Tom Williamson has over 15 years of experience in project management, enterprise software development, and over six years of cloud computing with specialized expertise in business process improvement, change management and Business Analysis. Hates zombies, clipping toenails and fighting with bullies.
Data Scientists Need Love Too, Predictably
Our data, the new (not really) black gold of the business world, has become the means by which we crush our competition. That is, if you are fortunate enough to have a lot of smart people who know how to crunch data and serve it up like fine sushi.
These Data Artists can take your smelly, raw fish data and produce business results you will not typically want to see. Instantly you’ll know the why and the how, and be able to make informed decisions concerning your business. That’s great, but how will my decisions affect future business? Summon the Genie.
To this point, we’ve been dealing with Descriptive Analytics. These are summaries of historical data that tell us where we screwed up yesterday. This data is of value, but what if we could springboard that same result set two weeks or two months into the future? Now you’ll have the competition wondering how the hell you did that.
Practical Applications for AI and Machine Learning
Predictive Analytics can take many forms, including the simpler (not really) and more common data mining and statistical modeling to the complex machine learning and AI implementations. Now we can use these advanced analytic practices to find and examine patterns in the data that will help us make accurate predictions about future business events. It’s like adding a bunch of wasabi to a sushi roll. That’s got some bite!
All Day vs. Someday
Now that we’ve busted out the Ginsu knives and created a master piece of data roll goodness… How often is our data roll being served up? Daily, weekly, or the OMG Monthly? Let’s get our operational data in real-time. With the advent of cloud computing and some fantastic analytics tools you no longer must wait and find out you screwed up yesterday...today. You know instantly and can make course corrections accordingly.
Customer Experience (CX)
Why should we bother with all this analytical madness? Enter the customer and competitor. We need to court one and beat (not literally) the other, and what/who is the ultimate deciding factor? The customer. If their experience with your organization is better than the competition, then you’ve created loyalty, which is the goal.
Better analytics means you’re at the sushi bar preparing the data roll before the customer even sits down. You know what they like, you know what they want, and you are all stocked up ready to...roll.
You’ve got data sources for sales, accounting, customer service, shipping, and ordering toilet paper. Plus, you’ve got spreadsheets everywhere and reports that make little sense.
This is where you give a little love to the Data Scientist in your life.
What are the few data items you need that could make the difference? Work with your scientist and start small, prioritize according to customer need, and support them with everything you have. Before you know it, you’ll have a bento box of data roll awesomeness that your customers love and your competition envies.