People analytics – when implemented in the right way – can be a real fortune-maker for businesses. The problem is that a lot of ‘analytics’ styles out there will not reap the rewards that businesses expect. Explore the four styles outlined below to see if your analytics approach is missing a money-making trick…
One of the perks of being a consultant is that it allows you to compare a variety of business approaches used by different companies. Take people analytics for example: I’m constantly amazed at how some businesses make a fortune from their investments in this area, while others struggle to make ends meet and even to recoup their initial, potentially substantial, investments.
What separates winners and losers in the game of people analytics?
There are a variety of people analytics styles to choose from – and the approach a business decides to adopt can determine whether they fail or thrive in their implementation of people analytics… The four I’m going to consider here are:
- Infrastructure Obsessives
- Reactive Data Waiters
- Data Miners
- Proactive Business Analysts
1. Infrastructure Obsessives
You know those people who never seem to get any work done because they spend all their time rewriting to-do lists and playing with new time-management methodologies? Infrastructure Obsessive people analytics functions do pretty much the same. Instead of just knuckling down and doing some people analytics, they spend most of their time (and money) on…
- Governance: Setting up interminable governance structures for projects they’ll probably never run
- Stakeholders: Meeting ‘empathetically’ with stakeholders whose business they don’t understand and with whom they’ll probably never engage again
- Data Privacy: Enriching their lawyers by planning for data privacy contingencies, most of which would require – in insurance parlance – 20 consecutive Acts of God in a 24-hour period
- Data integration: Spending months (sometimes years) sucking useless data from all their inconsistent global databases and spreadsheets into one place; then discovering that it’s mostly out of date; then cleaning it for a sum that even would make even Giorgio Armani blush; and then eventually using maybe only one-tenth of the data to generate a report for someone on the fourth floor who they don’t even realize left the company five years ago
- Technology: Evaluating technology after technology before finally investing an amount equivalent to the GDP of a small state on the ‘perfect platform’ – and again, only ever to use one-tenth of its capability
- Conferences: Attending endless conferences and then meeting with swarms of ever-hopeful consultants to discuss dozens of methodologies that they don’t even understand, let alone ever use
- Consultancy: Spending more time with that high-end management consultancy than the average Fortune 500 company devising a people analytics vision, mission and objectives, which they’ll never end up implementing
And finally (but only if there’s any time left)…
- People Analytics: Waxing on ad nauseum about the value they could generate if only the above activities left them some time to do actual people analytics
In other words, Infrastructure Obsessives spend so much time and money building an infrastructure that there’s seldom any time left for doing any decent people analytics, let alone profiting from it; and, in some cases, their bosses eventually curtail their people analytics investments altogether because of the high resource consumption compared to the low returns.
Of course, no one is suggesting that infrastructure is a bad thing. But people analytics – like any organizational activity – is about balancing risk and reward. If you go overboard with risk, you never end up collecting a reward; nor will you make real money from your investments.
There are many possible reasons why people become Infrastructure Obsessives. For starters, they are often the victims of consultancies that emphasize people analytics infrastructure but who themselves lack the experience to deliver meaningful analytics.
Another cause of infrastructure obsession is CHROs whose people analytics skills are limited, but who realize that ‘one needs to be visible in people analytics nowadays’.
For these individuals, infrastructure obsession is a useful deflective measure because it makes them appear to be busy with people analytics while in reality, they’re not budging out of their comfort zones.
Finally, infrastructure obsession is sometimes caused by an excessively risk-averse corporate culture. In these cases, people analytics is seldom the only function to be affected by this aversion to meaningful activity.
2. Reactive Data Waiters
Data Waiter people analytics functions start out similarly to Infrastructure Obsessives, but they at least make some money by actually using their infrastructures to do some ‘analytics’. Their issue is that the analytics they deliver are primarily just reactions to user requests for simple data reports which could be taken care of with a little self-service and end-user training.
However, even in this reactive scenario, Reactive Data Waiters could add some value by asking users why they need the data in the first place, rather than simply just handing it over. Typically, user responses are:
- “My manager asked me to get the report but I don’t know why she wants it”
- “We’re concerned about engagement, retention, absence, cost of recruitment.” In other words, they require the data to address a people process or workforce capability issue (see Levels 3 & 4 in figure 1 below).
In both of these cases, people analytics professionals could adopt a more value-added approach by trying to determine whether there is an associated business issue (of the kind found in Levels 1 & 2 of figure 1) on the basis that there’s not much point in trying to address Level 3 & 4 people issues if they aren’t causing any business problems.
A Data Waiter mentality is usually more commonly found in people analytics professionals who understand the HR language of Levels 3 & 4, but are uncomfortable with the business language of Levels 1 & 2. The fix is usually a commercial education program.
While Reactive Data Waiter people analytics functions probably manage to keep the wolf from the door, there is a huge opportunity cost because they don’t come close to the potential of what might be achieved if they adopted a more proactive people analytics approach as described below.
Click here to continue reading Max Blumberg’s article.