Six steps to double the business value of HR data and metrics: part 1

In the first of our two-part series exploring HR data and metrics, Nick Kemsley from the Centre for HR Excellence at Henley Business School looks at the first three of six practical steps any HR function can take to double the business value of the information they are providing to their business.

As CEOs and boards push to squeeze maximum value out of their organisations, the need for insight to guide their decision making and to manage both short and longer term risk has never been greater. Recent research by the Centre for HR Excellence at Henley Business School has validated the importance of this in the minds of senior HR and business leaders. Leveraging data and metrics is seen as a significant challenge by more than 90% of those surveyed as part of this research. As a result, HR departments and their functions have been put under increasing pressure to re-examine the way in which they use people and organisational data.

HR functions need to focus on providing insight – not just information – to help align metrics to business goals and to examine outcomes at least as much as processing metrics, and they can do this in six simple steps:

  1. Identify the insight needed to underpin strategy delivery and manage organisational risk.
  2. Understand the decision-making data your board needs to support shorter-term performance.
  3. Determine the critical gaps between information and what you currently provide.
  4. Find the most pragmatic way to plug the gaps.
  5. Optimise the format that the data is presented in.
  6. Develop the right skills to analyse and talk about the data.

Identifying the insight required to underpin strategy delivery and manage organisational risk

The question to ask: “What are the organisational risks that can impact strategy delivery, and what is the best way of validating and monitoring them?”

The key words here are organisational risk. Instead of asking “what data do we have which we would like to present?”, we instead need to deduce the type and format of data and metrics that will best support an understanding of organisational risk. When your CEO and CFO talk to analysts, shareholders, potential investors and your employees about the strategy of the business and make promises about performance, there can be no confidence that any of it will come true without a solid understanding of the organisational risk – every business has a strategy. What ultimately differentiates the winners from the losers is the ability of a business to activate strategy through organisation.

For example, if your business strategy hinges around the acquisition of a more innovative, creative type of person in key areas, then strategy delivery depends on your ability to put these specific skills in place at the right time in the right quantity. Your CEO simply wants to know if this is going to be easy or hard to do, whether or not it is likely to affect any of the growth promises made, what is happening to mitigate any risk and if these activities are on track.

You need to know if supplying against this skills need poses a significant risk, if you have the downstream talent supply pipeline to attract this kind of person and if you have the internal culture to retain them. This may require changes to reward processes, the flexible working policy, supplier choice and employer branding – all of which means you need to start the work before these things are actually needed. Going forward, you will need to share data on your effectiveness in hiring these specific skills, how employer perception is shifting and how retention is improving – perhaps at the expense of sharing the earth-shattering news that the percentage of women versus men in the organisation has not changed radically from last month’s figures.

It may be that this organisational risk analysis has already been completed in your organisation, but chances are that if you haven’t done it, it hasn’t been done. The key deliverable for any HR director is a comprehensive view of how people and organisational risk is being managed in the context of the strategy. Yet often, what HR functions present to their boards does not speak specifically enough to the strategic plan, and in some cases it is hard to find a meaningful link at all.

If you wish to gain a top-level view of the organisational risks relating to the strategy, apply an organisational model such as the Seven S Framework, which is based on Japanese management and was developed in the 1980s, or similar. It doesn’t matter which one you use as they are all broadly similar, but it should allow you to interrogate your strategy/business plan and make a decent stab at the following questions:

  • What are the organisational implications of the strategy on resources, structures, facilities, systems, processes, skills, behaviours and employee engagement? This gives you a picture of the key strategic enablers your organisation needs to deliver to support its strategy.
  • How do these implications compare against current capability, where are the biggest gaps and which are the hardest to bridge? This draws out the critical organisational risks.
  • How do these compare against existing support function strategies? This helps you iterate and align HR and IT strategies to better address these risks.

Understand the decision-making data your board needs to support shorter-term performance

The question to ask: “What things are front of mind for your senior decision-makers right now, and what data, in what format, will add the most value?”

The role of organisational data and insight here is less about strategic risk and more about supporting decision-making and trade-offs. Get a copy of the last three board meeting agendas, talk to senior leaders and use the experience of your HR director (who usually sits in these meetings). What are the top five decisions/issues that they are debating now, and what about in the next six months? What people and organisational data and insight are most relevant to these decisions?

For example, a global technology business is below plan for quarter-end EBITDA (earnings before interest, taxes, depreciation, and amortisation), and there is an upcoming IPO offer (sale of stock by a private company to the public). The board is looking at ways to cut costs in short timescales. There is discussion about making some of the sales force redundant. The HR director, who is commercially-minded, comes to the board meeting armed with some data on pending recruitment assignments, their costs and criticality to business goals. HR has already done some top-level analysis to identify which roles should be considered non-critical and the cost-avoidance benefits of putting recruitment activity relating to these roles on hold or looking for an alternative route to fill the gap. This is shared as a recommendation, and after a brief discussion about a couple of the roles, it is agreed. The business has found a practical route to cost avoidance in short timescales and the HR director has helped the business avoid an action which would have damaged its ability to deliver longer term. A good result.

Determine the critical gaps between this and what you currently provide

The question to ask: “How does this top-down need compare with what is currently presented, and where are the critical gaps?”

Most HR functions provide a pretty standard pack of “HR data” – something about staff turnover, statistics on sickness and absence, diversity information and the like. This is all good stuff, but if this is all that we provide, how does the leadership of the business get the insight it needs concerning specific organisational risks to the business strategy and decision-making support for important shorter-term performance issues as outlined in the above two sections?

Much of the information that we present is just that – information – and can be hard to relate to specific issues. At the same time, some of this information is a regular update on something which simply doesn’t change very often, such as the gender profile within a business, and is backwards looking. The opportunity, having gone through the two exercises so far described, is to consider gaps in:

1. The data itself Are we presenting data that is not very relevant at the expense of data that is? Do we have gaps in our data portfolio that we need to plug? Do we have data already that we are not leveraging? Are we presenting outcome data and linking to process where needed? As a general rule, the value of process metrics and data is in working out why an outcome is not happening. It is essential to have process metrics, but these should come second. For example, a financial services organisation measures its succession planning process. It is very pleased to report that, for its top 200 roles, it has “ready now” successors identified for 98% of these. It is reporting to the board that succession planning is “green” in terms of risk categorisation. However, when an outcome-oriented question is asked – “When a vacancy arises in the top 200, on what percentage of occasions is it filled by the individual identified as a successor?” – the answer is only 8%. Now, it is clear that the succession planning process is not working.

2. The way we are synthesising data How does the business use trends, projections, correlations and ratios? Are we getting underneath the data to understand what might be happening and what it might mean? Are these insights clearly tied to what is important to the business? Often, the insight is to be gained by a correlation between outcome and process metrics or between leading and lagging metrics (those showing a good performance against hoped for outcomes and those trailing behind that), but rarely does it come purely from process or purely from lagging. Yet this is often our approach. For example, a public-sector HR organisation is under pressure to spend more and more money on a particular type of training, when it is not convinced that this is the major influence on the risk it is trying to manage. Time and again the organisation has found it impossible to convince the business leaders, who are reacting to pressure from regulators. Data relating to incidents is plotted on a graph against training spend over a period of three years. This graph shows that when training was first introduced there was a noticeable decrease in incident frequency, but that this effect has not increased beyond these initial levels despite a four-fold increase in training spend. Other data suggests that an expansion of staff induction processes carried out in local areas has a far greater impact for no additional cost. As a result of this insight, HR goes to the leadership team with a recommendation to re-allocate some of the training funds to other areas.

3. The accuracy of our data How up to date is it? Is it accurate enough to support decision-making? For example, an HR function is challenged on an organisation’s people costs. There is a suggestion from the CFO that contractor costs are a key factor. The HR director is asked to come back to the following week’s meeting with data on the issue. They return to their team and discuss the problem. It soon emerges that HR has very little up-to-date information about the number of contractors in the business, what they are paid and how these rates compare with the market. The reason for this is that the use of contractors has sat with managers locally through the use of external agencies that are not controlled by HR, which has a focus on permanent hire. It takes nearly three months for HR to gather the relevant data and put in place controls to monitor this going forwards, damaging its credibility significantly.

The second part of this article will look at the remaining three recommendations for examining and pragmatically overhauling HR’s approach to data and metrics. If applied, they will help HR to develop insight and lay out what opportunities an HR function can take to add real business insight through data, and therefore build its own credibility.

Nick Kemsley is co-director of the Henley Centre for HR Excellence at Henley Business School.

Using data and statistics more effectively

This article is the latest in a series on using data and statistics more effectively in HR:

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