We live in an experience economy. Forrester Research says companies that focus on the customer experience (CX) can generate 5.7x more revenue than competitors. According to McKinsey, $13 trillion could be added to GDP by 2030 through digitization, automation and AI. And combining digital investments with superior strategy and median performance in agile operations, organization, and culture could yield a projected growth of 4.3 percent in annual revenues. With that context, it’s no wonder enterprises are so enthused about AI, ML, IoT, Cloud and CX. Yet while many companies focus on capturing data, their attention should instead be on leveraging that data to develop a level of enterprise intelligence that enables them to boost their agility, resilience, and revenue.


Becoming an intelligent enterprise is not a destination, but an ongoing journey. Companies must have the ability to harness data, derive insights from data, then translate those insights into actions to respond to market dynamics. Having data alone is insufficient; intelligence comes from the capability to learn from and act upon it. As markets evolve – and as this pandemic year has shown, they can evolve at a moment’s notice – so must the enterprise’s intelligence evolve. It is therefore critical that company leaders understand their Enterprise IQ (E-IQ) and the business value that is created as a result of being an Intelligent Enterprise.


What is Enterprise IQ?

The intelligence quotient (IQ) of an enterprise functions much like an individual’s IQ, measuring both what the organization knows and, more important, how it solves problems. To solve complex business challenges (e.g. problems), organizations must have the sensory ability to understand the environment, convert the signals into competitive intelligence, share that intelligence across the enterprise, and develop market-appropriate responses to expand the business.


Much like human intelligence exists on a continuum, so does the intelligence of different business units. Being able to measure these differences and chart their progress is critical to understanding where and when a company should invest to accelerate its time to impact.


The trick is scaling intelligence throughout the business. By breaking down internal silos, connecting the respective dots, and building the capability to act on data, companies can become truly intelligent.


This requires organizations to think differently. Very similar to having core capabilities in the new world like domain, design, engineering, agile and cloud, Intelligence must also be an underlying fabric connecting the enterprise. And all enterprises must have a well-established framework to determine their E-IQ.


The Business Implications of Enterprise Intelligence

When companies know their enterprise IQ and are empowered to take action to improve it, they can build the intelligence required to drive business outcomes. Top on most lists is exploring new revenue streams, which is likely when companies can develop new products and services based on actionable insights. Similarly, Intelligence can help create a superior digital experience while interacting with various stakeholders like customers, partners and employees. Internally, organizations can digitize operations and improve their agility based on their analysis of various data streams. And when enterprise intelligence is scaled across the business, organizations can begin to proactively shape business outcomes rather than simply predicting them.


Imagine the power superior E-IQ can create for different industries, be it companies adopting the world of digital commerce, or companies in oil and gas sector grappling with seismic industry shifts.


For instance, creating an intelligence layer in the enterprise architecture framework of an oil company could elicit AI-led business capabilities that help them morph into an adoptive enterprise. Complex functions with deep environmental impact, like inspecting the rigs, can transform into an expert system carrying out remote surveillance with the help of drones that capture real-time maintenance information to mitigate potential risks. This captured intelligence would automatically be transferred to alert the supply chain in order to fix the problematic assets. This approach could also translate to the Utilities industry to deal with safety issues during catastrophic events like wildfires.


Similarly, in the world of digital commerce, Intelligence can create a seamless connection throughout the enterprise value chain. Imagine a system that evaluates customer points of contact to understand preferences and behaviors, suggests targeted hyper-personalized offers (keeping in mind the customer, supply lines and vendor options), picks up orders to begin supply-chain actions (from shop floor to warehouse to delivery), and then closes the loop with a superior customer experience.


This is true enterprise intelligence. In the examples above, the companies have captured various types of intelligence, but – more important – have communicated that intelligence across the business units to analyze the need, identify potential solutions, and enable the company to act on the insights and drive outcomes.


Such cross-functional collaboration can be challenging for many organizations. It can also be difficult to evaluate where on the intelligence spectrum different functions lie, and therefore whether they can contribute to enterprise-scale intelligence. This is where measuring the Enterprise IQ becomes so valuable. Without that knowledge, companies will struggle to know which investments need to be prioritized.


A Framework for Evaluating Enterprise IQ

Intelligence assessment for an enterprise is best evaluated using a five-stage framework:

  1. Sense: Help the organization uncover and utilize information from all available sources. This will help determine the Information Utilization quotient.
  2. Decide: Simplify and disintermediate processes with augmented or automated decision making. This will help determine the Decision Intelligence quotient.
  3. Act: Use insights and smart decisions to drive actions in a closed-loop manner by automating processes. This will help determine the Process Efficiency quotient.
  4. Interact: Transform touchpoints with suppliers, customers, partners and regulators to deliver a superior experience. This will help determine the Engagement quotient.
  5. Adapt: Enable the agile enterprise to recalibrate itself to changing business dynamics. This will help determine the Business Agility quotient.


Each of these areas rated independently, though their cumulative score is used to determine Enterprise IQ.



Much like transformation is a journey, intelligence also evolves. Leaders should therefore benchmark, regularly evaluate, and seek to improve each area over time. By doing so, companies can continuously analyze their business strategy and align processes that need to be infused with intelligence, prioritizing high-ROI use cases based on time to value and feasibility.


With a tool to improve their enterprise intelligence, leaders can accelerate a company’s ability to adapt to changing markets. Transformation may seem like the need of the hour, but in reality, it’s the need of our era. Customer demands, supply chains, market fluctuations … these considerations and many more require businesses to continually evolve. Organizations are thus compelled not only to gather data, but to develop insights and take action based upon it. Knowing where, when, and how to act requires embracing a new way to gauge and boost intelligence: Enterprise IQ.

Mukund Kalmanker

Mukund Kalmanker

VP of Intelligent Enterprise and AI

Mukund and his teams collaborate with leading companies across industries to deliver experiences aligned to emerging digital behaviors, achieve competitive business insights, and drive efficiencies by leveraging technologies such as Artificial Intelligence, Machine Learning, RPA, and Big Data. He has more than 21 years of experience in these areas.

What you’ve read here? Tip of the iceberg. Are you ready to be part of the excitement?