Gary Cokins, Founder, Analytics-Based Performance Management LLC
In your opinion, what was the most important thing that happened within BI/Analytics in 2016?
- My opinion is that the most important thing that happened with BI/Analytics in 2016 involved the marketing function’s increased ability to gain insights into customers. They have gone beyond just helping their sales force colleagues with targeting to identify the relatively better customers to retain, grow, win back, and acquire. In 2015 they leveraged analytics to gain higher “profit lift” from customers by identifying next best purchase offers tailored to each customer.
- We are all familiar with Amazon’s on-line message to us with “others like you also purchased X, Y, and Z”. In 2015 marketing upped this game by applying “associations”. They considered the most relevant demographic information they have about their customers, such as age and home residence location. Then for each resulting customer micro-segment they determined the following. For customers who purchased products A and B but also C, let’s target similar customers who also purchased A and B but not C. Then offer them coupons, deals, or price discounts to purchase C. Increased sales and profits are the result.
In your opinion, what will be the most important development within BI/Analytics in 2017?
- I believe the most important development related to BI/Analytics in 2017 will be further advances with real-time visualization. When we were children our mothers told us “Looks are not everything.” She lied! They do. Today managers and analysts are very busy with many priorities. Their time to analyze information is limited. It is cumbersome for them to interpret stacks and columns and rows of table data. They want pie charts and histograms. Real-time visualization involves changing input independent variable, such as forecast sales volume, with a “slider” on one’s computer or mobile device, and then immediately viewing the results. With this example of sales volume forecasts the real-time calculated result would be the changes in profits.
There was a lot of talk about digitalization in 2016 – How do you think this will affect the market in 2017?
- I believe that in 2017 digitalization, specifically self-learning machine software, will begin to substantially eliminate jobs. How often do you use an ATM machine rather than a human bank teller?
- Many executives, managers, and their organizations underestimate how soon they will be impacted and the severity of the impact. Without responding soon their organization’s viability and competitiveness will be adversely affected.
- The accounting profession is also vulnerable. This is because many of the tasks that accountants perform – processing repeatable transactions and producing reports – are logical and lend themselves to automation.
- Organizations that embrace a “digital disruptor” way of thinking will gain a competitive edge. This type of technology is not that complex, such as relying on integration among disparate hardware and software systems. It involves the understanding the specific keyboard clicks that a human is making and replicating them with a software. Many of the algorithms used, such as a credit check, are fairly standard. As machine self-learning algorithms become commoditized, have access to data bases, and are “trained” by domain experts, then the prices for S/RPA technology will go down while the value proposition for the tools will go up.
What new concepts do you think will emerge within BI/Analytics in 2017?
- I believe an emerging concept in 2017 will be “data governance and curation”. My reasoning is that the IT function has been involved for decades with data governance, typically with large legacy systems. IT has not paid much attention to individuals creating and sharing their own files, such as spreadsheets. That will soon end. IT looked the other way when users purchased BI software that was priced just below the procurement policy threshold requiring a higher level manager approval. But now as leveraging “big data” begins to emerge as a competitive edge, the existence of multiple and disparate BI software vendor products imposes the same threats and complications that “data governance” addressed decades ago. The reason I added “curation” is because so much of big data comes from external resources. That is, big data does not exclusive come from an organization’s internal data. So, similar to a curator in a museum who is also responsible for art work that is loaned to the museum for display, but not owned, “curation” should be added to “data governance”.