Contextual Intelligence - Enabling Organizations to shift from "Data Driven Businesses"​ to "Insights Driven Businesses"​

Business intelligence, analytics & reporting as a capability across most organizations is fractured.

In this article, I share my thoughts around how unified intelligence from research and operational data can improve the end user experience and alleviate the frictions associated with explain-ability. I call this **Contextual Intelligence** or **Intelligence 360**

There are two distinct sources of information that generate insights and enable leaders to drive their strategies in running the business.

**Insights from research** comprises of insights derived from primary & secondary market research, competitive & market intelligence, state of the industry - analyst reports etc. This is usually consumed by the executive management within an organization as a way to inform and influence their business strategies and projected trajectory. The types of insights generated are (including and not limited to)

• Insights about customers (behavioral insights, social medial insights) that inform around relevant trends & unmet needs
• Insights about competitors (competitive intelligence from press releases, SEC filings, strategy, job postings/ hiring strategies)
• Insights about markets/ regulatory space
• Insights about product & quality of service (social media, product complaints etc.)
• Insights about business events & market trends (new entrants, business disruptions etc.)

These insights are generated from documents which typically reside in document stores.

**Insights from operational data & systems **are derived from structured data sources from various internal & external systems that help run the business processes. Systems pertaining to sales, order management, contracting, HR, marketing, sales force automation, customer relationship management, supply chain, manufacturing, quality, planning etc. all fall under this bucket. The transactional data generated from these systems is usually transported to data lakes and data marts where it is aggregated to support tracking business performances, forecasting, quality & health of business functions and processes etc. The types of insights generated are (including & not limited to)

• What happened?
• When did it happen?
• What would happen if?
• How are we tracking to our goals & objectives?

These insights from operational data are usually consumed by mid-management executives to help them track business & process performance for streamlining & optimization.

Unfortunately, even with the advances in technology, AI & computing - both of these streams of insights are generated, operated and managed separately, and rarely integrated.

There are two fundamental challenges with this set up

• There is a whitespace in availability of both sources of insights across decision making levels which drives inefficiencies
• Insights from research provide contextual intelligence to the operational metrics & KPI's. In their absence, the question of "Why it (an event of interest as indicated by data) happened?" becomes unnecessarily complex to investigate and answer

Integrating the insights from both sources (research & operational data) would drive Intelligence 360, bringing context and uniform visibility to insights that support all levels across the organization.

The key to creating Intelligence 360 is anchoring both insight streams by intent.

Imagine if a business user wanted to understand the market trends for a product/ brand. A traditional business intelligence report or visualization might look something like this

The chart just shows that Competitor C sales have ramped up between Q3 & Q4. Now if you wanted insights into potential reasons of why this happened, contextual insights from research may hold the key.

Imagine if the insights from research were integrated, the user could just click the light bulb on the top right to see the details

This would bring up a pop up which would show the contextual relevant insights that may help uncover the reason behind the numbers.

While majority of organizations are doubling down on improving reporting & analytics systems built on operational data, creating this Intelligence 360/ Contextual Intelligence ecosystem will be the next big frontier for transforming from "data driven businesses" to "insight driven businesses"

In the next article, I will share more on the technical and operational challenges in creating such a system and how to overcome them.