Why You Should Apply Analytics To Your People Strategy…

Applying analytics to your people strategy seems like common sense. Today. But in recent times past, ‘HR’ was often considered the softer side of an organisation. The department that made decisions based on intuition and little, if any, hard data.

I recently listened to this episode from The McKinsey Podcast about the importance of applying analytics to your people strategy. The podcast is hosted by McKinsey’s Global Director of Digital Communications, Simon London, and was aired on the 25th April 2019. It’s a topic we’ve discussed recently, which you can take a look here and here.

Today, I’ve provided a synopsis of this podcast episode from McKinsey, as it demonstrates the power of bringing advanced computing and analytics capabilities to people strategy decisions, in order to drive lasting organisational change and to boosting the bottom line.

Extracting real value from people analytics:

The podcast episode featured an interview McKinsey partners Bryan Hancock and Bill Schaninger who believe that to extract real value from people analytics, the following requirements are paramount:

  • Technical insights and capabilities
  • A solid understanding of organisational behaviour
  • A good grasp on how the business actually makes money

people strategy

The central premise: if the organisation can capture and analyse data about its ‘people’ (of which there are many facets and layers) and use that information to make better business decisions – decisions that actually go beyond its people strategy – all things being equal, the performance of the organisation will lift.

This was a critically important outtake for me. It directly correlates the potential power and impact of well-informed, strategic people decision-making on the performance of an organisation. Which sure, to my point at the start of this article, is increasingly a ‘thing’ in today’s corporate landscape (albeit, not ubiquitous but certainly growing). But with true objectivity in mind, don’t you think we’re a little late? Why has this taken so long? It hasn’t. Simple as that.

The McKinsey folk explained…

The concept of people analytics isn’t new. It’s been around for a long time. There’s nothing radical about the idea of applying data insights to help organisations make better people strategy decisions. But in the past, the technology was limited for this to be achieved in a way that was simple, straightforward and meaningful. Now, not only has computing power advanced exponentially, but it also allows organisations to do more with the information.

Think about this:

Bryan Hancock noted there’s a spectrum of people analytics, and similarly a spectrum of what these insights are capable of. Most organisations deliver basic analytics reporting. Like turnover (who, where, department, location, under what style of management). And, they often deliver root-cause problem solving to uncover what’s behind these data points.

However, few go beyond these basics. Few delve into bigger data sets via advanced computing power, or combine data sets to determine what really drives high-performance in a business. This is really the next frontier of HR and people analytics, in support of people strategy, and very few organisations are there.

Not all HR Analytics are Equal..

Bringing data insights to bear on people-related decisions isn’t required for all workforce issues, as some simply aren’t as important as others. But one thing the McKinsey team did agree on was that these data insights should probably be brought to bear on more people issues today, than the status quo.

Where things get exciting, and where the data has a higher standing on the value hierarchy, is in the realm of advanced computing capabilities. Akin to marketing’s use of data to better understand the customer, HR data can inform the best characteristics, skills and preferences for, say, the ideal salesperson.

And exciting developments have also been made in the area of where the data is sourced from. Hear me out…

Outside of basic information on an organisation’s people – like where they went to University, key skills and other basic data – today more in-depth insights are available to be combined for advanced understanding and potential boost in talent engagement and output… like personality traits, the optimal environment for the worker, the management style typically suited to them. Bringing these groups of data insights together, means organisations can more naturally combine people, environment and workstyle for a positive bottom line impact.

Being held back by old beliefs…

Don’t be. It’s that simple.

Try to let go of the often baseline thinking of ‘we don’t have the data’. Because you do. You just haven’t accessed it or taken it to the next stage of its value lifecycle. And mostly, this data is in the public domain, so better you capture and use it now, than your competitors.

Recognising that the outside world likely had better data on your employees right now is confronting; but it’s also workable.

Think about LinkedIn; much of the data is public. Resumes uploaded on LinkedIn provide an opportunity to aggregate the data – think about the tens of thousands of profiles, the patterns that exist amongst them, the comparisons and points of connectedness like categories of talent that aggregate by functions, locations, companies, management style. It then becomes possible to compare employers on these measures – which the McKinsey guys did with Amazon and Target – where, with the right computing power, data on where the best talent can be sourced, the categories of talent that work best in each different corporate environment, trends on talent backgrounds by employer: the data opportunities are incredible.

Another angle on the public availability of data is the various platforms out there like Glassdoor, where employers are rated by individuals on specific measures, but also on qualitative measures. Aggregating comments and feedback can give you insight as to how your company stacks up to talent competitors on a multitude of valuable and interesting measures.

Mind. Blown. 🤯

Take Lessons from Marketing… (no eye rolling please 🙄)

This may seem anathema to an HR leader’s intuition. But the smart ones will know there’s good oil here.

I touched on this earlier, but think about how marketing have truly advanced their understanding of the customer, through data and analytics. And over time, they’ve gone deeper and deeper so that the view of their customer’s profile, behaviour, industry, source and predictability has been honed to deliver minutia like never before.

Marketing achieved this by predictive analytics, data mining and harvesting and leveraging the advancements of technology. HR can take heed of this progress: because today, HR have the ability to unearth the same level of facts and insights on employees that marketing has on customers. This is people strategy version 3.0 💪🏼.

What makes individuals and teams successful?

Firstly, the questions must be ‘for what?’. For what job, for what outcome, for what business deliverable?

Importantly, over time, jobs evolve. And unfortunately, organisations become stuck on incumbency, they closely tie an individual to a job. It’s easy (lazy?), old-school thinking. This applies to both permanent and contingent workers. It also often applies to year-on-year people strategy.

people strategy

At any point in time, a given role will mutate, shift, enlarge or all of the above, by the very nature of business progress and the impact of time. So, organisations that have hired individuals for a specific role, now find those individuals operating (be that successfully or not), in quite a different role.

Hence, to collect an utilise data in this dynamic, enables business leaders to shift from old-school thinking of ‘this is the JD, this is the candidate spec’, to thinking ‘what do they need to know? What capabilities do they need? What experiences have they had? What attributes really matter?’. In terms of people strategy, this approach is far more in-depth and analytical.

And finally, a word on data privacy…

In the world of data capture, analysis and the resultant insights, the processes need to be watertight, to comply with all levels of privacy legislation: think GDPR. Every data capture and analytics program in an organisation, no matter what size or scope, needs a legal-governance framework.

From both privacy and employment law perspectives, data protection is key. Engage advice to ensure you’re protecting the data, and to ensure that the way that data is being used in a way that is legally compliant, as well as assisting fair & equitable people decisions. Where your data program is not fair, equitable or compliant, you run the risk of enormous legal risk to the organisation.

The McKinsey Podcast is a fantastic source of intel for your people strategy, and more broadly, your organisation. Check it out  here.

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