Your Planning Maturity Diagnostic

Three in four senior executives don’t trust their plan enough to use it for full P&L trade-off decisions. That isn’t a data problem. It’s a maturity problem.

Only about one in four senior executives trust their planning enough for full P&L trade-offs (McKinsey 2022); the rest work around the plan. And roughly two-thirds of organisations still run S&OP / IBP as a periodic review meeting rather than a continuous decision engine. This isn’t a data or software problem — it’s a maturity problem. The gap to the mature minority is measurable, costed, and closeable. That’s what this report is for: your result in context, the gap, the cost, and the value of closing it.

You land at Developing (41/100). High maturity is a minority: fewer than 10% of organisations have the governance and incentives of Leading IBP (McKinsey 2022); most cluster in Developing and Defined. Leaders aren’t using better software — they have finance in the room every cycle, quantified exec trade-offs, and a plan treated as the operating commitment. The gap is behavioural and structural before it’s technical. You have the bones of a process, but it’s inconsistent and rarely drives real trade-off decisions.

Five stages, each a structural signature — behaviours and governance, not features. The gap is rarely where people think: the root cause sits upstream, in who owns the process with authority, whether S&OP is the decision forum or a ritual, and whether the plan is the single source of truth. Fewer than 10% have the incentive structures that separate Advanced from Leading (McKinsey 2022) — incentives are the deepest gate.

This isn’t one clean number — anyone giving you a precise figure for a business they haven’t seen is making it up — but the components and ranges are real. Typical forecast error runs 20–30%+ MAPE (IBF), and inventory becomes the shock absorber for that inaccuracy. Global inventory distortion — overstock plus out-of-stock — is roughly $1.77T (IHL 2023). The mechanism is universal: an untrusted plan means every function buffers, expedites, and works around the number.

Illustrative, not a promise. These figures are illustrative estimates derived from published supply-chain benchmarks and Zuloma practitioner experience. They are not a forecast, guarantee, or commitment of results. Actual outcomes depend on your data quality, product mix, demand volatility, organizational adoption, and execution. Treat the Expected case as a hypothesis to validate, not a promise.

Forecasting adds a further, best-case layer (McKinsey “Supply Chain 4.0”): error down 20–50% and inventory down 20–30% while holding service — but only once data readiness and governance are in place. Planner productivity typically rises 10–20%, which quietly removes the “we don’t have the headcount” objection. These effects compound — and they compound faster when governance is in place before the technology. That sequencing is the roadmap.

Transformations fail on the wrong sequence, not the wrong destination: capability added before the structural gates are fixed doesn’t hold. So this roadmap is your next one to two stages only, aimed at your weakest dimensions first (S&OP > Master Data > Demand > Supply > Inventory > Systems).

Sequence:structural gates first (S&OP, master data) → demand → supply → inventory → systems last.

A bounded 30-day engagement: one working session on your results, a prioritised intervention list specific to you, and a 90-day implementation brief. Not a transformation programme — a focused piece of work that leaves you a plan to execute internally.