Your skills problem is not always a training problem.

The uncomfortable part

A team that can't work with data is usually seen as lacking training. When nothing changes after the training, there are reasons for that too.

• What's learned isn't used at work.

  If the team returns to a job with no data, tools or time for it, what they learned is forgotten within weeks. Training should be planned together with work it will be applied to.

• Everyone is in the same room.

  When someone who has never touched Python and someone who codes daily get the same content, one gets lost and the other gets bored. The level gap has to be measured up front.

• Management doesn't know what to ask for.

  When executives don't know what AI can and can't do, the team gets either unrealistic expectations or no requests at all. Technical training doesn't pay off until the management side is ready.

I will tell you early which of these applies. If I see your problem is solved by a hire or a project rather than training, I will tell you that too.

▶ When you should not hire me for this

If any of these is true for you, let's not start this engagement:

• The training is just a line in the annual plan.

  A training nobody will apply afterwards produces nothing but certificates.

• You actually need a project.

  If the work needs to get done soon, doing the project may be faster than training the team.

• You want training on a specific tool.

  Teaching a software's menus is the vendor's job. My focus is the skill of thinking and working with data.

• The team won't have data access afterwards.

  A team without access to data and tools can't apply what it learned.

▶ Questions and answers