In today’s breakneck business world, a single delayed decision can cost millions. Just ask Netflix, who transformed from mailing DVDs to a streaming giant by making bold, rapid-fire choices while Blockbuster clung to their traditional model. The secret to staying ahead? It’s business agility. Moreover, this is not just about moving fast—it’s about moving smart using actionable analytics. Indeed, business agility is not a new idea, but it is sorely needed in this age of rapid digital transformation and global competition. To best illustrate business agility, let’s look at the decision cycle framework of Col. John Boyd, the OODA (Observe, Orient, Decide, Action) Loop. This is one of the most versatile, and simplest way to achieve business agility. 

In this article, I’ll describe each phase of the OODA Loop decision framework and substantiate why it is one of the best ways to achieve business agility. Moreover, in each of these OODA phases I’ll identify the types of analytics needed to support rapid, informed decision-making. So, let’s get started.

1. Observe Phase: Find Out What is Happening Using BI-Based Descriptive Analytics.

A critical first step for any organization is gaining a clear view of its business landscape. This is where leadership can leverage descriptive analytics such as Business Intelligence (BI). Specifically, executives need access to data feeds that are both cross-functional and targeted. This enables businesses to keep an eye on trends, risks, opportunities, and anomalies. 

For example, decision-makers could use a BI dashboard that focuses on key performance indicators (KPI) or key risk indicators (KRI). Ideally, these smart dashboards don’t just display data—they actively alert decision-makers to significant trends, risks, and anomalies. For instance, executives could use a BI Balanced Scorecard dashboard depicting operating margins, order fulfillment, and inventory turns. For more details on this, see Lora Cerere in her article, Aligning Supply Chain Metrics to Improve Value.

“To warn of everything is to warn of nothing.”

CIA saying

2. Orient Phase: Prioritize Rapidly to Diagnose Pressing Problems and Size Up Opportunities.

Next, in the OODA cycle, the organization must quickly analyze the critical information gathered during the Observe phase. This second phase, Orient, is basically an impact assessment driven by the need for speed. Indeed, businesses must do a rapid assessment during this phase because decision timing is both fleeting and essential. Specifically, many times opportunities are transitory and problem resolutions are time dependent. So, decision-makers must quickly prioritize what to assess with the information that they have available. Also, they need to determine the reliability of the data. This in turn will help leadership to determine whether they should move forward with a decision or not. Below I describe critical steps within the Orient phase.

“The signal is the truth. The noise is what distracts us from the truth.”

Nate Silver

a. Both Internal and External Phenomenons Can Trigger a Business to Orient.

First during the Orient phase, not all analytics are triggered by changing external market conditions. In many cases, organizational decision-making processes are activated by internal factors such as a new leadership initiative or innovative ideas surfacing within the business. To further detail the analytical tasks needed during the Orient phase, what follows are the key types of analytics used and the critical assessment actions that must take place.

b. Insights for Decision Requirements Gleaned Through Both Diagnostic and Predictive Analytics.

Without a doubt, the Orient phase of the OODA Loop calls for great agility and intense analytics. Specifically, the organization will need to use two types of analytics, diagnostic and predictive. The goal of these analyses is to first identify information requirements needed for making a decision. Simultaneously, the decision team must gather the information required to fulfill those requirements. Also, it is during the Orient phase that decision-makers grasp the problems, probably impacts, risks and opportunities at hand. Hence, though not perfect, the business has the information to determine whether to move forward with a decision.

“There is no such thing as information overload, there’s only filter failure.”

Clay Shirkey

c. The Analytical and Assessment Ingredients that Are Needed to Rapidly Orient on a Point of Decision.

As discussed, there are many analytical tasks within the Orient phase. Also, depending on the situation, this assessment to “Orient” decision-makers can range from milliseconds to months. In many ways, this Orient phase within the OODA decision cycle amounts to an impact assessment, except that the analytics needs to be completed in seconds versus months as in the case of strategic planning. Below, I’ll introduce you to an innovative approach to conducting impact assessments that align with today’s rapid business decision cycles. By following these assessment steps, decision-makers can quickly understand complex situations and make better, informed business decisions.

A Rapid Approach to Assess Impacts to Best Orient Decision-Makers

The Best Impact Assessment Approach that will Quickly Orient You for Better Business Decisions

1. Prioritize Which Event Needs an Impact Assessment.
2. Assess Confidence Level of Data Sources Triggering the Impact Assessment.
3. Use Diagnostic Analytics to Determine What Happened.
4. Apply Predictive Analytics to Assess Potential Impact of Not Acting.
5. Identify What Information is Needed to Make a Good Decision and Then Gather Missing Data.
6. Complete Impact Assessment Determining What Is Most Likely Affected, When Will It Happen, and Mitigation Factors.

For a detailed description of this rapid approach to impact assessments, see my article, The Best Impact Assessment Approach that will Quickly Orient You for Better Business Decisions.

“Orientation isn’t just a state you’re in; it’s a process. You’re always orienting”

JOHN BOYD

3. Decide Phase: Analyze What Can Happen (Predictive) and What Action Should Be Taken (Prescriptive), and Determine Best Option.

Predictive Analytics Types: The Best Opportunities For Supply Chains

Here, business leaders make informed decisions. This includes considering multiple options, determining risks, prioritizing decisions, consulting stakeholders, and making decisions. Also as part of this step, decision-makers need to put their choices in context evaluating both risks and the results of past, similar decisions. Lastly, the decision-makers need to fully identify the likely outcomes to include resources needed and any mitigation actions required to increase the likelihood of success.

From an analytics perspective, the decision-maker leverages both predictive and prescriptive analytics. In other words, the decision-maker assesses “what actions should be taken” (prescriptive) and also draws conclusions of “what could happen” (predictive) in a given scenario. 

4. Act Phase: Tell the Organization Your Decision and Intended Outcomes, Monitor Progress, and Use Business Agility to Adjust as Changes Occurs.

Supply Chain Analytics Types and The Way They Work To Better Empower Decision-Making

In this step, the business executes decisions. As this is an organizational setting, business leaders need to communicate clearly their decisions, establish clear goals, and monitor progress. In some cases, a mission-type statement is needed detailing who should do what to include the allocation of resources. Also, this step includes monitoring progress and making changes as appropriate to maximize the success of the decision. During this decision cycle stage, leaders can and will use the full range of analytics to evaluate new information as it becomes available. Hence as the organization acts, decision-makers can both adjust decisions and provide new guidance to assure optimal outcomes for the business.

“Never interrupt your opponent while he is making a mistake.”

Napoleon Bonaparte

5. Repeat the OODA Loop: This Business Agility Cycle Is an Iterative Process Using Continuous Feedback for Optimal Decision-Making.

An Agile Decision Platform to Empower Executives For Superior Supply Chain Performance: Here Are The Best Attributes

As this is an iterative process, this agile decision-making cycle repeats itself over and over again. Indeed, this loop, when executed effectively, enables the corporate executive team to compete more effectively. This is because their decision-making is highly responsive to change and closely aligned with market demands. Further as decision-makers and the organization take action, they also learn. Hence, they continue to gain knowledge that consequently improves both their decision-making and their actions in the future. As a result, when changes occur, decision-makers are more responsive, making adjustments to their decisions to improve the likelihood of success.

“He who can handle the quickest rate of change survives”

Col. John Boyd

More References.

For a more detailed discussion of the OODA decision framework and how businesses can leverage it, see this article, The Forgotten OODA Loop: It’s An Amazing Military Decision Framework And Awesome Gift To Business. Also, for ideas on how systems today can support Business Agility, see my article, An Agile Decision Platform to Empower Executives For Superior Supply Chain Performance: Here Are The Best Attributes. Lastly, for a more detailed discussion of the different forms of analytics, see my article, A Data Analytics Perspective To Better Empower Supply Chain Managers.

Business Agility: The Best Way For Leveraging Digital Tech To Disrupt Competitors, Seize Opportunities, And Overcome Obstacles

“Technology. It is the physical manifestation of the human will.”

Daniel Suarez

Lastly, if you are in the supply chain industry and have a need to supercharge your decision-making cycles, please contact me to discuss next steps. I’m Randy McClure, and I’ve spent many years solving data analytics and decision support problems. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers.  I specialize in launching new analytics-based strategies, proof-of-concepts and operational pilot projects using emerging technologies and methodologies. To reach me, click here to access my contact form or you can find me on LinkedIn.

For more from SC Tech Insights, see the latest articles on Data Analytics and Decision Science.