Strategy Survival Guide

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• Are the units correct? Step Seven: Let Excel make your life easier Microsoft Excel has a number of features that make analysis easier to navigate and complete: • Sorting • Functions • Aggregation (SUM, AVERAGE, MIN, MAX) • Conditional (IF, AND, OR, Nested IF) • Lookup Values (VLOOKUP, HLOOKUP) • SUMPRODUCT • Table command • Financial functions • Manipulating data strings • Using formulas (LEN, LEFT, RIGHT, MID, SEARCH, TRIM, CONCATENATE) • Converting text to columns • Formatting cells • Pivot tables • Conditional formatting. Step Eight: Understand the sensitivities Having built the model and development output, understand the sensitivities of the output to key input variables. To do this, undertake three key steps: • Determine the range of valid values for each variable • Test impact by changing each variable on its own • Test impact by changing combinations of variables. A good first pass of the two tests is to change the values of the variables in the assumptions sheet to their maximums and minimums. Step Nine: Presenting the Results Much of the impact of analysis can be lost if it is presented badly. In particular, complex modelling with many variables and sub-analyses can easily become confusing and lose credibility unless presented logically and sequentially. Think very carefully about the story the analysis tells. Transparency is crucial, as much discussion will be held over assumptions in the model. A typical presentation to explain an Excel model would cover: • Overall objective of the model • What the model can and can’t do • A schematic overview of how the model works • The key data sources • How logic of how the variables are combined to produce the outputs • The key inputs, the value of each and the rationale for this value • The key assumptions, the value of each and the rationale for this value. Econometric Modelling This is the application of mathematical and statistical techniques to economic and social problems. Econometric studies proceed by formulating a mathematical model, then, using the best data available, statistical methods are used to obtain estimates of the parameters in the model. Methods of statistical interference are then used to decide whether the hypothesis underlying the model can be rejected or not. Econometrics is thus concerned with testing the validity of economic and social theories and providing the means of making quantitative predictions. Regression analysis is a major tool of econometrics. It permits different hypotheses to be tested about the forms of the relationship and the variables that should be included in it. Strategy Survival Guide – Strategy Skills Page 132
Regression analysis is used to determine relationships between variables that analysts believe intuitively to be related. Once a relationship is established, it can be used to forecast the outcome. In business, regression analysis is often used to examine the relationship between: • Sales, price, promotion and market factors • Production costs to production volumes It is equally useful to policy makers as illustrated in the ‘in practice’ example. See BMJ.com for more detailed guidance on how to use these techniques. Strengths • There are a variety of different tools with which to conduct data analysis. The key is to keep focused on the specific question/task, and not allow the focus of the analysis to stray. • Modelling can provide a clear structure for the analysis, which can help create buy-in to the process from other government departments. • Modelling allows examination of a range of factors, all operating at once. It investigates the strength of these factors and their interaction, and generates robust quantitative evidence. Weaknesses • A strong end-user focus is needed to avoid becoming too bogged down in technical issues. • Analysis may suffer from a lack of available data. • Modelling work often has to deal with numerous uncertainties surrounding data and assumptions. A pitfall to be avoided is to try and hide these weaknesses within coding in the model to try and make the results appear more robust. It is important to be transparent about all the data and assumptions, and to be aware of the degree of accuracy required by the results in order to reach a robust conclusion. References The Green Book, HMT. Appraisal and Evaluation in Central Government Derek Rowntree, Statistics Without Tears Sprent P, Statistics in Action Statistics for Economists, R.E.Beals Statistics for Economics, R E Davies and J N Foad Cambridge Econometrics - Modelling for Government Multi-Criteria Analysis: A Manual (DTLR) Strategy Survival Guide – Strategy Skills Page 133
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Strategy Strategy Survival Survival
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Building an Evidence Base 113 Data
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A Framework for Strategic Direction
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Identifying key stakeholders and th
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Compelling vision for action - the
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Designing an implementation plan In
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Creating Public Value http://www.nu
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Strategy Unit, Admiralty Arch, The
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Strategy Survival Guide

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