I've been thinking a lot lately about the fundamentals of analytics and how to break them down to their core components from a business-needs perspective. I have been dealing with this directly for years in the contact center market, and most recently by way of a real estate investment business that is trying to sort out the chaos in the housing market. So I'm kind of thinking out loud here about commonalities that I've seen across industries.
Based on my experience, I believe there are 3 fundamental products that people want to buy when they buy a business intelligence or analytics solution, and people buy these solutions hoping that they're actually getting one of these products. If these boxes were sitting on the shelf next to Cognos or whatever they'd get bought every time as they directly address the core need:
- The Workflow Optimizer. Every business in the world is built on one or more workflows, the actual work that needs to be done. Actual work like handling a phone call, buying a property, following up on inquiries, etc. People buy this product to make their workflows work better, faster, and cheaper.
- The Workflow Assigner. When you're dealing with massive quantities of data like financial markets, Web traffic, etc, a manual process will not cut it here. Do you send the call to IVR or a live agent? Do you buy the property or ignore it? Do you allow the transaction or decline it? If you cannot assign workflows in real-time or faster, you've created a bottleneck. If you don't prioritize instantly and assign accurately you're. This must be instantaneous.
- The Opportunity Finder. Again, mountains of data means that you not only have to assign workflows properly, but the number of different workflows that you have to create and implement mushrooms as well. You can implement a white glove service for your VIP customers, but only if you can identify them instantly and assign the correct VIP processes. You can buy properties in many different places, but the profit potential is different in each.
Reports, dashboards, scorecards, all of the existing analysis products only exist to support these core needs.
If I had to guess I'd say that 99% of analytics products are Product #1 in different clthoes–they help optimize existing workflows. Rather, they help trained professionals figure out how to do this, the optimization is typically not part of the analytics process itself. This is typically done by looking at the past using metrics and trends, and is pretty standard at this point. SMS alerts, wall boards, etc are all there to alert you when one of these workflows breaks down in some way. Advanced analytics products implement data mining algorithms to help identify patterns in the data to help these manual processes work better.
Most of the exciting new data-related opportunities that I see are built around products #2 and #3. They simply weren't even needed before, in the Digial World 1.0, because there was a manageable amount of data generated, andpeople could manually do the jobs of Products #2 and #3. The amount of data is now getting to be un-manageable.
As more and more data streams come online–generated by smart phones, RFID tags, user-generated content, computer vision, etc–you can start to see patterns that you couldn't before. These patterns expose the underlying trends that you really want to take advantage of as a business. Things like illiquid markets, pricing inefficiencies, data starved veriticals. Every bit of data you add to your pool gives you the ability to see these more clearly.
Selecting the proper workflow or process becomes more accurate the more data you have available to support the decision. Buy the house? Only if you know what it's worth and how much you'd make relative to other houses that you're not buying. You can figure it out, but only if you have enough data. Prioritize the call to a live agent? Maybe, but you'd better make sure you're not bumping someone more important, and you need data for that.
When you have more extensive information on the entire world of data it becomes much easier to identify groups of properties/customers/whatever that are unique in some way but not being treated as such. This is when you'd want to focus your efforts on taking advantage of them by sending them through a special process that plays to their unique characteristics. This is almost pure data mining, but it becomes much more accurate with more data.
The more data you're able to crunch, the bigger your competitive advantage, but you need Products #2 and #3 in order to do this. These products either are not sold or are almost completely manual right now.
I especially think there is a lot of potential in point solutions that deliver products #1, #2, and #3 pre-tailored to specific veriticals in an easy to use package. Particularly as a cloud-based solution that offers pre-packaged integration with existing data sets such as Twitter, news, the 2010 Census data, weather, etc.
More thoughts to follow as I continue to work on and think about this.
