Analytics for Everyone
There was a great article in DM Review in September titled Analytics for Everyone by Swayne Hill. What I took from the article is the idea that end users need more information and less data, especially historical data. Being a true analyst, I want to have all the data to look for patterns, trends, seasonality and stories. However, it’s not data that the end users need. They need results and enabling information. IT skills shouldn’t be needed to make sense of data like it typically is today. An excellent example of this was found in this article and shown below.
“This point became clear to me recently when I visited my new wireless carrier’s local retail outlet. I was about to take a trip abroad and needed to upgrade to a new handset that would work overseas as well as at home. As the salesperson handling the changeover entered the data for my new account, I noticed two small rows of dots at the bottom of the screen labeled “churn” and “revenue,” and I immediately realized that this was a perfect example of the value of analytics embedded into the middle of a business workflow”. (DM Review)
Instead of the retail salesperson having to look at all of the customer’s data to understand how valuable the customer is to the company on the spot, it is presented immediately. Granted it probably should have been less visible to the customer, but that’s irrelevant. It’s not that difficult to program logic to determine the lifetime value of a customer. It’s a little bit more difficult to define how likely the customer is to stay with the company. Regardless, this type of predictive analytics is exactly what businesses need today.
In an environment where costs have been cut, cut more and cut to shreds, there needs to be more emphasis put on future looking and predicting outcomes and value. Knowing what a customer did yesterday, last month or last year will only tell you just that. If that historic data is used with specific logic, then it becomes very valuable as in the example Swayne gave above.
Stayed tuned for more posts on predictive analytics including examples.
Related Posts:
October 19th, 2008 at 10:03 am
[...] comic comes at a perfect time to follow up on the recent predictive analytics post. I am trying to keep things light on the weekends. I hope you [...]
October 31st, 2008 at 7:17 am
[...] Analytics for Everyone [...]