Training your data science team is tough. They are already fabulously smart. Making them smarter, faster and nicer is hard. It needs focus determination and the right combination of information. You want them to work well with their customers. Need them to work for you. Whatever you do shouldn’t add to your workload.
So what can you do with your high potentials? They need skills. Practical knowledge. Support.
Here’s what not to do: 6 mistakes that organisations make over and over in training:
- give them piecemeal band-aid solutions
- use different providers for every program
- give them unfocused, generic training
- train for symptoms not causes
- give them no reason to learn
- make sure there is no bottom line focus to what you teach them.
Which ones have you made the mistake of doing in the past?
Give them piecemeal, band-aid solutions
You are busy. Your job is to lead, to manage and to inspire your team.
When you see a problem you fix it. Last week someone needed presentation skills. The week before that php. Next week it will be someone needing a mentor. And you get it, fix it, make it happen.
The issue is that serial problem-solving like this spends your limited budget on knee-jerk band-aids.
You need to co-ordinate and strategise your approach so you get answers that will make a dent in the problem.
Not something that fixes a hole in a bucket you’re not even using.
Use different providers for everything
Secondly, if you want to muck it up royally, get a different provider for each training need.
Your soft skills providers are different to your process improvement providers. These are as different again from your strategic planning providers.
Because all of these are all different they don’t speak to each other.
You don’t get an overview. What goes on in your presentation skills coaching doesn’t link with the team-building workshop and only marginally aligns to fit your stakeholders’ buying styles. You get more value when your providers too have an interest in making sure programs align.
Make sure it’s unfocused, generic training
Some of the training you do is training for the sake of training.
It’s unfocused and generic. Great for mucking up the training of your professionals. Great way to alienate them.
As an advocate of infinite learning, I applaud you getting your team new skills. But a lunch and learn on how to deal with difficult people isn’t the best professional development for technically brilliant consultants whose clients are not so much too “difficult” as human beings frustrated by problems.
Train to fix symptoms not causes
Another way to break it it to train to fix symptoms without addressing the causes of the problem.
Generically we all need time management.
Specifically we need time management because our business as usual takes up so much of our time that we can’t work on the strategic intent.
The symptom is a lack of time.
The cause is not poor time management. It could be that your team don’t know how to manage scope creep and say no nicely when they need to. Or even that your team spend a large part of their time in meetings which are ineffectively run. The cause may be that you haven’t explained what’s important so they prioritise the wrong things and create rework for each other.
So training to fix the symptom ain’t gonna fix it.
Give no Reasons for people to learn
If you truly want to muck up your people, try to teach them rather than getting them to learn.
Make sure they have no reason to learn. Never ask them to use what they’ve learnt, and ignore it when they do learn something new.
Just because you send them to training doesn’t mean that they will apply it (yay, broken!). It takes effort and a system to get them to remember to apply what they learn. They need a why.
So if you want to muck it up, don’t give them any of that.
Remove any bottom line focus
To muck up your learners’ chance of learning make sure it’s theoretical. That there are no indicators of performance.
Remove any bottom line focus (such as it is). And them make sure it’s a one-off. For bonus points run similar training programs with different providers, and put some of your folk through similar programs so they can undermine the trainer and question the information in the program, so that not only they but everyone else in the program are confused.
Or you can get it right
So the flipside of this is easy to say and more complex to put together. And when you do magic happens. Things get done. Here they are:
- take a holistic view – training does not stand alone but part of an overall strategic initiative
- align your providers as far as possible, and hold them accountable for interacting
- make the training as specific as it can be
- train to fix causes
- give everyone a good “why” they are going to training
- know what changes should happen from the training. Track and measure them. Hold your provider and your team accountable for delivering that change.
Talk to me about how we can do that together. Let’s get your data science team working smarter, faster and nicer today!