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Article • Finance & Planning Intelligence

Prepared for Multiple Futures

The most resilient finance and operations teams in the UK are not the ones with the most accurate single-point forecasts. They are the ones that have institutionalised the discipline of preparing for futures they cannot predict, and built the foundations that allow them to act on those preparations with speed.

Decision Inc. Finance & Planning Advisory 2026
Stefan Gradin
Stefan Gradin Director, Decision Inc. UK
63%
of organisations cannot reliably forecast beyond a six-month horizon
BARC Planning Survey, 2025
36%
of CFOs are confident in their ability to drive impact through AI and advanced analytics
Gartner CFO Research, 2025
15%
of organisations have achieved genuine analytics scale
Decision Inc. Data Maturity Survey, 2025

There is a persistent misunderstanding about what distinguishes high-performing finance functions from their peers in volatile markets. The conventional assumption is that they forecast more accurately, that through better models, more granular data, or more sophisticated analytical methods, they predict what is going to happen with greater precision and plan accordingly.

The evidence does not support this. The leaders we have observed navigating macroeconomic volatility most effectively are not better forecasters in the traditional sense. They are better prepared. They do not plan for one future and then react when it does not materialise. They plan for several, systematically, and they make the decisions required to act on each long before conditions make those decisions urgent.

This distinction, between forecasting accuracy and planning preparedness, is the central insight of what Gartner describes as adaptive scenario planning. It is also the capability that most UK organisations are furthest from having, despite the current urgency to develop it. According to the BARC Planning Survey 2025, 63 per cent of organisations cannot reliably forecast beyond a six-month horizon with meaningful confidence. This is not primarily a data problem. It is a structural problem, a reflection of planning architectures that were built around single-scenario outputs, annual rhythms, and centralised processes that cannot accommodate the speed or complexity that current conditions require.

01 , The Confidence Gap

The Gap Beneath The Surface

Despite widespread investment in data platforms, business intelligence tooling, and FP&A technology, only 36 per cent of CFOs report confidence in their ability to drive measurable business impact through AI and advanced analytics, a finding from Gartner's 2025 CFO research that is striking given the scale of technology investment that has preceded it.

"The shortfall is almost never about technology. It is about the data and governance foundations that give technology something reliable to work with."

An AI-enabled planning model that ingests inconsistent, ungoverned, manually reconciled data does not produce better forecasts. It produces faster versions of unreliable ones. The organisations that are genuinely building forecasting agility have understood this, and they have sequenced their investments accordingly, with governance and foundation first, and advanced capability second.

Our 2025 Data Maturity Survey of 136 organisations found the same pattern: the 15 per cent that had achieved genuine analytics scale had not done so by acquiring more sophisticated technology. They had done so by establishing the governed, trusted, production-grade data foundation that made their technology investments actually perform.

Prepared for multiple futures
The Central Insight

"They do not plan for one future and then react. They plan for several, systematically."

02 , The Three Disciplines

Institutionalising Scenario Preparedness

The finance functions that have made genuine progress on scenario planning have done so through three disciplines that are practised systematically rather than deployed opportunistically.

Discipline 01
Quantifying Risk Before It Materialises

The development of quantitative models that connect macroeconomic and operational drivers directly to financial outcomes, so that when a risk scenario begins to emerge, the financial implications are understood in advance rather than calculated under pressure. These models link Bank of England rate movements to financing costs, energy price indices to production margins, labour market data to payroll exposure, and demand indicators to revenue assumptions. The discipline here is the deliberate mapping of the external variables that matter most, the two or three drivers that have the greatest impact on financial outcomes, and ensuring those drivers are connected to the planning model automatically, governed, and in real time rather than manual, inconsistent, and lagged.

Discipline 02
Predefining Responses, Not Just Scenarios

The separation of scenario analysis from scenario response. Most organisations that practise scenario planning produce analysis, a set of financial projections under different assumptions. Fewer take the next step, which is to define, in advance, the operational and financial decisions that will be triggered under each scenario. High performers maintain planning playbooks: pre-agreed responses, validated by finance and operations leadership, that specify which costs are discretionary and reducible on what timescale, which capital commitments can be deferred and at what cost, and where capacity can be flexed and with what financial implications. When conditions move, the question is not what to do. It is which playbook is now in effect. This reduces the decision latency from weeks to days.

Discipline 03
Building Board-Ready Narratives Before They Are Needed

The production of board-ready scenario narratives as a standing output of the planning process, not as an emergency deliverable. In most organisations, the board receives a single financial forecast, a point estimate presented as the plan, with limited visibility of the range of outcomes around it or the assumptions that could cause it to vary. High-performing finance functions present scenarios as a matter of routine: here is the base case, here is the downside, here is the recovery path from the downside, and here are the early indicators that will tell us which direction we are moving in. This changes the board conversation from one of approval and accountability to one of informed decision-making.

03 , The Foundation

What Makes All Three Disciplines Possible

None of these three disciplines is achievable at speed without a governed data foundation that connects operational reality to financial planning in a reliable, trusted way.

A mega-scale urban development programme we supported had exactly the inverse problem: an environment where manual reconciliation processes were consuming so much analytical capacity that forward-looking scenario analysis was structurally impossible. Finance teams were spending the majority of their time confirming what had happened rather than modelling what might.

The solution was a governed, self-service analytics platform designed for over 500 users across the organisation, with automated pipelines, formal data quality controls, and end-to-end data lineage that eliminated the reconciliation overhead entirely. The outcomes were transformative:

126%
improvement in speed of access to business-ready data
90%
reduction in manual reconciliation effort
Hours
to produce board-ready scenario narratives, down from days
The finance function did not get smarter. It got faster, because the data it was working from became trustworthy enough to use without verification. This is the enabling condition for institutional scenario preparedness: not a better planning tool, but a data foundation that the planning tool can actually rely on.
04 , The Path Forward

From Reactive To Prepared

For finance and operations leaders reading this and recognising the gap between where their organisations are and where they need to be, the path forward does not begin with a new scenario planning methodology or an FP&A platform selection process.

It begins with an honest assessment of the data foundation: how trustworthy is the data that planning decisions are based on, how much capacity is currently consumed by reconciliation and verification rather than analysis, and what specific use cases, if resolved, would have the most material impact on planning quality and speed.

From that baseline, the approach is deliberate and staged. Focused eight-week sprints that deliver specific improvements to data trust, driver connectivity, or scenario capability, each one building on the last and contributing to a governed platform that scales across the organisation rather than delivering point solutions that fragment over time. This is the critical difference between organisations with five disconnected planning models and organisations with a single, governed, trusted environment that serves every planning need.

Our Enterprise Grade Roadmap and Governance Accelerator are designed precisely for this journey, establishing the strategic programme and the technical foundation in parallel, ensuring that governance, architecture, and business value are built together from sprint one rather than bolted on afterwards.

In Summary

The organisations that will lead in the next phase of UK economic conditions are not those with the best predictions. They are those that are already prepared for the ones they did not predict.

Scenario preparedness is not a planning luxury. It is the competitive infrastructure that determines how quickly an organisation can move when conditions change. The window to build it, before the next shock arrives, is open now.

Sources

ICAEW Business Confidence Monitor Q1-Q3 2025 • Gartner CFO Priorities Survey, August 2025 • BARC Planning Survey 2025 • Gartner Adaptive Planning Research 2026 • Decision Inc. 2025 Data Maturity Survey

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