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Businesses have so many options, choices and models from which to choose when it comes to strategies, software, systems, processes, and approaches. As a result, decisions typically result in outcomes that are highly unpredictable, unreliable, time consuming and error-prone. On the flip side of the coin, businesses faced with vast choices and options often become plagued by frustration, friction, indecisiveness, decision fatigue, apathy and gridlock. And many things can make the decision-making process even harder. Unforeseen innovations. Pace of change. Market shifts. Economic conditions. Staffing mistakes. Inability to see or grasp all of the variables. But businesses need their decision-making to be quick, precise, and mindful of the entirety of their business. So what is a business to do? How can a business better handle the decision-making process?
It was exactly this dilemma that forced the decision-making process to evolve. Welcome decision intelligence. The need for a better decision-making process led to the emergence of decision intelligence as a way to make accurate, strong, and efficient decisions based on how knowledge-led actions can lead to outcomes.
What is Decision Intelligence?
What is decision intelligence and where does the term come from? Like all advances, decision intelligence arose from a need. The decision-making process in all organizations had been pretty much the same for a century. In the case of business, a company’s staff collects data from various sources. Management helps to visualize it. And then leadership finds critical insights, and uses those insights to make decisions. It is a linear process that makes decisions after the data is collected and understood.
But, in traditional decision-making processes, the unpredictability and complexity of global organizations weren’t considered. There was exponential growth potential that one or a few individuals simply could not gather, process and factor in fast enough and accurately enough. That model of decision-making became unsustainable. There was a need for a better approach to help an organization evolve its decision-making process using advanced technologies like machine learning, artificial intelligence, natural language queries, intelligent apps, and more to create comprehensive platforms. That is decision intelligence.
That’s the key. Decision intelligence is not a software; it’s a strategy. Decision intelligence helps make accurate decisions using various techniques, processes and tools. It is an emerging field that uses machine intelligence (not one software but information from many various systems) to design and align decision processes and models. Decision intelligence includes decision support and management in a descriptive and predictive manner. This data processing strategy can improve the value and reduce the time taken to make a decision. Decision intelligence also reduces the risk of making a wrong choice.
How Does Decision Intelligence Improve Decision-Making?
Decision intelligence can consider how any given decision will affect the entire company. It allows a company to make decisions based on a mix of past knowledge and future estimates.
1. Make Better Data-Driven Decisions
Harvesting the benefits of data intelligence for decision-making can be tough. To make better decisions, staff (which are human and unpredictable) must be able to analyze data and make predictions. But artificial intelligence and augmented intelligence can help find patterns and spot anomalies in data in order to help improve decision-making and influence outcomes.
2. Make Faster Decisions
Big decisions can be time-consuming. Gathering the data, processing it, and having the right people interpret it takes time. Multiple stakeholders are involved in any major business decision. Some people take a lot of time evaluating options. Some waste a lot of time trying to determine the right choice. Others cannot fully grasp all the variables. But an artificial intelligence system can look at 100% of the data from 100% of the sources and process copious amounts of data not only with precision but also at a lightning fast pace.
3. Consider Multiple Options
Most businesses face more than one problem at a time. One problem can complement or complicate another one. This leads to multiple problems leading to the need for improved processes. But because decision intelligence uses artificial intelligence algorithms to make decisions, the decision intelligence process can highlight how one decision alters outcomes. A business leader has the flexibility to solve multiple problems and see how each affects the rest; looking at a multitude of possibilities. A stakeholder can see which aspects work best in the process. Looking at all of the variables, leaders of a business can select the best choice from a plethora of options, always keeping goals and growth strategies in mind. Think of it like a company using a traditional decision-making approach as playing checkers while those using decision intelligence are playing chess (on steroids).
4. Improves Accuracy
Mistakes consume time and resources. Using decision intelligence tools to make informed decisions eliminates the trial-and-error process. It allows an organization to spend less time on things that won’t work out in the organization’s favor. Imagine being able to save the time and trouble of not having to try things that won’t work. This allows a company to focus on opportunities that will have a greater impact and produce the best results.
5. Eliminate Bias from the Decision-Making Process
Companies are led by humans and humans have biases. Personal biases and mistakes creep into the decision-making process. That’s why, in any decision, there is a chance for bias to influence outcomes. But decision intelligence is not vulnerable to cognitive biases and thus can help shortlist the best outcomes. Decision intelligence can help companies make smart decisions and avoid conflicts in values and the self-interest and politics that affect many organizations. Decision intelligence eliminates the influence of those mistakes and biases when considering how options play out. A programmed algorithm looks at data accurately, without the influence of bias, in order to make the most accurate decisions.
Decision Intelligence in Action
Decision intelligence is already being used in multiple industries to drive resilient, sustainable, and cost-effective solutions for businesses. Case in point. Morgan Stanley helps clients invest more intelligently using decision intelligence. Their platform uses decision intelligence to suggest winning investment strategies for customers. Human experts then verify these plans before being suggested to the customer. For retail businesses, decision intelligence is being used to better predict which goods to manufacture based on customer demand, sentiments, and trends. This is the simplest use of decision intelligence and is being used by many retailers including Amazon and Walmart.
So how might a business use decision intelligence in its organization?
1. Identify Risks and Make Recommendations
Companies can look ahead with greater ease and confidence, identifying risks and taking action based on specific recommendations that avoid damaging the business. If a dynamic event disrupts a company’s supply chain, DI can be used to take action to successfully address the situation immediately. Imagine how many problems could have been avoided if all companies had been using decision intelligence at the start of the Covid pandemic. Current supply chain bottlenecks could have been mitigated.
2. Manage Supply
DI technology is excellent at predicting when products are about to become hot or cold, when a margin has or hasn’t reached a point where changing stock makes sense, and otherwise syncing up supply with consumer demand.
3. Make Growth Decisions with Confidence
DI eliminates the need for long conversations. DI provides a nexus of truth everyone on a team can refer to and trust. The collected insights offered are unbiased, accurate, and reliable. This allows decision-makers to act faster and reduces conflict within an organization. Decisions about whether to buy a business and how expansion into another product or service might affect the company’s goals are no longer based on personal preferences and hidden prejudices.
4. Improve Sales and Marketing
Digital intelligence looks at customer data gathered in the form of datasets. It identifies the ideal customer profile and matches it with the third-party data to create a target list of prospects for the marketing team. The strategy helps identify specific customer preferences and complements their needs.
A study by Bain & Company found that business performance is 95% correlated with decision effectiveness. And another study by GrowthAQ showed that decision-makers use just 22% of the insights and recommendations they receive in their raw data. Most importantly, research by Cloverpop found that 98% of managers fail to apply best practices when making decisions, and their decisions fall short of expected results 70% of the time. That means most companies are still making decisions while flying blind and those decisions account for why a company is effective. It’s time for a better way and while it is not perfect, decision intelligence certainly offers a vastly improved way for companies to make decisions. Now the only question is whether the decision to act on this information will cause gridlock or lead to change. It may be the most important decision your company ever makes.
Quote of the Week
“Profit is not the explanation, cause, or rationale of business behavior and business decisions, but the test of their validity.” Peter Drucker
© 2022, Keren Peters-Atkinson. All rights reserved.
