In the face of the increased volatility, complexity and interconnectivity which has become the 'new normal' for many companies, the ability of CFOs and finance functions to understand, quantify, manage and leverage risk is more important now than perhaps ever before. And yet, many organisations are still struggling to find practical solutions for the incorporation of risk into planning and decision-making.
There is increased pressure on CFOs from Boards, investors, and financiers to manage and optimise the risk-return balance of the company, and to more explicitly reflect the volatility in forecasts and plans. However, it is recognised that existing approaches to reflect uncertainty within the planning of the business are no longer fit-for-purpose.
CFOs have a need and a responsibility to act decisively to build new capabilities in order to fulfil the business partner and strategist role, and to target more value from strategic risk-return management. Risk-adjusted forecasting and planning is a powerful yet pragmatic response that allows organisations to respond to these pressures and to build lasting capabilities – focused on value protection and creation.
Risk-adjusted forecasting and planning
Risk-adjusted forecasting and planning involves shocking the financial forecasts with major risk drivers in an integrated and flexible manner. The approach allows a more robust and transparent evaluation of volatility and risk within current plans – helping to build a better understanding of the potential upside and downside inherent in the future of the business. The key elements of a risk adjusted forecasting and planning model are a set of inputs, a quantitative modelling 'engine', and a suite of outputs.
- Inputs - the inputs consist of consolidated financial planning data together with macro and micro risk drivers, such as demand uncertainty, volatility in specific elements of the cost-base, macro-economic factors, foreign exchange risk, regulatory changes, raw materials/commodity price volatility, etc.
- Modelling engine - the modelling engine uses quantitative techniques (based on Monte Carlo methods) to combine the risk drivers with the relevant components of the 'base-case' financial forecasts
- Risk-adjusted outputs - risk-adjusted outputs (e.g. cash-flow and earnings-at-risk metrics) allow the organisation to identify and understand key areas of volatility and exposure from a value enhancement and protection perspective.
These approaches focus on underlying factors rather than simply impact, meaning that multiple driver contributions to volatility can be analysed simultaneously rather than looking at single variables. The benefits to CFOs and to the organisation are various, and include:
- Improving the reliability of financial and strategic planning, both at group level, and within the business units and segments of the organisation
- Building transparency, within the organisation and when facing off to the investor community
- Developing stronger approaches to risk-return management to enable optimal capital allocation
Making it work in practice
For CFOs who aspire to take action and enhance the organisational risk-return capabilities, it need not require a major new initiative. The route to implementation is though a flexible and targeted pilot rather than a firm-wide reengineering project – acting on specific problems or areas, making significant quick wins, and contributing tangibly to the competitive positioning of the business.
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