Understanding the Basics of Strategy

A strategy is a general plan of action for achieving a business goal. This goal may be short-term, long-term, or overall. In uncertain times, a strategy is critical in achieving the business goal. It guides the decisions that must be made when executing a particular plan. Fortunately, the principles of strategy are not so complicated as they may sound. Read on to learn more about strategy and the different types of plans that you may need to adopt.

Strategies are based on a set of principles

Strategy is a hypothesis. A good strategy diagnoses a problem, proposes a guiding policy, and implements coherent actions to realize that policy. These four elements are the Kernel of Good Strategy, defined by Richard Rumelt. Rumelt, who is an engineer by training, later became a management consultant and advised the US Department of Defence. His work is based on a set of principles, including the need for transparency and accountability.

They are based on a set of activities

Each activity has two levels. Unit-level activities occur during the individual step of making or servicing a product. These include direct materials and labor, machine setup, and quality tests. Batch-level activities are the intermediate steps in a process, supporting the entire product line. Examples of these activities include engineering changes to an assembly line or a change to a product design. If a child activity fails, the parent activity gets a RESULT_CANCELED code.

They are based on trade-offs

These trade-offs are inevitable, but they are often elusive. Often, trade-offs become evident only in the long run, when we compare one alternative to another. Trade-offs can occur between two different attributes, reducing the space in which they can be optimized. A good example of trade-offs is steroid abuse, which can damage organs and lead to crippling debt.

They are based on data

Credit scoring models are statistical methods for predicting credit risk. The data used in these models is derived from empirical comparisons of groups of creditworthy and non-creditworthy applicants. These models are developed using established statistical principles and validated against the available data. The credit scoring models are constantly revalidated using appropriate statistical principles, so that they retain their predictive capacity. However, these scoring models must be used carefully, as they can be misinterpreted or even misinterpreted as the truth.