01 Apr Q&A: Dialoguing with your Data
There’s a lot of talk about “Easy BI” and “business intelligence for everyone.” And for obvious reasons: the current state of the art is hard to use and has required companies to scale up on report writers and other personnel with technical-to-business “translation”Âť skills. This swath of infrastructure is responsible for getting still-pretty-raw data from enterprise systems into the hands (and more preferably the brains) of managers and decision makers. But the standard tools of the trade—queries, spreadsheets, slides, printed reports and dashboards—are bottlenecking the process as more data and more complexity needs to be communicated.
Someone said to me recently “We’ll prepare 300 slides for management—they only end up looking at 10, and they ask for things we didn’t do. We can never anticipate how the conversation will go so we are always going back to the drawing board.”
That’s a lot of inefficiency and a lot of cycles at a time when all businesses are trying to do more with less. This loop between management questions and analyst responses has created a culture of “analysis interruptus”. Another senior business analyst told me “I have seen over the years that senior managers have trained themselves NOT to ask too many questions because they’ve seen how off-hand remarks can send analyst teams down a rat hole and burn weeks of time.”Âť
There are two lines of attack—one is to enable management and business users with easier to use tools for analysis, reducing report requests and decision cycle times. The other is to better equip analysts and report writers to have more answers at their finger tips to reduce the manual efforts and lead times of one-off reporting projects—less need to go back to that drawing board. Both of these strategies rely on visualization (to convey complexity and spot patterns quickly) and interactivity (to ask and answer questions and iterate analysis on-the-fly). When these two capabilities are brought together in a fluid and intuitive way, analytics can transcend the technology of cubes and queries and algorithms and become a dialogue or conversation with data. This is what I think of as  conversational analytics.