Some sage words from our new strategic business advisor Jim Muir – He is a Chartered

Jim Muir
Jim Muir

Accountant and Non-Executive Director having held partner positions in international professional services firms. (To find out more about Jim click on his LinkedIn page

As a Non-Executive Director, the most difficult part of the role is stress-testing or imagining business scenarios to provide a rigorous challenge to the Executive Team. The role is not to double-guess the Executive but to satisfy oneself that there is a robust process and that process is being followed diligently.

Much of the management information presented to boards is a rear-mirror view (often articulated in financial KPIs) where historical trends are often extrapolated “simply” with, perhaps, some sensitivity analyses with fairly static assumptions around key inputs.

Analytics Many of these inputs are at a macro level economically or are business specific idiosyncratic. These sensitivity analyses are often presented as stress tests and can be very linear in terms of outputs, often expressed in financial measures with very little drill down beyond the top level into operational impacts and other “side effects”. The process tends to be very manual and infrequent.

This can have the effect of the corporate planning preparation (and monitoring) in a business resting solely or mainly with the finance team and the board; reviewing the outputs in a very wide range, possibly supported by some financial “early warning indicators” to measure the drift from plan and to invoke some sort of remediation.

Often the connectivity of cause and impact is unclear and consequently, much of the remediation effort and energy is attempting to tackle or counteract the symptoms rather than assess or understand the root cause (which may ultimately be beyond the control of the organisation, in any event, and thus can be wasted energy).

Yet, historical data can be better used to predict business impacts. By understanding the most important drivers in an organisation, these can be connected with a full set of outcomes from financial to operational. Scenarios can be developed using these drivers to create a thorough and rich view of situations to allow contingency planning and remediation should any of the early warning indicators confirm a particular eventuality. Importantly, these programmed relationships can be in constant review with little or no manual intervention until an action has been triggered.

By examining past data, relationships can be established across a whole range of factors and outcomes to better statistically forecast the implications of a continuance of, or recurrence of, a particular event or cause. Many such relationships can be discovered and programmed giving a very rich predictive tool for advanced planning; the maintenance of which, through automation, can be very low-cost. Consequently, energies are expended on examining the predictions and forecasts to identify statistically meaningful risks (and opportunities). Plans can be drawn up at a more granular level and competitive advantage exploited (e.g. early price mover, instigated recruitment campaigns, capital investment acceleration or liquidity optimisation).

There is an enormous opportunity for businesses to exploit uncertainty by faster and more robust reaction to events. While the competition is muddling around wondering what to do about a historical result, the true winners will have seen it coming; will have set plans in motion; and will be further round the remediation loop assessing the effectiveness of their reaction to the event. Constant replenishment of data relationships will give depth to the plans and meaning to them such that a truly joined-up response can be implemented organisation-wide.

Planning is bringing the future into the present so that you can do something about it now” (Alan Lakein).

Many of the organisations with which I have consulted are data rich but insight poor. The team at IwP have a different approach which is helping clients predict a full set of outcomes based on the predicted movements of critical drivers. From operational to financial, these predictions are robust and granular allowing a pre-emptive action to exploit or mitigate the effects of movements. I am excited about these capabilities and their impact on maximising my clients business performance and improving risk management.

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