Imagine a supply chain executive poring over yet another spreadsheet, relying on gut instinct to make a decision that could either make or break the company. Incredibly, this is the norm in the supply chain industry despite many executives having access to teams of analysts, AI and sophisticated planning tools. Indeed, this no longer needs to be the case. In fact, advanced AI and data analytics is available where executives can now directly interact with software for rapid, informed decisions. This is what I call an agile Decision Platform—a multi-channel command center offering cross-functional insights, optimal choices, and organizational alignment, all at lightning speed.

Despite many years in the supply chain tech field, I continue to see traditional enterprise systems and decision support systems failing to meet executive needs. At the same time, digitalization demands real-time decisions in uncertain environments. It is a fact that current analytical tools often fall short and are rarely cost-effective in meeting senior executives’ decision-making needs. Hence, in this article, I’ll detail the essential software attributes needed for an agile Decision Platform that CEOs, COOs, and CFOs truly need. My aim is to demonstrate that we can better equip senior executives’ decision-making processes, exploiting emerging analytical technologies to maximize supply chain’s performance. So, let’s get started.

1. Executive Agility: Harnessing Emerging Tech for Rapid, Better Decision-Making.

In today’s digital age, I am convinced that corporate executives need to change their decision-making approach and how they use decision support software to stay competitive. To do this, first, senior executives need to take on an agile mindset that will enable their organizations to adapt and fully leverage technologies like AI, advanced analytics, and IoT. Without a doubt, by becoming more agile, business leaders can exploit digital technologies to swiftly adapt to market changes, continuously deliver value to customers, and drive innovation. Moreover, agility coupled with digital tech turns data into insights, insights into action, and action into favorable outcomes. Indeed, embracing Business Agility isn’t just about survival; it’s about thriving in an era of rapid change and disruption.

Below are six compelling reasons why Business Agility is a must-have in the digital age.

Six Ways Decision-Makers Can Capitalize on Emerging Digital Technologies

Business Agility and Its Many Ways to Exploit Digital Tech

• Move Toward Rapid, Iterative Decision Cycles: This reduces decision delays, faster business execution.
• Focus on Big Picture and Anomalies: Leverage tech to observe situational changes, both physical and digital.
• Exploit Data Analytics: Direct tech to make sense of data, confirm challenges and opportunities.
• Leverage Decision Intelligence Tech for Better Business Decision-Making: Favor Agile Decision Intelligence, not just Business Process Automation.
• Maximize Use of Digital Communications for Decision Execution: Leverage tech for organizational communications, readiness, and adapting to change.
• Facilitate Continuous Feedback: Coupled with a rapid decision-making cycle, incorporate continuous feedback to learn from decisions and make improvements as necessary.

For more details on how to use Business Agility to exploit emerging tech, see my article, Business Agility and Its Many Ways to Exploit Digital Tech.

“… senior executives need to take on an agile mindset that will enable their organizations to adapt and fully leverage technologies like AI, advanced analytics, and IoT.”

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

Also, without a doubt, current supply chain software and analytics tools are costly. What’s more they have significant gaps in supporting corporate decision-making. Indeed, most, if not all, supply chain software applications are digital silos by design. This is because they support only one function such as warehousing or accounting. Additionally, this lack of a comprehensive view causes executives 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. To detail, below are different types of enterprise software and the reasons why they do not meet the informational and agility needs of corporate decision-makers.

6 Reasons Why Enterprise Software Does Not Meet Executive’s Agility Needs

Agile Supply Chain Decision-Making: First You Need to Know The Truth About Enterprise Software

• Execution Systems: First, these systems (ex. WMS, TMS, OMS) are not designed for cross-functional, executive decision-making.
• Visibility and Tracking Systems: This type of software identifies problems, not solutions.
• Planning and Modeling Software: Here, these systems lack agility and do not work directly with decision-makers.
• Analytics and Knowledge Tools: These tools are short on practical utility for agile decision-making.
• Backend and Customer Support Business Systems: Basically, these are isolated data silos, not designed for agile supply chain decision-making.
• Business Automation – BPA, RPA, Personal Assistants, Autonomous AI: Lastly, this type of software is designed more for automation support, not decision support.

For a more detailed discussion on the disconnects between enterprise systems and agile decision-making, see my article, Agile Supply Chain Decision-Making: First You Need to Know The Truth About Enterprise Software.

So, today’s executives drown in supply chain data but starve for real insights. Current enterprise systems can’t answer critical questions: What’s about to go wrong? What should we do? Without proper decision-support tools, top executives to include CEOs, COOs, and CFOs rely on gut instinct, Excel, or transactional software not designed for agility. These outdated approaches fail in today’s fast-paced business environment. Supply chain leaders need agile decision-making capabilities now.

“… today’s executives drown in supply chain data but starve for real insights.”

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

Without a doubt, business executives increasingly face immense pressure to make swift, data-driven decisions that impact their entire organization to include their supply chains. So, it’s time to rethink how software technology supports executive decision-making. What is possible, and needed, is an Agile Decision Platform that empowers leaders to rapidly optimize supply chain performance. Below, I’ll describe an executive-level Decision Platform to include its key five attributes: targeted data collection, agile decision intelligence, executive-level User Interface (UI), rapid decision-based communications, and decision traceability.

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

To make effective decisions, corporate executives require an on-demand data collection platform that prioritizes timely and relevant data versus periodic “data dumps” or complex Digital Twins. For example, an organization could use a BI dashboard with automated alerts—facilitating an iterative process to collect targeted information for rapid corporate decision-making. Without a doubt, an executive-level Decision Platform needs to be data ready, facilitating an iterative, information gathering process to support timely, informed decision-making. The following five-step process details how an executive-level Decision Platform could quickly gather essential insights to support agile decision-making.

A Five-Step Process to Gather Relevant Information that Is Targeted and Timely

Be Data Ready: It’s About Relevant Information — Targeted and Timely — for the Best Business Decisions

1. Know Your Desired Outcome: The smart start to information collection and better decision-making.
2. Map out your decision criteria, scope and constraints to guide your information gathering.
3. Think through what relevant information you need to know.
4. Determine what relevant information is missing – the raw data you need.
5. Gather, clarify, and deliver the most relevant information you can in the time available.

For a detailed breakout of this 5-Step information gathering process, see my article, Be Data Ready: It’s About Relevant Information — Targeted and Timely — for the Best Business Decisions

“… corporate executives require an on-demand data collection platform that prioritizes timely and relevant data versus periodic “data dumps” or complex Digital Twins.”

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

Also, an executive-level Decision Platform requires agile Decision Intelligence (DI) powered by a seamless analytical continuum that is descriptive, diagnoses, predictive, and prescriptive. Rather than operating in isolation, analytics that support executive-level decision-making must work in concert to transform raw data into actionable insights. To maintain agility, the platform must also incorporate on-demand insights, AI-powered analytics and dynamic feedback loops that continuously learn and adapt. See below for a breakout of the analytical components of Decision Intelligence.

The Analytics Continuum Working in Concert.

Below are the baseline analytics capabilities of Decision Intelligence.

• Descriptive Data Analytics. Confirms the status quo, identifies trends, and discovers anomalies. Can trigger other types of analytics such as diagnostics. 
• Diagnostic Data Analytics. Identifies root causes, determining the “why” behind a trend, or validating a hypothesis. Can trigger further analytics such as predictive or prescriptive.
• Predictive Data Analytics. Makes forecasts about the future. Can trigger other analytics types. 
• Prescriptive Data Analytics. It uses advanced algorithms to recommend a specific course of action, explain why it is the best, and provide details on how to implement it. Works in concert with other types of analytics.

For more details on the Business Analytics Continuum, see my article, Exploit The Business Analytics Continuum For Awesome Data-Driven Decision-Making Results.

The Agile Components of Decision Intelligence.

Moreover, to support executive-level decision-making, Decision Intelligence requires adaptability, speed of execution, and continuous learning. See below for the agile components of Decision Intelligence.

Agile Decision Intelligence: High-Velocity Analytics To Best Empower Executives In A Quickly Changing World

• On-Demand, Real-Time Analytics. Here, powerful computing capabilities enable rapid analytics that provides on-demand results based on the decision-maker’s operational tempo and decision requirements.
• AI-Powered Analytics. Also, AI can supercharge data analytics. It is able to work with massive data sets, unstructured data, and knowledge-based tools. Also, it has agent-based AI capability to act autonomously.
• Continuous Feedback loops. Lastly, it is critical that DI incorporates feedback based on real-world outcomes. As a result, it continues to learn and adapt to improve its decision support capabilities. Basically, it gets smarter over time. 

For a more in-depth discussion on Decision Intelligence’s analytics capabilities, see my article, Agile Decision Intelligence: High-Velocity Analytics To Best Empower Executives In A Quickly Changing World.

“… executive-level Decision Platform requires … a seamless analytical continuum that is descriptive, diagnoses, predictive, and prescriptive. … also incorporate on-demand insights, AI-powered analytics and dynamic feedback loops that continuously learn and adapt.”

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

Despite great information technology advancements, there is a significant disconnect between modern analytical tools and executive-level decision-making. Unquestionably, most executives still lean on gut instinct and basic spreadsheets. This is despite organizations investing in costly business software, sophisticated BI dashboards and complex “digital twins” that often go unused. To bridge this gap, imagine a “digital command center” for executives, similar to a fighter pilot’s cockpit. This would not necessarily be one piece of software, but a multi-channel user interface (UI) for executives designed for volatile, rapid decision environments. Without a doubt, we can put advanced analytics and AI directly into executives’ hands, allowing them to interact with critical insights through their smartphones, tablets, or even dedicated command centers.

An UI for Agile Executive Decision-Making: Five Interactive Components

For an example of an executive decision-making UI, see below. Indeed, by leveraging advanced technologies, executives can have a seamless, adaptable user experience where they directly Observe, Orient, Decide, Act (OODA), and Adapt to make rapid, informed decisions.

An Executive Decision-Making UI: A Stunning Way To More Quickly Observe, Orient, Decide, And Shatter The Competition

1. Observe: Empowers executives to observe the ever-changing digital landscape.
2. Orient: Enables executives to determine the why behind problems and opportunities.
3. Decide: Flexible, High-speed UI to enable executive decision-makers to make quick, informed decisions and conduct rapid pre-implementation planning.
4. Action: An UI to support decision execution, communications, and measures results.
5. Adapt: Lastly, a feedback loop UI to incorporate lessons-learned, add knowledge and adjust strategies.

For a more detailed discussion on this topic, see my article, An Executive Decision-Making UI: A Stunning Way To More Quickly Observe, Orient, Decide, And Shatter The Competition. Here, I provide a detailed description of the major UI attributes for each of these five interactive modules (Observe, Orient, Decide, Act, Adapt).

“… a multi-channel user interface (UI) for executives designed for volatile, rapid decision environments … put advanced analytics and AI directly into executives’ hands, allowing them to interact with critical insights …”

d. Rapid Decision-Making Communications.

An agile Decision 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, an agile Decision Platform should have an API that enables executives to use their preferred business communications tools to communicate their decisions.

Also, an agile Decision Platform would need an interface to sync with knowledge platforms and other systems for the purpose of creating or updating policies based on decisions that affect organizations and systems. Further, z Decision 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.

“… An agile Decision Platform … needs to facilitate collaborative decision-making … to support the effective transmission of decisions across the supply chain and within organizations.”

e. Decision Platform Traceability.

Also, an agile Decision Platform must incorporate robust decision traceability to effectively measure the impact of decisions. This includes documenting critical team actions, such as why system recommendations were rejected, and identifying missed opportunities. As a result, decision traceability records what the decision was, the expected results, and who made it. With this information, executives can receive constructive feedback as the system measures expected results against actual results. Thus, Decision Platform traceability ensures accountability and the capability for the decision team to learn from past decisions, update policies, and optimize best practices.

“… Decision Platform traceability ensures accountability and the capability for the decision team to learn from past decisions, update policies, and optimize best practices.”

Conclusion.

With our current technological capabilities, we can design software that empowers corporate executives within an agile decision-making environment. Without a doubt, this is what will ultimately maximize executive-level decision-making and supply chain performance. This article has outlined the essential software attributes for such an executive-level Decision Platform, leveraging advancements in AI, data analytics, Decision Intelligence, and knowledge graphs. Moreover, this multi-channel platform, with its intuitive user interface, offers an agile workspace that enables executives to directly engage in a compressed OODA Loop decision cycle—Observe, Orient, Decide, and Act—to optimize their supply chain’s efficiency and responsiveness.

References and Resources.

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.
• Lastly, here are more links about the information technology that enables an agile Decision Platform: Knowledge Graphs, Advanced Analytics, AI, OODA Loop, Decision Platforms, and Decision Intelligence.

A Breakthrough In Decision Systems: The Need For AI Analytics To Best Empower Executive Insights

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 proof-of-concept and pilot projects for emerging technologies. 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 decision science, supply chain, and data.