Are you using data to inform your HR Strategy?

“To get insight into the drivers of your economic engine, search for the one denominator (profit per x) that has the single greatest impact.”

Jim Collins, Good to Great

As Jim Collins describes in his iconic book ‘Good to Great’, data (both people related and business data) can play a critical role in providing the evidence you need to enable quality decision making and strategic planning. With this in mind, a key question for senior HR and OD leaders challenged to do more with less is: Are you using data to inform your HR priorities and decision making? If the answer is no, read on!

Last year we commented on the opportunities for HR and OD professionals in the emerging ‘Big Data’ trend. Barriers to HR embracing people analytics as an enabler of effective people decisions and investments are often cited as being capability driven (lack of deep analytics and interpretation skills required to test and validate cause-and-effect relationships) or data driven (poor systems and data leading to incomplete data sets). Whilst these are clearly important, our experience is that a mindset of enquiry, rigour and discipline – anchored in commerciality, is the ingredient most vital to people analytics work actually coming to life.

In a nutshell, what is people analytics?

People analytics is the science of linking people practices to business performance metrics in such a way as to understand which people practices are having the most impact on performance. In turn this data can then be used to model (and compare) the potential impact you are likely to have when you invest in initiative X, Y or Z. Put simply, people analytics is about building a sound business case and story to explain to the CEO why investing $2 million to redesign and launch a new performance management system will have more impact on business performance than spending $2 million on a frontline customer service capability program.

Whilst the rationale for building people analytics capability (hopefully!) makes sense, we have identified and ‘labelled’ three primary reasons HR and OD professionals typically seek to undertake people analytics work. With these in mind, you should be able to better spot situations that might benefit from a data driven approach.

1.     Validation

This is the situation where an organisation would benefit from validating a belief or assumption that is commonly held but is yet to have tangible analysis conducted to confirm if those assumption(s) are in fact correct. This can have huge implications for building a business case that requires significant investment.

A practical example of this might be the belief that the length of tenure and amount of training provided to employees has a direct effect on customer satisfaction and the number of complaints. Validating this one way or another could assist greatly in increasing / decreasing spend on employee training and on-boarding, as well as increasing commitment to the identification and actioning of key employee retention strategies.

2.     Myth-busting

This refers to those situations when ‘hard to pin down’ assertions are repeatedly used, become folklore and in some instances drive years of investment in a particular initiative or program without any evaluation of the actual (or relative) business impact being achieved. Continued support for an incorrect assumption means wasted time, resources and energy.

An example of this is where an organisation holds the assumption that moderate to high absenteeism levels within a particular business have and will always be a part of running that organisation. Further analysis could in fact identify the factors that cause spikes in absenteeism, leading to opportunities to address those factors directly. ‘Myth-busting’ can be made difficult in part by the fact that ‘myths’ can be hard to spot and test as they are simply ‘accepted practice.’

3.     Metric Isolation & Understanding

Metric isolation and understanding refers to the situation when you believe a key metric exists that has impact on multiple performance factors but you would like a clearer and deeper understanding of true and direct impact. Not having a complete view of the impact of a metric may limit the impact of activities designed to shift that metric, not properly linking it to all performance outcomes possible.

An example of this might be where you are unclear about the size and real impact of staff engagement scores with performance outcomes such as customer satisfaction, cost and safety. Getting a fuller picture can justify investment and prioritisation of lifting engagement.

What does it take to start people analytics work?

Strong analytical skills, as well as a quality data set are important to producing reliable and deep people analytics, but they’re not everything. We’ve listed below the top 4 things any organisation can do immediately to lift the quality of decision making in people strategy work.

1. Create a conceptual framework that links key business outcomes with people data. In this instance ‘conceptual’ means that it needn’t describe proven linkages between people and business data, but rather describe the hypotheses (i.e. beliefs!) key stakeholders in the organisation have about how people related activities link to key operational, customer and financial outcomes. As a foundation, this at least makes transparent the beliefs that are driving decision making.
2. If you’re unhappy with the quality of data at your fingertips to test beliefs in a framework such as the one described above, take the time to map the data points you would ideally have that would enable you to test your framework. Then audit what data you do have/are collecting, as well as what you need to begin collecting. Often we find organisations have a more useful data set than initially imagined and can do some good analysis at this point.
3. Recognise that somewhere in your organisation the skills to do great data analysis probably already exist. Finance, Risk Management, Actuarial and Strategy functions often have the skills you are looking for. However, it is incumbent on you to provide a frame (or a hypothesis) for those with skills to ‘test/analyse’. Without this, analysis work can be very inefficient, and if it leads to early dead-ends, risks losing momentum quickly.
4. Start small by simply gathering opinion based data through interviews of senior execs and staff. Data gathered on the health of key people metrics, coupled with a well-designed and facilitated strategy workshop/process that uses key criteria to help evaluate best options in terms of impact and cost, can inform valuable decisions.

The opportunity for HR and OD to have more impact on business performance through the intelligent use of data to make decisions is large. Added to that, the expectation of business leaders to see decision making that puts the organisation and people who enable it in the same data set is growing quickly.

Like to learn more about using People Analytics to drive HR Strategy? contactus@www.curvegroup.com