Think back to a strategic business decision you or your team made recently. Perhaps it was around pricing strategy to fend off a new competitor, or maybe it had to do with vendor evaluation for a new product? Now focus on the process used to make the decision. Who was involved? What information was used? Was the information accurate, relevant and understandable? Did team members share an intuitive understanding of data and probe for deeper analysis? Or was the decision finalized prematurely based on dominant opinion, emotion or politics?
Few organizations have learned to ride the wave of analytics and AI well enough to tangibly improve strategic decision making. Most businesses are drowned in challenges of data integration, inflexible data architectures and legacy business processes. As a result, they fluctuate between emotion and “E-motion”  (term coined for an overload of digital information, reports, metrics, etc)! A shortage of skilled resources, increased urgency for fast decisions and the lack of a framework to balance information with intuition have resulted in the situation of “data, data everywhere but not a moment to think.”
The good news is that organizations can now choose from a rich variety of visualization tools, self-service data-prep products and various comprehensive AI / machine learning solution stacks to build impressive data capabilities. If these technologies are integrated into a disciplined, cross-functional, agile problem solving process, businesses can truly reap the rewards of informed collaborative intuition.
Let’s look at the journey that organizations or business functions take toward this ideal state. We like to think of this as a scale for “Data Intuition.” Each level described below represents a dimensional shift in capability. It is impractical to generalize and put an entire organization into any one level, especially for medium businesses and large enterprises. Therefore, try to evaluate one specific business function against this scale below.
Most teams or business functions begin their data journey in an unmeasured state. This doesn’t mean there is no data in the environment, just that the business process of concern is not instrumented effectively. Perhaps it’s a new activity or a division that’s growing by leaps and bounds so measurement systems are not yet in place. Leadership has a host of new and shiny distractions that prevent them from committing the required energy to implement meaningful metrics. Strategic decisions are made by heroic, snap judgements. This is seat-of-the-pants management at its best where emotions and dominant opinion rule the day.
At some point, either when growth tapers down or a crisis of some sort shocks the team into understanding the need for better control, they invest in themselves and progress to a measured state. Reporting capability becomes an important factor in selecting and implementing transactional systems, and core processes start to be instrumented, giving the organization a regular cadence of key business metrics. Individuals and teams start to be evaluated based on key metrics, and reports are available for review when required.
As businesses grow and demand more efficiency, they study information about their core processes and start automating decision making where possible; specific actions are triggered based on defined parameters. In this automated state, information drives action and enables standardization. Here we refer to automation as including both programmed functions and standard operating procedures. Although economies of scale are achieved through such automation, information flow can become static and inflexible. Over time, many business functions become stuck in rigid processes that have been automated and allowed to fossilize.
With the right energy for change, teams can learn how to balance intuition and information in their decision making, and start forming hypotheses around specific business problems. These hypotheses are validated through controlled experiments. This leads to a learning state, which enables adaptation of processes, rules and systems based on feedback from experiments and minimum viable products. Data governance and data quality start to become important priorities for the organization, so that instrumented learning loops are predictable and widely available. Teams find opportunities to impact key business drivers using predictive analytics and machine learning.
When a team becomes adept at collaborative learning through a balance of intuition and information, and consciously focuses on this balance in their decision making process, the shift to unconscious or intuitive learning starts to happen collectively and at scale. The business function start moving to a sensing state, where shared collaborative intuition starts emerging. The business function is driven through iterative improvement by cross-functional agile teams and rapid prototyping that is fully integrated across the value chain.
What factors enable a business function to reach the learning and sensing levels of Data Intuition? Adapting a concept from the field of neuroscience, let’s call this Organizational Neuroplasticity.
A human being consists of multiple systems, sub-systems, networks of cells, neurons and neural pathways. Companies also have business units and departments, and its own networks of communication and decision making. Just like individuals develop muscle memory when a particular action becomes a habit, from neural pathways that are wired together, organizations also develop patterns of decision making and communication between individuals and business units. These patterns serve an important purpose both at the level of an individual human being and an organization - to process information and function properly in a particular situation or environment. The ability to change and form these neural pathways in response to new experiences determine the adaptability of both humans and organizations. In essence, this provides both resilience and innovation - essential success factors in a competitive world.
Factors that promote neuroplasticity for a human being include healthy diet and lifestyle choices . For an organization, these can be compared to data - i.e. information that feeds the organization - and culture. Business functions that advance to the learning and sensing states described above exhibit a high degree of “plasticity,” which is enabled by the availability of good quality data, a culture that encourages collaborative intuition and a reasonable threshold for risk. Per contra, the lack of integration between information and intuition can stifle an organization’s decision making process and limit it to the “measured” or “automated” levels described above.
By calibrating the information and intuition flows in an organization for a specific business function, teams can make better decisions in complex, unfamiliar situations. Not only will these decisions align more closely with the core values of the organization, but they will also unleash untapped organizational wisdom and creativity, resulting in better business performance.
 How to Solve Problems and Make Brilliant Decisions by Richard Hall