Keeping Data Projects Library

Does your organization have a data projects library?

A large library with a librarian selecting books based on a list.

So your company decided to start building up your data and AI capabilities, how should you prepare the ground so that your company can continuously gain value from data and AI?

There are TWO things that I recommend any business that is starting out on data and Artificial Intelligence. They are:

1. Data Collection

2. Data Project Library

Data Collection will be a topic for another issue and I want to focus more on data project inventory here.

What Is a Data Project Library?

Basically, it is a library of all the use cases that the business has worked on using data, data analytics, machine learning, and artificial intelligence, including but not limited to dashboards, business reports, etc.

Why the need?

I see several benefits of having one

1. The library of use cases can serve as reference for

   1. Audit Purposes

   2. Train and onboard new members

2. Currently, turnovers are high among the data professionals and no company can always guarantee the projects that they provide and can be worked on interest data professionals they hire. Having the inventory helps to keep the knowledge within the organization and not be subjected to spotty memory of the team members who either are still around or have left.

3. All organizations will have both successful and failed projects. Assuming they are documented, relevant lessons can be extracted from these projects to either quicken any data projects by tapping on past experiences and/or avoid pitfalls that have caused projects to fail.

4. Certain projects failed because they might be too ahead of the time it was thought of, for instance, the technology then was far more expensive as compared to current. Having the inventory helps to revisit the failed projects again while being a reminder of why they failed, it also allows the business to revisit and determine if the reason for failure still exists. If it does not, then is it possible to revive it?

Having a project inventory can help retain knowledge, onboard new employees, avoid pitfalls, and repeat success!

How to do it well?

Good documentation is definitely needed for each data project but such instruction is too vague. I feel it is important to determine at the start of your capabilities-building journey, to plan and design the whole project planning, execution, and deployment process, together with the data and information you may want to collect.

Besides the details on what to collect, there is the matter of how to store and retrieve the relevant use cases in a timely manner. This will require some archival, and labeling planning as well as setting up the categories of the project, determining failure codes for stating why a project failed, etc. This is library science actually (remember your Dewey Decimals System in your school library?).

To continuously extract value from your data projects and the sunk costs, both successful and failed projects, perhaps your business should sit down and plan for a data project library.

What are your thoughts on this? Will love to hear them in the comments or PM me on LinkedIn. :)

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