What is Decision Intelligence?

What is Decision Intelligence Blog Image

Decision Intelligence is a widely-discussed topic and an exciting new technology – but what makes a Decision Intelligence platform different from other types of software solutions? And how will Decision Intelligence benefit your business?

Read on for the answers to these questions, plus some examples of how this technology is transforming daily operations at some of the world’s largest and most dynamic companies.

What is Decision Intelligence?

Decision Intelligence is the digitization, augmentation, and automation of decision making across the enterprise. Decision Intelligence combines artificial intelligence (AI) and machine learning (ML) and enables companies to make the faster, more accurate decisions required by today’s competitive and ever-changing business environment.

Why is Decision Intelligence important?

To put it simply, the need for fast, accurate business decisions is outpacing people’s ability to make them … and this gap continues to widen.

Many companies still rely on insufficient manual, analog, iterative decision-making processes, with critical data spread among a patchwork of specialized tools and systems – visualization, data science, spreadsheets, data warehouses, online analytical processing (OLAP), and more, requiring a great deal of manual time and effort to make a decision.

Changes in work have magnified this decision-making challenge, starting with the Great Resignation and continuing in today’s uncertain labor market. Experienced decision makers are leaving critical roles, taking their accumulated knowledge and experience with them. The employees who replace them are spending less time on average in these roles than their predecessors. People have been the “safety stock” protecting businesses from volatility, but these changes in how we work are depleting the institutional knowledge that used to guide decision making.

The result? Many important decisions that could avoid risk, reduce cost, or increase revenue either go unmade or aren’t made optimally, causing business performance to suffer. The average estimated cost of this lack of decision-making effectiveness for each enterprise in the Fortune 500 is $250 million per year[1], while the business impact of unmade or poorly-made decisions is over $4 trillion globally, every year.[2]

To overcome these challenges, businesses need not only end-to-end visibility, but also data science, institutional knowledge, trust, and collaboration throughout the ecosystem – all operating seamlessly to drive effective decision making at scale. Decision Intelligence includes the artificial intelligence (AI) and machine learning (ML) capabilities to transform how companies make decisions, giving them not only agility but the ability to learn from each decision executed.

What Decision Intelligence is not:

Decision Intelligence is not the same as process mining, data visualization, or robotic process automation (RPA). These tools primarily focus on making legacy processes faster, but they don’t fully address the challenges of business decision making in today’s world.

Some companies are using “Decision Intelligence” to describe their own approaches to data analytics or business intelligence, but these are not necessarily true Decision Intelligence solutions. Gartner highlights the full scope of Decision Intelligence by defining it as combining “multiple traditional and advanced disciplines together to design, model, align, execute, monitor and tune decision models and processes.”[3]

What makes a true Decision Intelligence platform?

Digitizing, augmenting, and automating decision making requires the integration and orchestration of the four foundational pillars of Decision Intelligence. In order to be a true Decision Intelligence platform, it must incorporate all four of these crucial attributes:

  • Data: A true Decision Intelligence platform can extract and harmonize billions of transactions from complex enterprise systems and external data sources in order to create an open, composable, and transactional decision data model.
  • Intelligence: A true Decision Intelligence platform operationalizes advanced techniques (including optimization, predictions, modeling, and AI) within the context of business decisions across the enterprise. It has the ability to automatically observe conditions, sense changes, analyze, and predict, creating a real-time learning loop. Because of this, a Decision Intelligence platform is able to go beyond decision support and deliver data driven decisions with confidence scoring and context, at the moment of maximum impact.
  • Automation: A true Decision Intelligence platform models the dynamic cognitive processes that underpin human decision making – delivering transparent, explainable recommendations that drive decision making and execution. Automated decision making based on defined business rules will become an important source of competitive advantage for companies in a fast-moving business environment.
  • Engagement: A true Decision Intelligence platform offers an explainable AI and a transparent user experience, with full visibility into the data and intelligence behind every recommendation down to the transaction level. Instead of a “black box” whose workings aren’t clear, a Decision Intelligence solution must be transparent and auditable, allowing users to understand the basis for recommendations. This intelligent human/machine collaboration drives trust in the process and makes it easier for teams to rely on AI.

What kinds of companies can benefit from Decision Intelligence?

Virtually any company can benefit from Decision Intelligence to help digitize, augment, and automate decision making. Among the companies currently utilizing Decision Intelligence platforms are some of the world’s best-known consumer brands, along with Fortune 100 companies in consumer packaged goods (CPG), pharmaceuticals and life sciences, manufacturing, chemicals, and oil & gas.

In particular, large companies with massively complex operations are excellent use cases for Decision Intelligence – both to harmonize the massive amounts of data they generate across multiple systems and data lakes, and to digitize, augment, and automate decision making at scale.

What do companies need to get started with Decision Intelligence?

To benefit from Decision Intelligence, companies need a cloud platform that integrates and orchestrates all four of the pillars described above: data, intelligence, automation, and engagement. With a true Decision Intelligence platform, a company can digitally transform decision making across every business unit in a matter of weeks, not years – without ripping and replacing its current tech stack or data repositories.

Companies often start with a clearly-defined business problem, then apply Decision Intelligence to understand it better, then address the issue through improved decision making:

  • A global steel manufacturer uses Decision Intelligence to identify root causes of delayed shipments, recommend a course of action, and improve communications and customer service when orders are at risk of being delayed.
  • A petrochemical company deployed Decision Intelligence to address shipping performance concerns and gained real-time visibility across the entire supply chain – including areas managed by third-party partners.
  • A global pharmaceutical company uses Decision Intelligence to calculate available-to-promise (ATP) estimates across a wide portfolio of products, harmonizing data from multiple ERP systems and data sources so that customers know when an order has been received, when it will be shipped, and when to expect it to be delivered.


[1] McKinsey & Co., “Decision making in the age of urgency

[2] VentureBeat, “Lack of AI implementation may have cost enterprises $4.26T

[3] Gartner, “Decision Intelligence,” Gartner Information Technology Glossary.

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