelling technology, which allows companies to carry out ‘what if?’ analysis. While take-up is low, some experts believe that predictive analytics will form the next wave of adoption.
The breadth and indeed depth of functionality within comparable products can be telling here. While take-up of these analytical tools may be relatively low, many of the products have evolved over years and are in advanced stages of development. PeopleSoft, which is broadly recognised as a pioneer in the space, launched its first Workforce Analytics applications more than five years ago.
The third level of reporting becomes critical for Workforce Business Impact analysis because it pulls in data from non-HR systems, such as financials and increasingly, customer management applications. It’s here where there’s some divergence in approach between vendors. Where organisations have standardised their core applications on the same vendor’s software platform, it’s easier to pull data together. Oracle, which favours a ‘single platform’ strategy for applications, has made this the centrepiece of its analytical efforts, focusing on data generated within its transaction systems and providing web-based self-service through what it calls Daily Business Intelligence. That makes it simpler to implement analytics and allows for faster deployment, although in practice most organisations will also need to import data from third-party systems.
Another approach is to build a separate central repository (or datawarehouse) to store data that’s sourced from a variety of different systems. These warehouses come with a range of tools to help customers both manage and manipulate data and usually contain pre-built metrics, but it’s important to bear in mind that this can be a significant IT undertaking.
While it’s helpful to divide the analytics market up into these different levels, they don’t necessarily correlate chronologically. Just as it’s a mistake to think of analytics as the second phase of an HCM strategy after process automation – the two should actually go hand-in-hand – so it’s important to see the full range of analytical software capability as a menu – or an armory – that can be selected from at will. Different organisations have different business priorities, and second and third-tier applications could generate significant business benefit in specific environments.
Keith Rodgers is co-founder of Webster Buchanan Research, a market intelligence company specialising in human capital management. Email: [email protected] or visit www.websterb.com.
