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)
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)
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
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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.
TOP Global Co-creator, System Entrepreneur
1 年"Bridging the gap between insights from research & insights with those operational data and bringing them together is the next big frontier for business intelligence." I invite you to check the AI platform developed by Dr Walid el Abed since DEMS NEXUS is exactly bridging the gap between data and #contextualintelligence thanks to his expertise in linguistics and AI Global Data Excellence We call it #contextualpolarization
This needs a agile mindset to keep churning insights at the speed of business - be it asking questions of the data ( self service ) or discovering new correlations and patterns that are impacting busienss objectives. Data is a founding lever and that has to be governed no question , but the work of busienss driven KPIs and insights needs more busienss involvement and active governance. Else IT will churn the standard 10,000 reports never used. A framework to engage the business better with interactive and intuitive authoring capabilities is key. And well if insights around those data sets and correlations are to be determined , that is key. Last but not the least , coexistence of several tools is key with a loosely coupled services architecture. I see new age augmented analytics, metadata driven and API driven principles ( data services , BI services , user authorization , visualization services ) will be key to drive this change. Long way to go, but the need is beginning to be felt.