Imagine if corporate executives had their own software that could significantly enhance their decision-making to maximize supply chain performance in today’s fast-paced digital world. Indeed, this executive-level decision platform, without any middlemen, would offer cross-functional insights, best options, and support decision-making communications throughout the supply chain. As a result, this tool would make executive-level decision-making more agile. Positively, this is now possible, due to recent advances in AI, data analytics, fast computing, and the global internet. Further, this agile decision platform would enable executives to quickly seize business opportunities and tackle challenges by supporting faster, compressed decision cycles.

In this article, I’ll look at how digitalization is creating a growing requirement for business leaders to be increasingly agile in their decision-making. This is even more true in complex supply chains, where corporate executives are working in a dynamic, digital environment. Also, I’ll identify how current software systems and analytical tools neither meet the agility needs for executive-level decisions, nor are they cost effective. Lastly, I’ll identify the key software attributes that corporate executives need in an agile decision platform that will fully empower their decision-making to maximize supply chain performance. Indeed, corporate executives to include CEOs, COOs, and CFOs need better decision tools to maximize their supply chain performance.

1. Emerging Tech Empowers Corporate Executives to Make Better Decisions Quickly

Today’s information technology allows decision-makers to receive data instantly, enabling quicker and more efficient decisions. What’s more, this instant information access has the potential to allow executives to act faster than their competitors as new opportunities arise. Indeed, emerging information technologies enable them to rapidly Observe, Orient, Decide, and Act without waiting for their organizations to gather and process data. This rapid decision-making ability is similar to a fighter pilot in a dogfight, where actions happen swiftly. In fact, corporate leaders working within this new digital landscape have the opportunity to eliminate information delays that are often the norm in traditional business decision-making cycles.

In today’s age of rapid information, executive management can learn from a military doctrine inspired by fighter pilots. This doctrine is known as the OODA Loop, which stands for Observe, Orient, Decide, and Act. Originally devised by military strategist John Boyd, this four-step continuous loop helps decision-makers formulate quick and effective decisions in high-stakes environments. Indeed, the OODA Loop concept is particularly useful in information-rich, fast-paced situations as is the case with our increasingly digitalized supply chains. By compressing decision cycles, business executives can disrupt competitors by getting inside their decision process. For more information on this concept and how it applies to business, see this article, The Forgotten OODA Loop: It’s An Amazing Military Decision Framework And Awesome Gift To Business.

2. Today’s Supply Chain Software Is Costly and Does Not Meet Executives’ Agility Needs.

Current supply chain software and analytics tools are costly and have significant gaps in supporting corporate decision-making. This is particularly true for CEOs, COOs, and CFOs who need a cross-functional view of their business and supply chains. Indeed, most, if not all, supply chain software are functional, digital silos by design, providing only a limited view. Additionally, this lack of a comprehensive view causes executives in particular to make isolated decisions. As a result, they may fix one problem but create others within the supply chain. Moreover, these digital systems do not provide executives with the agility to quickly implement their decisions throughout the supply chain. Below are different types of supply chain software and reasons why they do not meet the current informational and agility needs of corporate decision-makers.

a. Most Supply Chain Software Lacks Agility for Executive-Level Decision-Making.

Below are types of software found in supply chains.

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• Execution Systems: Possess Rich Transactional Data, But Are in Functional Silos Not Designed for Corporate Decision-Making. These types of systems include TMS, WMS, and OM systems. Select data from these systems are needed for corporate analysis.
• Visibility and Tracking Solutions: May Meet Select Visibility Needs, But Missing Information Such as Demand and Financial Data. For example, these types of systems can include a cloud-based “Control Tower” or a shipment visibility system. These systems are expensive and only provide partial information to executives.
• Planning and Modeling Software: Designed for Planners to Leverage Big Data Sets, Not Designed for Agile Decision-Making. This type of software can include ERP, Inventory Management, S&OP, Digital Twin, Forecasting, and AI-powered systems.
• Analytics and Knowledge Tools: Costly, Labor-Intensive Reports that Decision-Makers Tend to Not Read Nor Take Action On. This type of software includes business intelligence (BI) dashboard and Decision Intelligence systems. Also, includes Machine Learning (ML) pattern matching, AI expert systems, and knowledge graph tech to name a few.
• Many Other Types of Business Systems: Valuable Data Siloed in Back-End and Customer-Facing Systems. These other types of systems have functions such as procurement, payment, accounting, customer relationship, and customer support. At times, the data in these systems are needed by executive management teams.
• Business Automation – BPA, RPA, Personal Assistants, Autonomous AI: Designed to Automate Processes and Execute Tasks, Not Support Executive Decision-Making. Also, within most business environments there is business automation software. This can include Business Process Automation (BPA, Robotic Process Automation (RPA), Personal Assistants, and emerging autonomous AI applications. For a more detailed look at business automation, see my article, Business Automation AI Remake: First Just Tech To Empower Processes And Now Operates Autonomously.

b. The Void in the Supply Chain Software Market: No Agile Decision Platform That Fully Supports Executives.

So, most corporate executives have access to an increasingly vast array of systems containing valuable supply chain data. However, these systems do not adequately support top executives, such as CEOs, COOs, and CFOs, who require a comprehensive view of their supply chains. This disconnect is frustrating for decision-makers, given that the necessary technology and data are available within the supply chain. To conclude, there is a gap in the software market for solutions that empower corporate leadership teams with agile decision-making capabilities.

3. Key Attributes of an Agile Decision Platform for Executive’s to Maximize Supply Chain Performance.

More and more business executives face immense pressure to make swift, data-driven decisions that impact their entire organization to include their supply chains. As discussed previously, various supply chain software and analytics tools exist. However, they often fall short of providing the comprehensive insights and agility executives need. So, it’s time to rethink how we support executive decision-making when it comes to supply chain performance. This means embracing the concept of a dedicated supply chain decision platform for executives. What is possible and needed, is an agile decision platform that empowers corporate leaders to rapidly execute decisions to optimize supply chain performance. I’ll call this supply chain software category Decision Agility (DA). Below, I will describe the ideal attributes for a Decision Agility platform dedicated for executive-level decision-making.

Software Attributes for Decision Agility for Supply Chain Performance

In this section, I describe six key attributes for a Decision Agility platform for executives to maximize supply chain performance. These software attributes include targeted data collection, agile decision intelligence, executive-level UI for the decision-making cycle, rapid decision-based communications, and decision traceability.

a. Targeted Data Collection: Focused on Timeliness and Specific Decision Requirements.

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To make effective decisions, corporate executives need timely and relevant data to minimize information latency and maximize agility. Also, they must see end-to-end how their supply chain is performing and any anomalies or changes that are occurring. So, this is where a Decision Agility system can monitor key performance indicators (KPIs) at the executive level. For instance, they could use a corporate Balanced Scorecard to track supply chain performance. Further the decision platform should provide timely alerts for issues needing executive attention. Indeed, constant data dumps or a “Digital Twin” will likely overwhelm busy executives instead of being useful. Positively, executives need specific, targeted information such as trend data linked to their business goals and alerts for changes and anomalies.

For example, a hypothetical ecommerce company has an inventory turnover rate at their main warehouse that is higher than the industry average. As a result, their Decision Agility platform triggers an alert based on Key Performance Indicator (KPI). Corporate executives then use their DA platform to get a comprehensive view of the problem. For instance, the DA system may then prioritize its data collection efforts and verifying data about the specific problem. This could include inventory levels, sales orders, and on-time, in-full (OTIF) delivery data that would provide executives a complete picture of the situation. As a result of this iterative process, corporate executives have a comprehensive view of the problem. Specifically, they understand the problem in context and are able to gain confidence in what is happening. As a result, the Decision Agility platform helps to confirm the need for a decision, and can gather relevant data for decision-makers to make an informed choice.

b. Agile Decision Intelligence: Analytics for a Fast-Paced, Changing Environment.

The next attribute for an executive-level decision platform is a decision intelligence capability that is agile. Indeed, the heart of a Decision Agility platform is its decision intelligence and analytical tools. For instance, a DA platform would leverage the latest analytical technologies and methods to include Artificial Intelligence (AI), data science, knowledge tools, business intelligence (BI), and decision intelligence. The purpose of this agile decision intelligence capability is to help executives assess changes occurring within the supply chain. Further, it can do its analytics processing within the contextual knowledge of corporate objectives, organization capabilities, and systems available. So, let’s first look at specific analytics capabilities that this system can leverage, and then discuss the need for an executive-level recommendation engine.

1) Agile Decision Analytics.

Indeed, this agile decision intelligence capability needs to operate within a rapid decision cycle, providing assessments using collected data and organizational knowledge databases. Where needed, it is augmented with appropriate expert analysts who have deep expertise in such domains as supply chain, AI or data science. As a result, the Decision Agility platform provides information on what is happening, why it happened, emerging patterns, and what is likely to happen in the future. Additionally, it reveals further questions decision-makers may need answers to. To detail, below is a description of key tools for decision intelligence and analytics include:

Decision Analytics Tools Types

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• Data Analytics. These tools analyze data to determine things like: what happened, why it is happening, and what may happen in the future. For more information on supply chain analytics types, see my article, Supply Chain Analytics Types and The Way They Work To Better Empower Decision-Making.
• Organizational Knowledge Tools. Here, knowledge graph technology enables corporations to capture and retain their organization knowledge. Tools like knowledge graphs are more than a corporate wiki page. Software developers can integrate these knowledge databases with other systems. Indeed, this organizational knowledge supports better, rapid decision-making by placing operational and historical data in context as well as assuring alignment with corporate best practices. For more on emerging knowledge graph tools, see my article, Knowledge Graph Tech: Enabling A More Discerning Perspective For AI.
• Decision Intelligence (DI). With the advent of faster computers, global networks, and AI, there is an emerging analytical software category called decision intelligence. Specifically, analysts use the software to design, model, align, execute, monitor and tune models and processes associated with decision-making. For more information on decision intelligence, see my article, This Is What Decision Intelligence Technology Is And Know What Its Not.

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2) Superior Recommendation Engine. 

Also, as part of agile decision intelligence, a decision platform needs to Interacts directly with decision-makers to provide choices, including risks and opportunities. Further, it offers operational recommendations for immediate decisions and tactical options for near-term decision-making. Strategically, it supports long-range planning decisions and provides an option to automate certain decisions. Further, the recommendation engine needs to document measurable outcomes of recommendations offered. Overall, a Decision Agility platform provides recommendations based on business constraints, competition and operational capabilities. Hence, depending on the situation and timing, corporate executives may make decisions focused at all levels of the corporate decision horizon to include operational, tactical, or strategic.

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c. Executive User Interface (UI): Dedicated Work Space to Observe, Orient, Decide, and Execute Decisions.

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Corporate executives traditionally haven’t used software extensively to help with their decision-making, and especially not for decision-making within dynamic, changing environments. Indeed, they typically rely on slide presentations, white papers, and BI dashboards to get key facts, analysis, and recommendations for a decision. Also, executives use informal communication like e-mail, texts, verbal conversations, and site visits to exchange ideas and assess situations. Additionally, many organizations use custom BI dashboards or software with a BI dashboard interface. However, corporate executives usually don’t interact much with these BI reports.

So, the technology and the need is there for an executive-level UI to support agile decision-making within an information-rich, dynamic environment. Now, I do not necessarily have all the answers for what this UI should be. However, I do have some suggestions that I will discuss below. Also, it is important for this software UI to support decision-makers through each stage of their decision-making process. Therefore, I’ll break out these UI suggestions by each stage of the decision cycle. To do this, I will use the OODA Loop decision cycle steps, Observe, Orient, Decide, Act, to provide suggested improvements to each decision cycle step.

Executive-Level UI Within an Agile Decision-Making Cycle

Step 1. Observe: UI Enables Executives to Observe the Ever-Changing Digital Landscape. 

In this step, the UI needs to focus on helping executives to understand their business situation. Here, supported by cross-functional, targeted data feeds, executives can keep an eye on trends and anomalies. In this case, the UI could be a BI dashboard focusing on key performance indicators (KPI). Further, the UI would provide alert messages as a result of changes and anomalies identified in the business environment. For instance, the BI dashboard could be a Balanced Scorecard depicting operating margins, order fulfillment, and inventory turns. For more details on a corporate-focused Balanced Scorecard, see Lora Cerere in her article, Aligning Supply Chain Metrics to Improve Value.

Step 2. Orient: UI Equips Executives to Orient on Problems and Opportunities Within the Supply Chain. 

Here, executives need an UI that enables both executive-level analysis as well as analytical input from organizational resources, both machine and human generated. Also, it is here that corporate leadership will conclude whether to pursue making a decision based on the new information received. Additionally, this UI needs to support internally generated decision requirements such as new executive-level initiatives or even a new executive such as a new CEO. Further, executives may need assistance from the platform to formulate specific decision requirements. With these requirements, the system generates a more refined analysis for that specific decision. So, the UI for the Orient phase should facilitate these three objectives:

1. Analytics focused on anomalies identified
2. Formulation of specific decision requirements
3. Analytics to support the specific decisions to be made to include determining the confidence level in information provided.

Step 3. Decide: Flexible UI to Enable Executives to Make Informed Decisions and Provide Decision Support.

Here, the UI needs to support executives making informed decisions. This includes considering multiple options, prioritizing decisions, involving the right stakeholders, and making decisions. Also, the UI should place the decision in context to risks and the results of past decisions similar in nature to the current situation.

 Additionally from an UI perspective, executives prefer short, concise communications. Alex Cuthbert in his article, focusing on the problem definition, provides some great advice on UI for executive-level decision-making. This includes providing an UI that focuses on “problem-action-result”. Further, the UI should assist executives with preparing for decision execution by answering questions like, “Who should I tell to do what?” Also, the UI needs to be customizable depending on the executive and type of decision they are making. For instance the UI should be flexible enough to support different decision-making paths to help executives to make the final decision. This can include providing support for different decision approaches such as metrics / impact, consensus / problem definition, operational efficiency, and vision realization to name a few.

Step 4. Action: UI Supports Decision Execution, Communications, and Measures Results. 

In this step, executives need an UI to support the decision execution and document their decisions. Indeed, in an organizational setting, business leaders need software to support clear communications, establishing goals, and monitoring progress when executing a decision. For more UI suggestions for this step, see next sections on the following Decision Agility platform attributes: d. Rapid Decision-Making Communications and e. Decision Traceability.

Again, any decision-making process is an iterative process where the decision cycle repeats itself over and over again. The whole purpose of the executive-level UI is to support this interactive process to enable better, rapid decision-making. Indeed, when executed effectively, a Decision Agility platform UI enables the corporate executive team to compete more effectively by being highly responsive to change and closely aligned with market demands. 

d. Rapid Decision-Making Communications.

A Decision Agility platform for executives also needs to facilitate collaborative decision-making. Further it needs to support the effective transmission of decisions across the supply chain and within organizations. As done today, communications may be via e-mail, text, verbal communication, or some type of team messaging software like Slack. Indeed, a Decision Agility platform should have an API that enables executives to use their preferred business communications tools to communicate their decisions.

Also, a Decision Agility platform would need to interface with knowledge platforms and other systems to define or update policies that may affect organizations and systems. Further, the Decision Agility platform needs to communicate key components of executives’ decisions to managers and other organizations. For example, these decisions could include guidance to commit additional resources, changes in organizations, and business process updates that may require software updates.

e. Decision Traceability.

Also, a Decision Agility platform needs to measure the effectiveness of decisions. Additionally, it needs to document rejected DA platform recommendations and identify missed opportunities by not choosing a particular course of action. The objective of decision traceability is to document what the decision was, the expected results, and who made it. With this information, executives can receive constructive feedback as the system would measure expected results against actual results. Thus, this ensures accountability and the capability to learn from past decisions and optimize best practices.

Conclusion and More References.

Positively, we now have the technological know-how to design software that can empower corporate executives to work within an agile decision-making environment. As a result, executives can more effectively maximize their supply chain’s performance. To help realize this possibility, I have laid out in this article the key software attributes needed for an executive-level Decision Agility (DA) platform. Indeed, this DA platform leverages recent advances in information technology such as AI, data analytics, decision intelligence, and knowledge graphs. At the same time, the user interface (UI) provides an agile decision workspace for executives. As a result, they can use a Decision Agility platform to interact within a compressed decision cycle to Observe, Orient, Decide, and take Action to maximize their supply chain’s performance. 

Also, below are some references that provide examples of where we are with executive-level Decision Agility within the supply chain software industry:

• ThroughPut’s Supply Chain Intelligence Software. ThroughPut Inc’s software embodies the essence of incorporating agility into executive-level decision-making. They describe their software as “…integrates advanced supply chain analytics best practices to quickly identify supply chain bottlenecks, make swift near-term predictions, and offer intelligent recommendations—helping you make high-impact decisions swiftly.”
• The Aera Platform. Aera Technology provides a multi-faceted, decision intelligence platform catering to all levels of supply chain decision-makers, not just corporate executives. They describe their decision platform as,  “The digital brain of your organization, making and executing intelligent business decisions in real time. It delivers outcomes at the speed and scale of your business.”
• OODA Loop – Enterprise Architecture Fundamentals. Rémy Fannader’s book stresses that enterprises are now immersed in a digital environment where change is the norm and agility is a must. Thus, it is paramount that software architects incorporate agility into enterprise systems using such agile concepts as Col. Boyd’s OODA Loop.

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For more from SC Tech Insights, see the latest articles on decision science, supply chain, and data.