Decision Intelligence – Unlocking Success in 2021 and Beyond

In a business context, the unpredictability of the outcomes in current decision models in most cases is a result of the failure to capture the “uncertain” factors linked to these models. Introduction of machine learning algorithms into the decision-making processes – an emerging field called “decision intelligence” – can create robust and more data-backed decision models adding value to a wide range of functions.


Decision Intelligence


Here are some common questions that business leaders come across while planning projects-

“How can I incentivize this project team to ensure that the go live is a big success?”
“How will change in this feature impact the adaptability of the product with end-users?”
“Will increasing the marketing budget by x% this quarter help me increase the profits?”

When you have looked at all the metrics that can influence the decision, analyzed the factors affecting them, and forecasted a scenario, how sure are you about the decision? Our assumption is the bigger the impact your decision will make or the bigger your organization, the less sure you are.

Worry not! Decision Intelligence has got your back.

What is Decision Intelligence (DI)?

Decision intelligence is a discipline for analyzing the chain of cause and effect in the decision-making matrix.

The journey from a decision to a conclusive outcome is not as straight forward as you might think, especially in the business context. One decision usually leads to another and that leads to another and so forth. This forms a chain. DI can help business leaders look at the broader picture and understanding if a certain decision is made at one point, how will it impact the chain of decisions or the outcomes at other places.

Decision intelligence (DI) connects human decision-makers with advanced technologies such as AI/ML, deep learning, visual decision modeling, predictive analytics, big data, statistical analysis, business intelligence, UX design, business process management, evidence-based analysis, causal reasoning, and more.

Why your organization needs DI to succeed in the coming years

Businesses today are trying to stay afloat in a sea of fast-moving data, and DI offers a missing link between the data and decision-making.

Decision intelligence can provide enterprises the capabilities to process large amounts of data to enable faster and better data-driven decisions. Decision Intelligence focuses on injecting proper insights into the problem at the right time, or, to put it more precisely, during the “critical moments of truth.”

Decision intelligence overturns what businesses have been typically doing with their data. In a big data approach, the analytics tools and the queries are usually selected to fit the data. With decision intelligence, decision being sought gets the top priority; it is only then that the query is constructed, and the data selected based on its relevance to the question. So, the data plays a supporting role and not the starring role for enable data-driven decisions.

Scope of Decision Intelligence Across Industries

DI enables better outcomes with accurate decisions, faster executions, no bias errors, and accommodation of the benefits of human intuition.

Some of the most prevalent and visible examples of decision intelligence in action are recommendation engines, which use intelligent analytics to predict which products or media consumers are most like to be drawn towards.

  • Organizational Coordination– Helps the conversion of leads for your sales organization, and optimized inventory and pricing to maximize sales and margin and an agile supply chain that delivers efficiently. All these improvements help in the transformation of the organization.
  • Logistics Management– Shipping, supply chain, and delivery require a lot of logistical decisions for coming up with the smoothest, most efficient, and cost-saving schedules. To avoid high supply management costs, decision intelligence helps in optimizing the supply chain in real-time.
  • Forecasting– To balance the supply and demand for the production systems, DI is integrated into the system by every industry. Demand Forecasting is a big headache for so many companies, especially those in retail and manufacturing. There are Hybrid Cloud Solutions to solve this problem, with speed and accuracy. Retail companies can use it to forecast the purchase of inventory and how much to order.
  • Decision Scenarios– Since DI’s model involves choosing among scenarios, many financial decisions can be taken considering a lot of metrics, which might not necessarily be the chosen ones in DI. This helps in deciding investment scenarios in marketing, operations, and other verticals.

Gartner Projects that by 2023

of large organizations globally will have analysts practicing decision intelligence, including decision modeling


Decision Intelligence is ushering in a new era across sectors, and executives should aspire to be at the forefront of machine learning in their decision-making. DI is the intersection of technology and business needs making companies react faster than ever before.

When the executives decide to use decision intelligence to transform their business, productivity can skyrocket. Our data science engineers can offer you the resources for your company’s best route to success. Let’s talk.

Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.

Geoffrey Moore

Publish: July 19, 2021


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