Strategy Dynamics - A Possible Dynamic Model of Strategy and Performance

A Possible Dynamic Model of Strategy and Performance

To develop a dynamic model of strategy and performance requires components that explain how factors change over time. Most of the relationships on which business analysis are based describe relationships that are static and stable over time. For example, “profits = revenue minus costs”, or “market share = our sales divided by total market size” are relationships that are true. Static strategy tools seek to solve the strategy problem by extending this set of stable relationships, e.g. “profitability = some complex function of product development capability”. Since a company’s sales clearly change over time, there must be something further back up the causal chain that makes this happen. One such item is ‘customers’ – if the firm has more customers now than last month, then (everything else being equal), it will have more sales and profits.

The number of ‘Customers’ at any time, however, cannot be calculated from anything else. It is one example of a factor with a unique characteristic, known as an ‘asset-stock’. This critical feature is that it accumulates over time, so “customers today = customers yesterday +/- customers won and lost”. This is not a theory or statistical observation, but is axiomatic of the way the world works. Other examples include cash (changed by cash-in and cash-out-flows), staff (changed by hiring and attrition), capacity, product range and dealers. Many intangible factors behave in the same way, e.g. reputation and staff skills. Dierickx and Cool (1989) point out that this causes serious problems for explaining performance over time:

• Time compression diseconomies i.e. it takes time to accumulate resources.
• Asset Mass Efficiencies ‘the more you have, the faster you can get more’..
• Interconnectedness of Asset Stocks .. building one resource depends on other resources already in place.
• Asset erosion .. tangible and intangible assets alike deteriorate unless effort and expenditure are committed to maintaining them
• Causal ambiguity .. it can be hard to work out, even for the firm who owns a resource, why exactly it accumulates and depletes at the rate it does.

The consequences of these features is that relationships in a business system are highly non-linear. Statistical analysis will not, then, be able meaningfully to confirm any causal explanation for the number of customers at any moment in time. If that is true then statistical analysis also cannot say anything useful about any performance that depends on customers or on other accumulating asset-stocks – which is always the case.

Fortunately, a method known as system dynamics captures both the math of asset-stock accumulation (i.e. resource- and capability-building), and the interdependence between these components (Forrester, 1961; Sterman, 2000). The asset-stocks relevant to strategy performance are resources and capabilities . This makes it possible to connect back to the resource-based view, though with one modification. RBV asserts that any resource which is clearly identifiable, and can easily be acquired or built, cannot be a source of competitive advantage, so only resources or capabilities that are valuable, rare, hard to imitate or buy, and embedded in the organization can be relevant to explaining performance, for example reputation or product development capability. Yet day-to-day performance must reflect the simple, tangible resources such as customers, capacity and cash. VRIO resources may be important also, but it is not possible to trace a causal path from reputation or product development capability to performance outcomes without going via the tangible resources of customers and cash.

Warren (2002, 2007) brought together the specification of resources and capabilities with the math of system dynamics to assemble a framework for strategy dynamics and performance with the following elements:

• Performance, P, at time t is a function of the quantity of resources R₁ to R_n, discretionary management choices, M, and exogenous factors, E, at that time (Equation 1).

(1) P(t) = f{R₁(t), .. R_n(t), M(t), E(t)}

• The current quantity of each resource R_i at time t is its level at time t-1 plus or minus any resource-flows that have occurred between t-1 and t (Equation 2).

(2) R_i(t) = R_i (t-1) +/- R_i(t-1 .. t)

• The change in quantity of R_i between time t-1 and time t is a function of the quantity of resources R₁ to R_n at time t-1, including that of resource R_i itself, on management choices, M, and on exogenous factors E at that time (Equation 3).

(3) R_i(t-1 .. t) = f{R₁(t-1), .. R_n(t-1), M(t-1), E(t-1)}

This set of relationships gives rise to an ‘architecture’ that depicts, both graphically and mathematically, the core of how a business or other organization develops and performs over time. To this can be added other important extensions, including :

• the consequence of resources varying in one or more qualities or ‘attributes’
• the development of resources through stages
• rivalry for any resource that may be contested
• intangibe factors
• capabilities