Insight platforms: Moving beyond big data

Companies are shifting their focus from big data to big insights. A recent Forrester blog post by analyst Brian Hopkins drove this point home, saying succinctly: “Businesses want action, not data. The path to action lies through digital insight.”

Until now, companies had to apply a range of disparate analytics toolsets, often living in different departments, in an effort to gain actionable insights. These solutions also require multiple software purchases that entail additional licensing agreements and multiple vendors. The net result is a disconnected, slow, cumbersome process that can produce insights that are inconsistent or lack relevance.

Fortunately, there’s a much better way forward.

The next step in the digital evolution

Today, businesses that can collect, process and analyze data rapidly to guide decision-making are stealing customers from slower-moving competitors. Their secret weapon? An emerging and powerful class of platforms known as insight platforms.

“Insight platforms unify the technologies to manage and analyze data, test and integrate the derived insights into business action, and capture feedback for continuous improvement.”

Brian Hopkins, Forrester Research

These platforms blend previously segregated tools such as BI, predictive analytics, data streaming, data visualization, reporting and more into a single software layer that delivers insights across the organization. It starts with building a data lake to source the right data and manage it efficiently. On this data lake, businesses can apply different kinds of analysis while enabling a continuous feedback loop.

The insight-driven company

As we wrote on the Mindtree blog, all digital business is fundamentally about the data ecosystem on the back end. This ecosystem provides the intelligence for digital solutions.

With a holistic insight platform, organizations can move beyond focusing analytics investments on specific functional areas of their business. They can now generate new insights because the data is no longer locked up in silos. Acting as a true insight-driven company, they can apply analytic insights to just about every decision—even seemingly small ones.

Insight platforms offer businesses a fundamentally different way of sourcing data and applying a test-and-learn approach to data analysis across the organization. This approach uncovers the most important patterns, helping organizations tap the information that matters most and create a feedback loop for rapid, continuous improvement.

Choosing the right platform

Technology vendors are getting on board quickly and expanding their offerings, which creates a challenge for companies evaluating these new platforms. A recent Forrester survey of 143 vendors in the data analytics market found that 55% now offer data management, analytics and technology solutions that can be classified as insight platforms.

So how do you choose the right one? To help enterprises compare the wide range of vendor solutions, Forrester has segmented insight platforms into five broad categories or classes: enterprise insight, insight application, business insight, business solution insight and big data management foundation, along with what each type does and who it serves. This is a very good place to start.

In addition, you should consider time to insight (or time to decision) when comparing platforms. How fast can the platform process data to help your company make evidence-based decisions moment to moment, even in a changing business landscape? This criterion should be part of any insight platform evaluation.

Mindtree Decision Moments is the first data analytics platform to apply continuous learning algorithms to large data pools, with critical features that accelerate processes and deliver faster insights. The platform’s innovative sense-and-respond system lets companies uncover compelling insights quickly that improve over time and create more value.

Learn more about how Mindtree is helping companies speed their digital transformation with Decision Moments.