Say “cognitive analytics” and you typically get two reactions. For some, it’s a new consulting buzzword that makes a simple thing sound complicated. For others, the feeling is, “Maybe companies somewhere are doing it, but we’re not and we’re never going to.”
The first may be true. The second is likely not. Cognitive analytics are coming your way and there’s no doubt about it.
Business professionals generally refer to cognitive analytics when talking about various uses of big data for business intelligence. The general concept here is that enterprises collect and aggregate large amounts of data from diverse sources. Specific software programs analyze these in depth to provide specific results and metrics that help the business get a better view of its own internal processes, how the market perceives its products and services, customer preferences, how customer loyalty is generated or other key questions where the insights are used to provide the business with a competitive edge.
In many cases, the underlying data is not really new. What’s new is the way in which it is combined and analyzed. Here are two case studies in cognitive analytics that illustrate the point, from my world of enterprise level automation and high speed business process testing.
Case 1 – Business Process Analytics: Where to optimize. In this example, we’re layering together two of the most vital data sets in an enterprise. The first is a description of every business process in the enterprise, and all their variations. The second is actual transaction information corresponding to each one of those processes.
Both data sets are big. A few years ago, assembling either one of them would have been viewed as virtually impossible. Today, actual business processes can be efficiently captured at the enterprise level with software for automated business process discovery. Transaction detail for nearly all processes are available as well from the enterprise apps that support them. After all, nearly every business process is software-tracked today.
Combining transaction and process-level data in a cognitive analytics platform delivers a ton of information that your team can put to work to streamline business execution. Which processes are most used? Where’s the volume? Where are the time bottlenecks? What’s manual that could be automated? Where have “exception processes” become the norm? Even better, these CA platforms are designed with visualization and heat maps that help make the analysis efficient.
Case 2 – Quality Assurance Analytics: Test what matters. In the second case study, we’re starting with the same enterprise-level business process definitions but this time combining them with QA results.
A typical large global enterprise will have 1000+ business processes and variations, consisting of 100,000+ individual steps. When SAP or Oracle have a software update, you’ll want an efficient way to determine which of those processes are impacted by the changes. Why? So that you can focus your staff and priorities on the technology changes, rather than wasting time on what stays the same. And you’ll want some smart analytics to figure that out. One of our clients had to deploy 4,000 software updates in a 12 month period and automation played an essential role in making that possible.
Then you’ll want an efficient way to test all those processes. Which tests passed? Which failed? Which failed last month? Which fail every month? How many tests are fully automated? How many are manual? Where can I re-deploy human testers and free up business users? Where can I grow my test automation portfolio to eliminate tedious manual effort and save money?
Cognitive Analytics: Where to aim the cannon. Today, there’s so much information and business complexity that it’s often difficult to identify priorities and understand what’s important. On top of that, there is the grim reality that your problem-solving resources are limited, and you had better deploy people on the most important business-impacting areas first. The way I see it, cognitive analytics help. The clarity will allow you to pick the right targets so that your team and your business hit the mark.
Today’s successful companies are embracing CA with its powerful business analytics and built-in AI to stay ahead of their competition. So don’t be left behind – because automation is HOT.