"Imagine the data we will create in the next five or ten years."by
Tom Marsden is CEO of analytics company Saberr. He is an entrepreneur with experience in strategy consulting, talent management and finance. As a company Saberr help people make better decisions about their people through data.
1) Even though HR has been using the term Big Data for ages, HR data is not voluminous, varied or fast enough to be truly called Big Data. Do you agree?
The term big data is overused, particularly in HR. The challenge isn’t the size of the data sets. It’s making sense of all the permutations of things you could analyse. Having said that, the size of data sets is increasing fast. 90% of the data in the world has been created in the last two years. Much of it through social technology. Imagine the data that we will create in the next five or ten years! In the not too distant future we will be dealing with big data in HR. That will be a fun challenge.
2) Give us three golden people insights that HR gain access to when they can truly make evidence-based decisions?
The key thing is that you focus on insights that are relevant for your business goals. Three issues that often arise are:
- The drivers of attrition and absenteeism. If you understand the drivers of attrition and absenteeism you can save large companies millions of pounds. But how many companies have a real insight over which populations are leaving or absent and the real drivers? It’s true - this kind of analysis has been around for years but still isn’t applied enough.
- The ingredients of a high performing team. When hiring new employees most companies focus on the “visible 50%” - hard skills and experience that we can read from a CV, probe at an interview or in screening. But what about the “invisible 50%”? Can we understand an employee’s personality and the fit with the organisation or job? Or more importantly, how their values are likely to connect or clash with other team members. We have evidence to prove that a proportion of this “invisible 50%” is quantifiable. Hiring managers can use data to assist in better hiring decisions.
- Skills gaps in the future workforce? This is more complex because it involves large amounts of variables. Discuss and understand future business scenarios with business leaders. At the same time extrapolate current workforce skills based on current trends. Nine times out of 10 when you compare the two you will end up with insight about a skill- gap that you need to address.
3) You say you're passionate about connecting an organisation's strategy with talent agenda. Can you give us a rich example of how do to this and the effect it can have?
Think through the human implications of what you are trying to achieve.
If you are a high growth technology company, talent acquisition may be of fundamental importance. Should you offshore part of your business to maximise benefits of wage arbitrage and tap into global skills? If you do offshore, how will you ensure that effective collaboration continues between teams? Can you make use of virtual workers available through e-lance to avoid fixed costs? How do you bind this disparate workforce together with a coherent vision?
If you are a large, global employer you may want to simplify structures and make your workforce more responsive and agile. You might focus on reducing organisational complexity. You might introduce tools for collaboration and change incentives so that individuals think across boundaries.
The effect that it can have is well documented. One study found those with the best relevant talent management practices outperformed the rest by eight times on total shareholder return (Hay Group’s Best Companies study).
4) It's 2020. What about the data/evidence-based HR analytics industry is exciting you the most?
It may sound strange but I think the debate about data privacy is fascinating. There is huge investment in wearable technology and the Internet of Things in the workplace. By 2020 we will have the opportunity to capture data we never thought imaginable.
We will be able to understand how humans interact on a real time basis and the correlation with performance. At the same time some employees have the increasing fear of a Big Brother enterprise. Winning applications of HR analytics will be founded on trust. Individuals will allow trusted organisations to borrow their data because they see a benefit in doing so.
5) How should companies go about getting everyone bought into the concept of a single source of truth?
First, have a view on what data needs to be clean and why? Cleaning up every HR data point feels like the “punishment of Sisyphus” or “painting the Forth Bridge”. Be realistic.
Second, have a master data management plan. This includes the process, governance, policies, standards and tools to manage the critical data. Third, where possible let individuals share in the benefits of a single source of truth. Give individuals back useful information so that they see the merit of keeping their records up to date and accurate.
6) What are the three biggest challenges you consistently see companies having when moving to data-led decision-making?
First, know where to start. The myriad of different areas that one might investigate can lead to paralysis. Our advice is start small and build. Second, find data across silos.
To create insightful and actionable reports you need data from across the enterprise. Third, find sponsorship and source skills. You need executive sponsorship and the skills of a data scientist to generate most impact.
7) How can HR lead the cultural change to a more data-led decision-making culture? What has defined the success stories among HR Directors who have spearheaded the change?
The reality is that HR is playing catch up to many other departments (finance, logistics, operations and marketing) in developing a data-led decision making culture. But HR Directors can take encouragement from a new breed of success stories in applying data analytics.
Well known examples like Google are being matched by innovative HRD or Talent Leaders we have worked with at Thomson Reuters and Capco. What characterises them? They are not afraid to start. They are connected to or are from the business. They are patient. They are trusted. We find that leaders in this field can inject optimism into the project so that everyone recognises that data can be used to make our working lives better.