There’s an old saying in business: if don’t ask the right questions, then how can you expect to get the right answers? For any given product or service, customer expectations, aspirations and requirements are often locked up in the customer’s mind. Finding out what makes people tick is the key.
In traditional terms, this is the last mile of business.
This foundational truth applies as much to traditional negotiations, sales and general commerce as it does to the electronic business. If we don’t ask the right questions of our data, then how can we expect to be able to apply intelligence to our new connected collaborative electronic business models?
In digital terms, this is the last mile of analytics.
Crossing a new chasm
Geoffrey Moore famously wrote about Crossing The Chasm to explain the gap that exists between early adopters and mass-market acceptance. A similar gap now exists between those companies who have thought about implementing data analytics to examine their business operations and those who are actually doing it.
The problem is actually one step further back. In reality, some companies have invested in a certain amount of analytics, but they are failing to use that insight to change the way they do business. These firms are failing to go the last mile, both commercially and technically.
It’s a concept posited by Chris Brahm of Bain Consulting. His ‘last mile of analytics‘ is the space between analytical output (data answers) and actual changed behavior. Everybody already knows the concept well enough i.e. you can lead a horse to water, but can you make it drink?
“We believe one of the biggest sources that we see clients struggling with is the last mile. That is the gap between great analytic output and actual changed behavior that creates value in the enterprise – whether it’s a frontline worker, a manager, or even a machine,” writes Brahm.
Empowering the knowledge worker
Historically the last mile has been the hardest part of the analytics pipeline to get right and also the most important. After all what’s the point in investing all that money in analytics tools if people don’t act on the information they provide correctly or even ask the right questions in the first place?
Search and AI-driven analytics company ThoughtSpot insists it has a solution to this problem… and it is twofold.
First, we to make it really fast and easy (we might say frictionless even) for any knowledge worker to get answers to very simple data questions through a search-based interface that more or less feels Google-like.
Secondly, we are now at the point where we can start to use AI to actually suggest data queries to human users based on a) trends and outliers in the enterprise’s core data and b) the specific actual role of the knowledge worker using the analytics software.