Part 1 Do your metrics miss the wood for the trees? This part shows why smartmetrics are needed. All firms use metrics but most are poorly designed. How the wrong metrics distort performance and why individual managers will not make the best decisions for the firm without smartmetrics to guide them. 1 Doing the right thing This chapter illustrates the problems of non-scientific strategy decisions: while the direction of strategy is right, the details are wrong How strategy gets set - case scenarios of typical strategy setting processes How poor measures lead to internal fights and lack of alignment eg data consistency vs usable reports, sales revenue vs profitability How strategy leads to the right idea but the wrong results eg NHS, CEO bonuses, e-business, Enron and derivatives. 2 Why is setting strategy difficult? This chapter explores the difficulty of getting the right strategic decisions: pinpointing what causes success. The firm as a complex system. The causes of complexity: autonomous agents (people and their behaviour) Issues in complex systems: local optima (empire building); sensitivity to small changes (the devil is in the detail) The problem of how to know which actions were responsible for success: the credit assignment problem How these issues appear in practice. Case M&S 3 Pointing managers in the right direction This chapter shows why managers need a framework to direct their efforts: their unaided intuition is not enough to figure out value drivers and measures. Why smart people don't make smart decisions Managerial decision biases and common errors: biases toward the simple, the recent and the local. Why there is no 'invisible hand' of the market to guide them. Managers acting in their own self-interest will not produce optimal outcomes for the firm. Their different biases and interests lead to a lack of alignment and cooperation. How firms attempt to impose alignment: process, culture, KPIs KPIs as the link between value drivers and alignment The problem of perverse behaviour under KPIs: meeting a stated goal while destroying unstated goals How alignment affects performance: examples of poor KPI alignment vs examples of good KPI alignment 4 Applying rocket science This chapter synthesises basic principles of analysis and measures from techniques used in different areas of management A survey of techniques from various areas of management specialisms, including finance, marketing, operations research, business modelling Synthesis of the basic principles to address the credit assignment problem: variation, grouping, preferences, linkage and dynamics. Finding drivers in the depths of the organization. The need to take a whole organization drivers approach. Research findings on success factors for value creation programmes. Issues in measuring drivers: problems of which financial measures (eg EVA vs TSR) at firm level, measuring both hard and soft factors, problems of group rewards, short vs long term measures, setting KPIs for interacting groups of drivers non-measurable or rewardable behaviours - why they may be needed and how to get them indirectly via measures Setting KPIs that promote alignment and joined-up thinking: whether the KPI set supports or destroys them. Dynamic analysis from different managerial and customer viewpoints. Part 2 Constructing Smartmetrics for your business: Killer Analyses This part shows how to construct the specific smartmetrics that are right for your business. How smartmetrics can have a major impact on performance on all aspects of performance including examples from M&A, marketing, finance, HR and operations. 5 Killer Analyses: setting the right KPIs Paying for performa
