Whether a decision’s outcome is to hire a new employee or introduce a new product or service, a business's decision-making process is rarely a simple one. This is particularly true if the consequences of your decision are significant.
A decision-making process can be made to be a more straightforward and logical one if in the process you collect worthwhile data, use helpful tools and select the appropriate accuracy requirements. But even this process can fall short unless the decision maker employs effective communication skills along the way.
Clearly Specify Relevant Data
Collecting reams of data is not a worthwhile endeavor unless the data is helpful in assessing the likely outcome of a decision. If the decision maker relies on others to supply data that can help him identify and weigh different options, it’s essential that the decision maker effectively communicate his needs so the data-collection efforts of others are limited. For example, if a decision maker requests strategy data even though he’s only interested in business-unit strategy data, those providing the data might provide information related to a corporate functional strategy rather than a business-unit strategy, so the decision-maker could end up basing a decision on the wrong set of data.
Define Specific Decision-Support Requirements
To obtain data that helps you reach a logical decision, you might work with a technical staff member to create a custom report based on data that resides in multiple systems. For example, you might need the programmer to export data from a production system, summarize it and reformat it for import to a desktop application, such as a spreadsheet application. Unless you communicate your requirements effectively, the programmer might export information you don’t need, summarize it in the wrong manner or reformat it for a different application than you intended.
State Particular Data Accuracy Requirements
During a decision-making process, it’s important to focus on data with a particular degree of accuracy and no more so that after you decide your data parameters, if necessary, you can request worthwhile information from others. Unless you can clearly communicate the degree of data accuracy you require, others might supply you with data at a more detailed level than you need. For example, rather than receive the actual cost of a car engine, you might receive the cost of each part needed to construct the engine. As a result, you’ll need to put forth the effort necessary to deal with the data in its existing format or request different data.