Strategy illustration Strategy theory

Decision making

A business organisation is a decision-making unit that sets out to produce a product in the form of goods or services. Key decisions need to be made about an organisations plant, its products, and its people.

  • plant - e.g. whether to invest in a new factory, or in updating present facilities
  • products - e.g. whether to introduce new lines
  • people - e.g through investment in training and development.

Most classifications of types of decisions are based upon the predictability of decisions. For example, Herbert Simon (The New Science of Management Decision, 1960) made a distinction between programmed and non-programmed decisions.

Programmed decisions are straightforward, repetitive and routine, so that they can be dealt with by a formal patterns, e.g. the re-ordering of stock by a company.

Non-programmed decisions are novel, unstructured and consequential. There is no cut-and-dried method for handling situations which have not arisen before.

Typically, there are three levels of decision-making within the organisation:

1. Short-term operating control decisions. These have to be made frequently involving short-term, predictable operations.

2. Periodic control decisions. These are made less frequently and are concerned with monitoring how effectively an organisation is managing its resources. For example, this might include the review of pricing strategies for certain products, reviewing problems occurring in an on-going company budget, or the re-appraisal of the way the sales force is being used. Such decisions are concerned with checking for and rectifying problems concerned with meeting company objectives.

3. Strategic decisions. These are major decisions about overall strategy. They will often require a considerable use of judgment by the person or group responsible for making the decisions. This is because although such decisions will require a considerable amount of analysis, important pieces of information will frequently be missing and so risk will be involved. Such decisions might involve the development of a new product, investment in new plant, or the development of new marketing strategy.

Decision Trees

Decision trees are so named because of the way in which they separate out into branches (outcomes) from an original stem (a decision). Decision trees are a technique for tracing through all the known outcomes of a particular decision in order to draw out the possible consequences.

In a decision tree, points at which decisions are made are represented by squares (decision forks), and points where chance/probability comes into play are represented by circles.

For example, a property development company may be faced with the decision of whether to sell one of its properties now, or whether to wait for a year in the hope the property market improves. If it sells the property now it knows it will receive £250,000.

However, if it sells in one year there are two possibilities:

1. There is a slump in the property market, so that the property can only be sold for £200,000. There is a nine out of ten chance that this will happen.

2. There is a boom in the property market, so that the property can be sold for £800,000. There is a one out of ten chance that this will happen.

We can use decision tree analysis to identify the 'best' course of action.

  • Sell now - result = £250,000.
  • Sell in a year:

£200,000 X 9/10 £800,000 x 1/10 = £260,000

You can see that the preferred option is to sell in a years time, because the outcome is higher £260,000 than to sell now £250,000.

The mathematics for selling in one years' time is easy. We multiply the expected outcome by the probability of that outcome happening. Although there is only a one in ten chance of a property boom it is worth taking the risk.

However, it is important to remember that some decision makers are more prepared to take a risk than others. In the example given many decision makers will take the cautious line and with the 9 out of chance of the property slump, decide to sell now.

Probability: Likelihood of an event occurring, measured by the ratio of the cases to the total number of cases possible.

Supporting Documents

These downloads will help to put strategy theory into context using real world examples from real businesses.

Innovation in infant nutrition
Cow & Gate logo

Find out how Cow & Gate used strategy theory to prosper in the food & drink industry by downloading our premium case study.

Using the marketing mix to drive change
Parcelforce Worldwide logo

Discover how Parcelforce Worldwide applied strategy theory to prosper in the logistics industry by downloading our premium case study.

Using new product development to grow a brand
Kellogg's logo

Discover how Kellogg's applied strategy theory to thrive in the manufacturing industry by downloading our premium case study.

Using sports marketing to engage with consumers
Kia Motors logo

Find out how Kia Motors used strategy theory to thrive in the automotive industry by downloading our premium case study.

Entering a new market with a new product
Experian logo

Discover how Experian used strategy theory to prosper in the financial services industry by downloading our premium case study.