One of the toughest analytics challenges to fix is when key people leave. This reason is another people problem, but with a technology bent. Depending on the importance of the person(s) who leaves, you can experience anything from a minor hiccup to a total meltdown of your project.
One example of this is when the one who built the database leaves. Often they take their unique knowledge of the data structure with them. Another example is when the systems architect who knows the ins and outs of where the data flows departs. This can make it difficult to track down errors and bugs. Lastly, the database admin who wrote the code might be the one who quits, taking with them all their coding work. I can even be worse if they leave on bad terms and take a key piece of your development work with them or even destroy it.
In general, the best outcome you can hope for is to is build workarounds that allow you to keep the project going, however sometimes you are better off just starting over or worst case you just live with what you have. So step one is seeing where you are in the process and then determining what it would take to replace that person.
If you are able to continue, then you need to start doing a better job of documenting and making sure information is shared so this won’t happen again. I learned this lesson early in my career. Learn all you can about all aspects of the data environment and document them. A lot of times a clear understanding and documentation will be required by management to assure funding and resources.
If you have to stop the project until you can find a replacement, then you should also learn, document and share everything so that the new person can pick things up as soon as possible.
In this case, the new person will likely be dependent on you to learn the ropes so use that opportunity to change your culture to be more open.
A final point to add, make sure you understand why the person left.
If there are things you can do to make sure the same thing does not happen again then it is on you to do just that. If it is a cultural thing, then you can be a catalyst for change. If its a compensation thing, then you can help define the expected scope of work and help in the compensation planning. If they left because of a personality conflict, then you can help find someone who will fit in better. Analysts have so much power to shape conversations. Use it.
Analytics Culture – The key to using analytics in a business is like a secret sauce that fuels Data-Driven Decison-Making. It is a unique combination of analytics talent, technology and technique that are brought together to enrich and empower an organization.
A successful analytics culture is not easy to create, but DMAIPH can show you how. Contact DMAIPH now at email@example.com or connect with me directly so we can build a strategic plan to turn your company into analytics driven success story.