How HR can unlock the treasure trove of workforce data

Gut instinct may be one way of making decisions in a crisis, but for organizations to thrive once this period of uncertainty has passed, HR leaders need to make use of workforce data to efficiently plan for the future.

The uncertainty created by the ongoing pandemic, combined with Brexit, is causing undeniable economic upheaval. In a moment where transformation is happening at an accelerated rate, having a clear oversight of the skills, knowledge, and experience of your workforce has never been more important.

Tapping into invaluable workforce data and using it to model for the future will guide the way to a future of work that the whole organisation can get behind.
Data will be instrumental in informing how HR leaders successfully design change across the business, and most importantly, deliver against the business objectives of tomorrow.

Gut instinct over data
As part of a wider research study we conducted with Vanson Bourne into decision making among business leaders across the UK (and the US), we found that most HR executives (84% in the UK or 87% in the US) in the past year have been making decisions based on gut instinct rather than data.

Although there are understandable reasons for this, including the unprecedented nature of Covid-19 and how this impacted the workforce, people data is extremely valuable to the business. Especially now that remote working is so prevalent.

So, why might HR leaders be overwhelmingly using gut instinct when making decisions and how can data be better utilized in these moments?

The need for speed
Despite HR leaders reporting there are more decisions to make, especially related to workforce planning, development, and costs, over half (55%) said that new technology makes people expect more immediate answers.

Making decisions is one thing, but making them quickly and confidently is another. In our research, the majority (89%) of organizations that felt they were taking too long to make decisions also said they were at risk of being left behind. Furthermore, 35% said their hesitation negatively impacts overall productivity.

To stay on the front foot, then, it would seem faster decision making is the answer. According to our research, organizations that have access to the right information are more likely to make decisions faster.

For many HR leaders, however, getting immediate access to the right data and research to inform urgent and imminent decision-making has not been possible during the Covid-19 crisis. It is in the moments where data is not accessible where gut instinct may be necessary. Instead, where HR can be utilising data more strategically is in planning what happens next.

Data unlocks the ‘what if’
The average HR department is sitting on a trove of data – information about employees, their skills, their opinions, their location, how they are interacting, and what competencies they see themselves needing in the future. HR leaders can, and should, utilize this data to ask themselves a simple yet crucial question – ‘what if?’

What if we moved to fully remote working longer term? What would productivity and culture look like then? Would this lead to a more dispersed workforce? Or what if we return to the office in eight months? What if we move into a new market segment? Do we have adequate capabilities and resources to support that venture?

Scenario planning against these types of questions by using workforce data will provide leaders with an unrivaled view of what they need to deliver long-term growth and transformation while also understanding where gaps exist right now. It will also help to provide a more considered approach to decision making that may have otherwise been made from the gut, or worse, as a knee-jerk reaction in a moment of crisis.

Tying back to business outcomes
Alongside the treasure trove of workforce data and using it to illuminate new ways of working by modeling different scenarios, perhaps the most important question to consider is how can this help deliver business outcomes and add real value’?

In a previous role, I led a project working with data scientists for an organization that relies heavily on its customer service centers. Data modeling allowed us to predict the employee factors that were linked to higher TNPS (touchpoint net promoter score), which we knew had a direct link to our bottom line EBITDA.

Honing in on a selection of characteristics such as the level of formal education and testing different hypotheses, our findings allowed us to predict, for example, that in certain markets customer service agents without university degrees drove higher TNPS scores. The findings required further research before a full conclusion could be made, however, it allowed us to question our existing hiring strategy from universities to customer services roles and help inform more targeted and strategic recruitment plans.

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