One thing I’ve noticed in human resources is that all leaders maintain the mindset that they are ready to react to emerging trends. Either the trend popped out of nowhere or their teams have thought about possibilities and planned for them. You need that one bad thing to happen so you can make all the positive steps to ensure that it is the only one. It's a great savings but you still need to have to deal with the turnover costs.
HR leaders are starting to build on Seth Godin's Tribe idea to identify groups of employees that fit a unique pattern and respond well to certain types of programs and initiatives to retain them. In practice, this means understanding what motivates your valuable employees so they will stick around and reduce your turnover costs. As a tech company, we are seeing the benefit of using data analytics to identify unique micro cultures at scale to see what can anticipate and prepare for opportunities and early warning signs.
Let me talk really quickly about what I mean by sub-cultures. We are all familiar with the traditional cultures based on role, location and manager etc. Some examples of a sub-culture include:
- Employees interested in moving within the organization
- Employees who seek to acquire new skills
- Employees who share some unique bonding experience
So let’s talk in more detail about a few ways machine learning can help you examine and prepare for your own micro-cultures and prepare for them. Let’s talk about:
- Roles played in the organization
Profile -comes first because it is the one great potential trap. When you are defining micro-culture’s where do you stop? Does it go so deep as dog lovers vs cat lovers? Left handed people vs right. The obvious answer is no.
But what I do know from dealing with HR leaders is they already have an understanding of their culture and machine learning is to help them dig a bit deeper. Machine learning will help them flag these areas of concern after you do a bit more digging. This is one of the great benefits of machine learning is that it lets the user define how to identify what needs to be flagged.
If manager A is keeping more people, than machine learning can do that deep dive and identify a commonality based on what stands out. Maybe it’s recognition? Maybe it’s because of some sort of team bonding? In any case there is that one thing that becomes a micro-culture which can be adapted to the larger organizational culture Of course machine learning can identify the negative things too and ensure that if there is a micro-culture around them, they can quickly be eradicated.
The best way for machine learning to work is to find that ideal culture and establish those signs that ensure your culture will succeed based on you being able to quickly identify its occurrences.
Roles played in the organization--The roles played in the organization present another opportunity for improving culture while also presenting a great risk. One thing I see a lot is an organization trying to engage employees via their role within the organization and struggling. The challenge is that this point can result in dozens of smaller cultures. The role played in an organization can result in micro-cultures based on personalities, skill set, desire to move up or laterally, and dozens more. Fortunately, this is something machine learning is ideally suited for.
When I’m talking to organizations for KangoGift, I’m able to show them how a solution like ours can help them because it’s possible to measure by micro-culture. Do you want to know if this manager is keeping employees? Then look and see why and THEN do a drill down on the why part. Machine learning can tip you off on the first part, which can then tell you to drill down and look for the second.
To end with a metaphor; machine learning offers you delicious smells around a particular cuisine. Then our tools help you eat the actual meal.
Movement--In our current environment it seems that most of us associate movement, and the organization, as movement out of it. The costs associated with that are terrible and the need to prevent them as much as possible are one of the reasons organizations like us are in business. Yet so many organizations see a person as only an analyst and can’t see them as someone who may be great in systems management. That’s why they leave.
So now you have this micro-culture of people who are interested in moving. Up, laterally or out the door. So now you have noticed that manager A and manager B are losing people and you find out the reason is due to lack of a growth opportunity. Well then the problem isn’t poor management skills necessarily the problem is opportunity. Here is the case of machine learning identifying a problem by first identifying the culture that causes the problem in the first place.
Micro-cultures are well known in the industry and sometimes seen as something that can not be fully managed. I’ll tell you that with machine learning and the desire to engage your employees in the type of authentic way that shows you care for them as people then you’ll see a marked improvement in a number of your metrics. Micro-cultures are real and always will be. It’s your desire to manage them or let them manage you that will be the decider to success or failure for you.