Complexity isn’t always the problem. Inconsistency could be.
No two warehouses are identical. Customers, volumes, automation, systems and operating constraints all vary. But that doesn’t mean every site should invent its own way of making the same important decisions.
That is where complexity becomes expensive. Different spreadsheets, assumptions and planning logic create local capability, but not network capability. You can execute well without always knowing why one site made a different call from another — or whether that difference was justified.
The answer isn’t to make every warehouse work the same way. It is to make important decisions in the same disciplined way: common questions, clear trade-offs and consistent logic, while reflecting the reality of each operation.
This month’s stories echo that. Better data, visibility and AI matter. But their value comes from turning insight into better, more accountable decisions.
That’s what we do.
Phil, CEO
MIT researchers find that AI can produce supply-chain insight far faster than organisations can act on it. The remaining challenge is often human and operational: agreeing priorities, understanding trade-offs and deciding where judgement adds value rather than simply adding another layer of intervention. (7 mins)
Cisco’s demand-planning agent is saving planners at least six hours each week. But the bigger question, according to an article in Supply Chain Management Review, is what happens next: turning that capacity into better planning requires reliable data, business context and clear ownership of the decisions AI supports. (10 mins)
Supply chains have spent years improving visibility. Maersk argues the next opportunity is turning that information into better decisions: identifying risks, comparing scenarios and understanding the trade-offs before acting. (9 mins)
McKinsey argues the next phase of enterprise AI is an intelligence layer connecting data, institutional knowledge and decisions across the business. The ambition is not simply faster tasks, but faster planning, clearer choices and quicker action, something we’re starting to enable. (27 mins)
Half of UK CEOs surveyed by EY say AI is already contributing materially to productivity. Yet only 14% have comprehensive visibility of its costs and returns, highlighting the growing challenge of turning individual efficiency gains into measurable business performance. (6 mins)
As AI agents gain authority, governance is becoming an operating requirement rather than a policy exercise. IBM finds many businesses expect agents to make more decisions, while their controls, audit trails and accountability structures are struggling to keep pace. (8 mins)
AI adoption across Europe's workforce is highly uneven: around 40% of white-collar workers use it at work compared with just 6% in elementary occupations. So far, exposure to AI has not translated into clear economy-wide job losses — but the skills and adoption gap is widening. (4 mins)
About Predyktable
Predyktable helps warehouse and logistics teams make better labour decisions from planning through to execution.
Our Labour Decision Intelligence platform combines demand, workload, productivity, workforce availability and operational constraints to determine how much labour is needed, create the right rota, deploy people where they deliver most value and adapt as conditions change.
The result is tighter control of labour spend, better visibility of cost and service trade-offs, more effective use of existing capacity and less reliance on overtime, agency and reactive firefighting.
We work with retailers, grocers and logistics operators where labour is a major cost, operations are complex or volatile, and better labour decisions can materially improve cost, service and operational performance.
Until next month,
Team Predyktable