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There has been a great deal of interest in analytics in the recent past. Technology and algorithms have evolved dramatically in the past decade but they are still being applied to the improvement of old processes. The best analytics outputs are useless if the organization isn’t ready for it!
C18 (originally “science dealing with facts of a state”): via GermanStatistik, from New Latin statisticus concerning state affairs, from Latin status state
Very often people tend to confuse analysis with statistics. Talk about analytics and immediately the discussion turns to trends, statistics, big-data and these days Machine Learning and AI. The tendency is understandable – data analysis is an important part of analytics and often gets mistaken for the entire process itself.
Showing people how fast you can create a pivot table is way cooler than just be seen as staring at the data, wondering what you are trying to do in the first place. Statistics plays a significant role in the analytic process, but those calculations only make sense in the context of our understanding the interactions and relationships of the elements in play.
Gartner has put up a rather nice image of what drives the success of Data Science and right up there (as a happy coincidence) are (a) Ask good questions and (b) Know the constraints
Analytics, when applied to humans at the workplace, have to deal with data from disparate sources – employee records, evaluations, surveys, social interactions and the list keeps on growing. In many organizations, the process gets stuck right at the data wrangling level since disparate systems operate in silos and just reconciling the information to get a complete view of the employee becomes a nightmare. Metrics reporting and preparing rudimentary dashboards then are made to pass for analytics. These so-called ‘analytics reports’ are then little more than a collection of pretty graphs and tables with no obvious value addition or insights.
Adapting Michael Porter’s concept of a value chain to the analytics process: A value chain is a set of activities that are performed to deliver value (product/service) to those that intend to consume it. We could then say that there are five core links in the analytics value chain.
Moving past the challenges of Data Collection and Data Wrangling we get to the primary three levels of Analytics
We looked at the value chain of analytics, but honestly, you wonder – why all this trouble (and it is not easy for sure)? What value does analytics really provide?
Well aside from making you cool and a hit among the colleagues for being a data-warrior (or ninja or whatever martial art form excites you) precious little (kidding!)
Most of the people who set out to be data warriors end up torturing the data till they get what they want to see. (Some of the ludicrous conclusions published, based on flimsy data or worse, are no less than war-crimes if you think of it)
The true value of analytics (when done right!) is essentially of two forms (and that too they eventually blend).
The biggest challenge when working with people analytics are those “little things” called “emotions” and “free will.” If a server in the cloud farm behaved in one way today, chances are likely it will behave exactly the same tomorrow. Not so with people!
Descriptive analytics can only tell leadership about what has happened in the past. To be able to predict future outcomes and to establish linkages to seemingly unrelated events makes HR Analytics both an art and a science.
To repeat a cliché’ – change is the only constant when it comes to the realm of human capital. Your recruitment and retention strategy for last year might be rendered totally ineffective this year because of moves made in technology, labor markets, company dynamics, business focus or a hundred other reasons.
So how can an HR organization develop an analytical mindset?
Three essential steps:
There is little scope to short circuit the move of an organization up the value chain. Organizations are tempted to throw money at the problem but that is not really going to help in the long run. You could buy systems that promise the Sun and the Moon (and indeed some of them are pretty advanced) but always remember the notion of GIGO (Garbage In Garbage Out).
Till you know what you are looking for (the right question), what you need to answer the question (your data sources), how you intend to get what you need (the data wrangling process), analytics will leave you feeling meh!
And sometimes the biggest challenge to a transformation comes from the leadership. If there isn’t complete buy-in, they might just end up being the biggest obstacle and you might end up sending the same message as O.H.Perry did in the Battle of Lake Erie
We have met the enemy and they are ours.
Two ships, two brigs, one schooner and one sloop.
Design thinking is now taking center stage in improving Employee Engagement and Experience at the workplace. Marketers have long obsessed about the Customer Experience (CX) journey. HR teams at leading companies are now adopting the same principles to better manage and improve the “Employee Experience”.
I was down at the local supermarket today morning. As usual I was loitering in the candy and cookies section (a section that is supposedly off-limits for me) when a little girl ran into me and nearly knocked me over. She was so focused on some candies on a shelf way beyond her reach that she just didn’t see me standing there. A couple of hops and a full body stretch but she still couldn’t reach them. I decided to help her and handed her a few. She gave the collection in my palm a very detailed check and nodded her head. She wanted the one with a bright yellow wrapper. And as soon I handed it over, she was off like a rocket. I shrugged and turned to get on with my grocery shopping. Seconds later she was back, a little out of breath. “Mommy says I have to say Thank you. Thank Youuu!” A big impish smile and she was off again.
Be sure the next time I meet that girl in the store; I will sort through the entire rack to pick out as many yellow wrapper candies she wants me to. The payoff: An impish smile and a thank you.
On my way back, I started thinking about all the stuff mothers teach kids. A whole lot of it sounds like best practices in employee engagement strategies. Here’s a quick refresher of stuff your mom already taught you (but then you forgot as you grew up in the big bad world)
Employee satisfaction and engagement are deceptively similar sounding attitudes when seen superficially. Many people tend to use these terms interchangeably but there are clear differences between these two and it is important for business leaders to know the nuances. In fact in some organizations, shaking up satisfied employees might be the key to growth!
I am starting a new series of short videos on Fridays (and hopefully will keep posting).
We would all love to have work that keeps up engaged and motivated. There are several dimensions to what drives engagement and the “job role” itself contributes very heavily to motivation levels. Put another way, if you are underpaid to do a lot of challenging work, you might still be pretty engaged (all startups pretty much work in this state) but if you are a smart person paid a ton of money to do nothing – chances are you will want to quit (fast!).
Here is the first in the Friday Videos series with some tips how managers can create Challenging roles to keep Employees motivated.
Having a meaningful vision to work towards, is a strong source of motivation for employees. Companies can use the psychological underpinnings of story-telling to better communicate and reinforce the organizational vision.
Most workers, many of whom are millennials, approach a role and a company with a highly defined set of expectations. They want their work to have meaning and purpose. Gallup, SOAW 2017 Report.