Strategic Problems: Modeling the Market Space
A new dimension for the use of multi-criteria decision analysis
By Santiago Castro
Multi-criteria decision analysis (MCDA) has proven to be a sound technique to solve complex problems where numerous available options must be evaluated against multiple criteria. This includes, for example, selecting a best project against many others or choosing the most efficient portfolio of investments. Apart from those traditional applications, more recent uses of MCDA have been developed to solve strategic problems, incorporating MCDA in the evaluation phase of scenario planning for example. These strategic uses of MCDA often consist of four basic steps: identifying the decision-maker’s strategic objectives; evaluating the performance of each strategy-scenario on each objective; weighting the strategic objectives and; obtaining the overall performance of each strategy scenario.
Advances in software have now expanded the basis and breadth of use of MCDA. More complex problems can now be modeled directly with model results being available in a few seconds. All this has opened a new dimension for the use of MCDA in the strategy arena other than the just mentioned scenario planning application.
When combined with advanced software technologies, MCDA becomes a very powerful methodology to represent the strategic situation of a company in all key market factors. Using various weight sets, it is now possible to capture at the same time the different points of views from the Board of Directors and Executive Team and/or simulate numerous value sets of various customer groups. Furthermore, as computers allow interacting with complex models and as the levels given to the different variables can be changed, an infinite potential for scenario simulation is now available. Enhanced scenario simulation capabilities facilitate testing hypothesis, building common understanding, learning and adapting to change as creativity is stimulated. In that sense the new scenario approach developed here is more about creative thinking rather than purely normative assessment of options or future-oriented forecasting of scenario planning.
Cogentus, a management consulting company specialized in applying MCDA techniques to business problems, has been engaged by different clients to develop their business strategy. The focus of attention is placed on choosing among different possible strategic moves; in other words, the set of managerial actions and decisions that could enhance business offerings and opening and capturing new market spaces.
In this respect, MCDA offers a solid methodology to model and facilitate understanding the company’s set of managerial actions and decision implications. In practice, a managerial decision implies an irrevocable allocation of resources given different options. Imagine that each option is a company activity area or industry factor. In this sense, a managerial decision to allocate more resources in one particular activity or factor will have an impact on its competitive performance in that particular field. The implications could be assessed relative to the position of other competitors in the same industry factor. In more general strategic terms, the impact of the same allocation of resources can also be measured in terms of the company’s objectives, mission and vision. In other words, multiple-criteria can be used to model the market space and analyze the company’s most efficient actions and product portfolio .
As shown in Figure 1, using MCDA software it is possible to display in a two-dimension graph a particular industry’s competitive performance. The horizontal dimension identifies the range of factors the industry competes on and decides to invest in. The vertical dimension represents its level of investment and consequently the offering level that buyers receive across all key competing factors. Different consumer values are simulated by the different size of the vertical lines. Thus, the same score in two differently weighted factors does not represent the same opportunity for the company. The mapping of competitors’ relative positions identifies the available market space (illustrated with the red circled area) where any of the displayed companies could decide to move and become the leader in that particular offering.
Figure 1: General graphical representation of competitive relative positions in the market space.
More generally this type of display constitutes an interesting tool to stimulate analysis about the implications of a strategic move decision. It offers a comparative approach of both the diagnosis of the current state of play in a particular market space and a possible company-wants-to-be scenario depending on the relative performance impact of a decision (see Figure 2).
This approach allows companies to recognize where the competition is currently investing, what customers are receiving from the existing offerings on the market and thereby where a particular company could be, following a possible strategic move.
Based on our experience, Figure 2 illustrates what companies tend to do first: increase the level of criteria performance in order to gain a competitive advantage. The final result of this type of decision is a general incremental change. However, the decision to only improve key industrial factors requires additional investment and expenses without a corresponding reduction of costs elsewhere to compensate. Such a non-compensatory attitude tends to produce an inefficient resource allocation policy. At the same time when the benchmark is competition, the result tends to be competitive imitation resulting from a lack of strategy innovation. Consequently, companies’ strategic profiles tend to converge, resulting in a lack of product differentiation as illustrated in Figure 1.
On the other hand, considering a totally divergent strategic profile, as well as considering possible trade-offs (i.e. reducing or even eliminating the investment in some market factors), would liberate resources that could be used to support a better strategic move such as strategic differentiation. In sum, if the focus is less on fighting for competitive advantage and more on strategic innovation, the result is that product differentiation can be achieved with an overall investment that can stay constant (see Figure 3). This is a fundamental step forward, if one agrees that creating a new type of product offering and finding a differentiated niche where no competition exists is the key for success.
Instead of diffusing its efforts across all factors of competition, the aim is for the company to focus only on some key factors, even though trade-offs between multiple factors are often hard to make. Once again MCDA techniques offer a sound framework to implement such fundamental trade-off between multiple – and differently valued – industry key factors. Combining MCDA with the mappings described above can help. The necessary trade-offs will result from systematically assessing the business strategy in terms of resource allocation, measuring and always guaranteeing its efficiency.
Tool to Evaluate Strategic Consistency, Efficiency
The strategic move aims to add value to the business, but its implementation is done within given conditions and restrictions. Therefore, the given level of available resources will imply a strategy cost limitation. Acknowledging those limitations and fixing a target cost can help to orient the strategic analysis, stripping out some costs.
Combining MCDA and resource allocation analysis to assess how efficient a particular strategic profile is implies evaluating and confronting two fundamental criteria: the added value or benefits of the strategic move against its costs. In particular, the benefit-to-cost ratio allows putting these elements together and enables companies to evaluate how to maximize the total benefit given a target cost. Having defined benefit criteria for each strategic move ( ? , ? or ? ), benefit scores can then be given. Subsequently, each score (let S ij represent the score associated with the consequence of a strategic move i on criterion j) must be multiplied by the relative value or weight factor (let W j represent the weight factor associated to criterion j); finally all value weighted benefit scores ( W j*Sij) are to be added together and the total value adjusted benefit must be divided by the total cost of implementing the new business strategy. The benefit-to-cost ratio is expressed in the following additive aggregation equation:
Benefit-to-Cost Ratio =
(?j Wj*Sij) / Total Cost
All values in this equation can be inputted in MCDA software, leaving the computer to make the calculations and produce the results.
One important output that the computer can produce following this methodology is shown in Figure 4. The horizontal axis displays the total weighted costs and the vertical axis shows the total weighted benefits. As illustrated, an efficient frontier – represented by the top left borderline of the football shape within the graph – displays all the possible points that maximize the benefit to the company. The red point represents the current state of the strategic profile. This means that either by reducing or eliminating factors in the general strategy, the company could generate a more efficient strategic profile and move in the direction of the left (or west) oriented arrow towards the efficient frontier.
Similarly, by focusing on the particular factors that offer more benefit to the company and deciding to raise their level or create them if not yet offered by the company, the resulting strategic profile will move in the direction of the vertical oriented arrow (or north) towards the efficient frontier. Finally the figure shows a comparison of two graphs where a vertical line is fixed in a different total cost level. This vertical line represents the target cost of the company. As explained above, given the resource restrictions or their availability, the managers of the company can fix a target cost.
Depending on where the target cost is fixed, and whether or not it is possible to invest additional resources, different possible strategic moves emerge (different possible arrows to follow in the graphs. It is important to say here that with a simple click the software can display a precise measure of the strategic profile in terms of its total benefit score, its total cost (how much economy is achieved and/or investment is needed) to implement an overall strategic movement. Based on those results, the decision to give priority to some strategic moves instead of others seems very straightforward.
To conclude, combining MCDA with appropriate software tools can offer considerable help to understand, model and choose between possible strategic choices in a market space. However, it is only a decision aid; the final strategic decision will depend on various factors. For example, depending on resource constrains, as illustrated with the target cost (vertical line) in Figure 4, the available choices will be limited. Also, once the competitors’ strategic profiles are added into the graph, resulting relative positions will give additional insights about some better and some worse orientations. In this respect creativity has an important role in taking the rest of the decision, because creativity is needed to invent a new offer. A fundamental part of the strategic planning process concerns in particular that aspect of generation and formulation of alternative strategic options. Exploring options before deciding is a great value.
Before deciding a “where do we want to be” strategy, it is essential to imagine, test and compare many “where we could be” alternatives. Before launching the expedition into the unknown, it is critical to have a rational vision. Once again, as strategic situations are represented and tested, combining MCDA with advanced software technologies offer powerful means to stimulate creative thoughts. Confidence in the final decision is strengthened by every additional option considered.
Santiago Castro is a senior analyst with Cogentus Consulting Limited (www.cogentus.co.uk/) in the U.K.
1. The work presented here is the result of combining ideas taken from the textbook “Blue Ocean Strategy” (Kim and Mauborgne, 2005) with MCDA techniques and applying such theoretical approach to practical cases.