Data Science Projects – Value Comes First
Most companies are investing in some sort of Big Data capabilities but just having these capabilities isn’t enough. They’re cool but if you can’t provide business value your investment dollars will dry up quickly.
Working for EMC, I can’t resist using an Albert Einstein quote:
It’s very easy to get caught up in the “sexiness” of Data Science /Advanced Analytics; it’s cool but coolness costs money. Properly targeting your Data Science teams at projects to have a quick win or short term impact will help the funding discussion if you are just starting out.
If it costs you $500K to get a $20K return for the business, your funding will dry up quickly. I’m a business guy first; all decisions need to start with what is best for the businesses. There are always trade-offs but when in doubt go with value. Value doesn’t always have to be a dollar ROI, but can be a change in the way we work or look at the business. Most of these should translate into improved customer relationships, product design, or efficiency; Value.
My recommendation for communicating this value is best explained by another Einstein quote:
Keep your explanations of the work simple and in business terms. Know your audience; we often have several decks with different levels of detail. You want to show the business impact and highlight the value or lack thereof.
Not every project will be a home run; you may fall short or even fail. I’ve said in prior posts how I use MythBusters as part of my executive readouts to highlight that fact. You can also use Albert Einstein quotes : )
If you have an established data science team, I’m curious if you found this to be true you or if you had a different angle to your success.