Key Driver Analysis Modelling

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Key Driver Analysis Modelling

by Rickard Warnelid on February 28 2011

During October 2010, the CPA Congress was held in New South Wales, Queensland and Tasmania. Dr Liam Bastick, Director of Corality (Melbourne) was invited to deliver a series of presentations and workshops during the course of the event.

 

Key driver analysis

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Presentation: Key driver analysis modelling

In his presentation, “Key Driver Analysis Modelling”, Liam Bastick explained the central issue associated with model forecasting, and discussed three common approaches to risk evaluation, Strategic Options Analysis (SOA) and real options analysis.

“I presented a high level overview of how to determine and quantify what the key drivers of a business are using scenario, sensitivity, simulations and real options analyses.” - Liam Bastick

Importance of understanding key driver analysis modelling

We are frequently required to build Excel spreadsheets which are based upon single point estimates of key variables, in the context of uncertain future expectations. In order to incorporate the role of uncertainty within the model, we use single-point values as a “proxy” for a range, we add “contingency factors” and may even add a “risk premium” to discounts rates used in evaluating NPVs.

When doing this, it is important to understand the role of uncertainty and risk in our models.

Presentation snapshot

The presentation “Key Driver Analysis Modelling” covers three common approaches in risk evaluation:
  • Scenarios
  • Sensitivities
  • Simulations

Scenarios are used to generate “top down” views, whereby several variables are changed in order to simulate particular situations. However, a key issue with this approach is that changing variables can be cumbersome, and there are issues with lack of knowledge regarding the likelihood of each scenario occurring.

In contrast to scenarios, sensitivities are used to generate “bottom up” views, where we change a single variable and measure its impact on key outputs. Because only one variable is being varied at a time, this technique requires careful interpretation otherwise it may lead to unrealistic results.

In simulations, we adopt a probabilistic approach, where all assumptions under consideration are varied at the same time, and interrelationships and correlations are included. Since this method takes into account a large number of scenarios and correlations, it could be perceived as the preferred method. However, it can be time intensive.

Strategic Options Analysis (SOA)

SOA is an application of scenario analysis. Liam discussed the four stages of SOA in his presentation:

  • Frame strategic options
  • Develop strategic options
  • Analyse and value strategic options
  • Decide on strategic options, lay out business plan

Real Options

NPV is frequently used in investment decision analysis. It considers the shareholder value maximization objective and considers the time value of money. However, a significant issue with NPV analysis is that it does not consider the value of embedded options.

It is therefore preferred to use real options as it enables us to capture:

  • Value to delay
  • Value to expand
  • Value to abandon

Real options is the practical application of financial options theory to real assets, using quite complex mathematics.  This proves challenging for many end users and therefore, this technique should be used with caution and transparency borne in mind.

Key findings

Make sure to:

  • Understand different approaches to risk evaluation (scenarios, sensitivities, simulations)
  • Understand the stages involved in Strategic Options Analysis (SOA)
  • Recognize the limitations of NPV, and the advantages of using real options to capture value to delay, expand or abandon

Download presentation

Click here to view and download a condensed version of the presentation.

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