In The New Wave of Analytics, Actions Speak Louder Than Insights
CONTRIBUTOR
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Analytics and algorithms have already transformed our world. Now they are about to do it again.
The scientific use of data has revolutionised every aspect of life – from the way we make decisions in large scale corporations to the way we grow vegetables. But to get to this state, information and its analysis has evolved drastically. Brian Wiclove covered the history of this evolution for TechCrunch earlier in September. In his piece, he also briefly touches upon what’s to come – the visionary future of data and how it’s used by machines to help humans solve problems.
This is a conversation that everyone in business needs to have – “How can we use the data and knowledge we already have, to train machines to help us?”
Training Machines ?
It sounds like a nightmare scenario from a sci-fi blockbuster like Terminator or I Robot, but in fact training machines (i.e. machine learning) to automate human actions is neither new nor scary. From 1957’s first Casio calculator to modern day deep machine learning, we’ve rightfully become comfortable with outsourcing hard computational work. Today, we depend on technology to process data and inform us. The best analytics solutions are the ones that are able to ingest the most data and quickly turn it into metrics. The best data visualisation solutions are those that present those metrics in the most understandable way.
“Analytics software has taken huge strides in the past 20 years and has made miraculous growth and optimisation possible. But there is also an inherent feeling in the industry that this is not enough. And I think what’s missing is the direct delivery of actionable insight directly to the stakeholder.”, said Dominik Blattner of Cupenya – an Amsterdam-based operational intelligence company.
Training machines to crunch numbers and make graphs out of those numbers has taken business, and humanity in general, very far. But we can go further. The steps that follow after gaining the insights from a report are still performed by humans. At the moment, they normally are:
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- Have a meeting to present and discuss the report and its findings.
- List the learnings that can be taken away from the report.
- Discuss what actions can be taken to make an improvement or fix an issue.
- Delegate those actions to the right people that need to execute them.
- Execute the actions.
- Wait for the next report to inform you whether the learnings in point 2 were the right ones and if the actions decided upon in point 3 did what they intended to do.
You can see that along this procedure there’s just too much human involvement – too many points where handoffs occur and, respectively, too much delay. And in this case, the analytics are an example of intelligence, that is not operational, and not actionable.
