Why AI requires Supply Chains to Think Differently
The best process improvement for your supply chain may involve your thought process. AI adopts your thoughts and beliefs about the supply chain into the business process, for better or worse. If you want more effective AI, start with more effective thinking.
Let’s examine why you may want to change your thinking before you implement supply chain AI.
AI Requires Supply Chains to Think Differently
Gartner’s 2022 CIO and Technology Executive Survey of 2,387 CIO and technology executives in 85 countries focused on "business composability", - which involves the mindset, technologies, and set of operating capabilities that enable organizations to innovate and adapt quickly to changing business needs.
- More than half of the respondents indicated they plan to invest heavily in business intelligence and data analytics next year.
- Monika Sinha, research vice president at Gartner, said, “Business composability isn’t uniformly high across the economy because it requires business thinking to be reinvented. Traditional business thinking views change as a risk, while composable thinking is the means to master the risk of accelerating change and to create new business value,” Sinha added.
Reinventing thinking. Companies must rethink business models, processes, strategies, and risks with AI. Issues like solving the Supply Chain 4.0 riddle, will be taken out of the closet for reexamination. But first, we need to understand a little about the current state of supply chain AI.
AI Depends on Our Thinking
Supply chain AI is a tool limited only by our thinking, literally. An AI gets its intelligence from multiple sources, including engineers that built the algorithms, but primarily from the business enterprise employing it.
The business enterprise is a working model of your corporate thought process - a company’s strategies, values, priorities, tactics, methods, and culture. The business process supports this model, and decision-making in workflow aims to keep efforts in compliance. The people and systems that comprise this process provide intelligence. This is the intelligence that fuels AI.
What You See is What You Get
AI’s effectiveness depends on how coherent this enterprise intelligence is. A holistic enterprise with aligned processes, data, and business rules readily translates intelligence to humans and AI. Coherent thinking produces coherent enterprises, and the opposite is also true.
AI algorithms parse an enterprise’s strategies, priorities, values, and decisions to synthesize the rules for its supply chain. These include rules built up over the years that sustain systemic dysfunction rooted in legacy systems and a flawed supply chain model. It’s baked into the enterprise and is the invisible source of many supply chain problems.
The business enterprise cannot detect the cause of systemic problems, nor can AI - unless there’s a change in thinking to shift perspective.
AI Enables Self Reflection
AI is like a mirror in several ways, mimicking our thought processes and reflecting them in the rules it formulates. Many AI-enabled apps have dashboards for visualizing supply chain health, problem areas, and resolutions which facilitate clarity. Tools like this can make it easier to assemble a mental image (model) of the supply chain processes, improving understanding of the processes involved.
With greater clarity, self-reflection is possible, and it may reveal the truth: we can’t fix a supply chain with the same thinking that created the problems. That’s why we are blind to systemic dysfunction. We can’t fix a problem we can’t see.
Too bad AI is not a magic mirror that reveals the flaws in our thinking. Instead, it reflects our thoughts. AI can end up optimizing a flawed process, and the improvements will justify its use, but the supply chain will never reach its full potential until the source of the problem is revealed and corrected.
The Lame Blame Game
Why talk about invisible problems when we can see and feel the wildfire threatening supply chains? Poor visibility. Volatility. Transportation crunch. Blaming the external events that reveal the weakness of our solutions is easier than looking in the mirror for the truth.
We kick the can down the road, blame a virus, and grumble about political incompetence. AI doesn’t know about those things; it just needs us to create systems that keep feeding it data - systems that don’t fail.
Reflecting on these points us to: mismanagement, unrealistic plans, failures to assess risks, poor analysis, bad project management, training, neglect of continuous improvement, shoddy implementation.
Again, a problem in our thinking prevents us from seeing the problem in our supply chain. AI can’t fix these problems, and neither can we if we are blind to them.
OK. So how do we change our thinking?
Effective Thinking Produces Effective AI
Effective thinking produces effective AI. What does effective thinking look like for a supply chain? The answer is simple: a clear, holistic supply chain process that’s purpose-driven. A good supply chain model supported by a lean logistics process is evidence of such thinking.
AI just needs a good platform to start with - your thinking.
