One of the first things a company should start doing is defining initiatives for data science and artificial intelligence. These initiatives are a way to formalize and isolate the development of different systems with a particular goal.
Turning Ideas into Initiatives
Most company managers feel lost when it comes to deciding what thing the company should focus on first, once they’re ready to start doing data science.
Selecting which initiatives to develop should not be purely intuition-based but evidence-based, either through data, simulations or both.
It all starts with describing an initiative. Each initiative should have at least the following items:
- Necessary data;
- Involved stakeholders, their awareness and availability;
- Necessary infrastructure to deploy the solution;
- Necessary integrations with the current systems;
- Associated objectives and expected impact on each of them;
- Associated indicators and expected impact on each of them;
Then these initiatives should be prioritized accordingly, taking feasibility, expected impact, importance and urgency into consideration.
Tracking Initiatives and Knowing When to Move On
If you define the initiatives correctly, as described earlier, you now have a way to track them and their results.
Tracking initiatives is a seriously undervalued action that companies must take to be effective with DSAI.
The Observation chapter is extremely helpful to keep track of the initiatives, don’t forget to read it here.
Focus, Clarity and Motivation
Having a clear way to see the Indicators the project is having an effect on will give you clarity on why the project is important and how you’re moving forward.
A lot of times, teams are so deeply immersed in the project that they lose clarity over the reasons why the project started in the first place. Tracking your initiatives against the objectives will help keep the focus, clarity and motivation of the people involved.
Knowing when to stop: Objective already accomplished
Let’s say your target is to get your retention rate at 15%. And you have a budget of 1 year for the project.
After Q1, you have already reached the goal. This is a good time to stop. Even if you estimate it’s possible to go to 20%, the law of diminishing returns quickly sets in and that 20% is never guaranteed.
Be happy with your success and add the improvement to that project as a new initiative, to have its priority assessed later against all the other initiatives.
It’s very easy to get carried on and continuing improvement a project. So much so that I had one project where we only stopped after we tested a human against our machine. Our machine was more than 2.4 times better. Great for bragging rights, but an awful waste of time for the company that could be used somewhere else.
This is a silent killer of projects. As one project becomes successful, it’s easy to get even more motivated to focus on it and forget about other initiatives that the company needs. Remember, FORCE initiatives always have at least one objective defined. Once it’s accomplished, look into the next high-value initiative!
Objective is Currently Unattainable
It’s important to know when to move on.
Sometimes the objective is just too hard to achieve in the current context and you start hitting a plateau.
Imagine the target objective is to reach a 50% retention rate. As you can see, after one year of development, the progress hasn’t advanced and seems to have converged to 20%. It’s time to stop.
Even though it might feel like defeat, it’s a victory to be able to control our egos and understand that there are other, perhaps equally important, initiatives where we should be focusing on instead.
Sometimes required effort to improve these systems would be much more productive elsewhere. This is particularly true when you’re starting your journey. Accept it, move on. You can always come back later with more knowledge and tools that you didn’t have before.
Last updated 28 Aug 2023, 11:41 +0100 .