Insight is a powerful concept, suggesting the ability to comprehend and understand a complex situation or problem. In a business context, insight is derived from data and informs the decision making process. It’s the basis of Business Intelligence but the depth, relevance and timely delivery of that insight can mean the difference between valuable intelligence and a missed opportunity.
This is the last of a 2 part blog series on Insight by Exception.
What’s the Root Cause?
Identifying an exception is one thing but how do you then determine the underlying cause? Typically, the user will have to explore possible influences that have impacted on that metric to get to the bottom of it. This has to take place before they determine the correct course of action to take, again causing delays between analysis and insight. Could Machine Learning help here too?
We wanted to be able to provide the kind of cause and effect information that could help speed the decision making process so we looked at the range of indicators peculiar to each metric. We found we could use AI not only to flag exceptions but also to provide the most likely contributing factors to that change.
Let’s say you had a Smart Alert about a dip in Sales. Drilling into this would provide you with a waterfall chart of various measures that make up that particular metric. You can then very quickly see the issues surrounding that negative trend and drilling down still further sees you presented with 5-10 possible reasons why there is an impact on sales.
Or perhaps there’s a positive upturn in Sales attributable to a particular team or region? What are they doing differently? How can you replicate that elsewhere? The Root Cause Analysis gives you the reasons behind that variance which the user can then explore. It gives some degree of prediction but it’s still down to the individual to decide upon the correct course of action to take. In this way the business applies automation to maximum effect in the processing of raw factual data but still benefits from the intuitive human analysis where it counts, at the end of the process… which means faster time to insight.
Bigger, better, faster, more
Insight by exception is just one of the core pillars of our philosophy along with Time to Insight, Automation, Extensibility and Customer Success.
Going forward, data will inevitably increase in volume as will the number of unstructured and structured sources. This means the BI platform the business selects will need to be future-proof in its support. It’s for this reason that we champion open access and we play nicely with other data stores and applications, allowing data to be not only collected but sent anywhere. To support this moving forward we have plans to launch a marketplace to foster greater collaboration in the BI community.
Within the business, we prevent vendor lock-in and aim to promote extensibility of the existing environment as opposed to the ‘rip and replace’ mentality of proprietary models. It’s in our interest to ensure that the business is actively engaged with the technology and is seeing maximum benefit.
That’s why we measure our own insights by exception, treating engagement and value as our key metrics ahead of revenue.
This is the last blog in the series “Insights by Exception”. Read the first part of the series, where we look at the benefits of automating business intelligence.