Decision Intelligence vs. Business Intelligence: What Is Your Company Running On?

In this special guest feature, Karl Hampson, Chief Technology Officer, AI + Data, for Kin + Carta, discusses two different perspectives for how your company’s data assets are being utilized: decision intelligence vs.

business intelligence and what is your company running on.

Karl has been working with data for over 30 years.

He holds a First Class BEng Honours Degree in Electronic Computer Systems Engineering from the University of Salford, Manchester, United Kingdom.

His focus today is on applying emerging and cognitive technologies to achieve speed to value in delivering business outcomes with data.

All data-driven organizations need robust business intelligence tools to help them transition from running a business on intuition, to running it with intelligence.

The challenge for many is knowing where to start.

With data streaming in from a seemingly endless array of systems and applications, using it to improve business outcomes is a skill that is notoriously difficult to master.

Pushing the technology envelope googletag.

cmd.

push(function() { googletag.

display(div-gpt-ad-1439400881943-0); }); The rise of data analytics and business intelligence has created the illusion that companies are now able to understand and visualize every aspect of their business and this will somehow allow them to operate in a better way.

The reality is much different.

  First generation data warehouses and business intelligence tools were typically about analyzing historical data (data in rows and columns) and understanding what happened in the past (descriptive, diagnostic analytics).

Second generation systems, known as data lakes, are about creating a single large data ecosystem that effectively extends the capabilities of first generation systems by allowing all kinds of data, such as documents, to be available in one place.

Data lakes have typically been over-promised, but for many organizations, have under-delivered.

Increasingly essential in today’s fast-moving business environment is the ability to see over the horizon and around corners to understand the impact of today’s decisions on all of the desired outcomes.

This is where next-generation business intelligence tools come into play ―using faster (real-time) and more modern cloud data platforms to solve problems based around a specific domain.

Unlike self-service business intelligence, Decision Intelligence is focused on injecting the right information into the problem at the right time, or more accurately, at “critical moments of truth”.

Better decisions for better outcomes There is still no magic wand to better insights.

So far, the best approach to Decision Intelligence has been determining how data is going to be used and what accompanying technology is going to make better decisions.

A robust process must be put in place to ensure that the right data can be translated into a meaningful context to solve problems, optimize decisions, and achieve the required outcomes.

This is as much a people and process issue as it is a technology one.

Many questions still need to be asked, such as: Who is involved? What information will they need?What format does it take and how can this be seamlessly injected into their daily workflow? What data is required?What level of maturity needs to be achieved in order to get that data at sufficient quality?How will success be measured using KPI’s?More precisely, what are the problems that need a solution? Nothing actually happens unless a decision is made.

Connecting design thinking with modern data platforms creates new digital products that help turn information into better, faster, and fewer decisions at any scale.

Sign up for the free insideBIGDATA newsletter.

.

Leave a Reply