Data map

One of the potential problems in the Confirm stage is data overload and misalignment. There are numerous ways in which to measure how the client system has changed, and there is every likelihood that the confirmation team will consist of people from a range of areas. The use of such a diverse team of people can lead to political in-fighting, data discrepancy and inefficient resource allocation.

Imagine the case of a call centre computer system upgrade. The IT team might be focused on measuring system performance by monitoring the transaction speed across the network. The client will want to conform that the new system has increased the call-handling rate. You might want to ensure that the people have received effective training in the new system. Finally, the finance director has decided to use the audit team to guarantee that financial integrity has been maintained. Unless all these activity streams are managed cohesively, then it will be difficult to agree if the change has fulfilled its objectives. One solution is to trace the various measurement activities on to a common map, one that indicates the type of measurement, who owns the activity and why it is being taken.

When building the data map, it is important to ensure that people are clear why the data is being gathered. Usually it is for one of these five reasons:

• Augment: This is used to create the initial data set or build or expand upon the level of knowledge about a particular area. So if the data indicates that certain issues within the engagement might have been less than effective, the choice is to re-visit to get more data on which to take a decision.

• Broaden: It can help to gather broader-based data, possibly about other parts of the organization, benchmarking against other businesses or wider academic views on a particular subject.

• Confirm: To verify that a particular data set is giving accurate information, possibly by triangulation or by a repeat process in the same area.

• Depth: The goal is to develop a more detailed picture about a topic. This might be where you mine deeper into a financial report, gather more data on people's views about a subject or run a focus group with customers to verify that a product enhancement is adding value.

• External verification: You can use external agents to verify that bias or corruption has not crept into the change. They are able to verify that the process and the content of the findings are accurate and reflect the true outcomes. The term "external" might mean independent consultants or agency groups or simply a separate department within the company that hasn't been affected by the transition.

Take as an example a customer service programme implemented in a national fast food chain (Fig. 10.5). In building the data map, the steps are:

• Augment the limited data by running a postal survey. The aim is to build the first data set to ensure that all people have attended the programme and to gather their initial thoughts.

• Gather information in more depth about some of the issues raised in the feedback through a series of random interviews.

• To check this data to confirm the outcomes with a number of focus groups and a limited telephone survey.

• The results would then be augmented by specific interviews.

• All of this data are used to build a customer survey questionnaire and so broaden the information by undertaking a postal survey with a selected range of customers that have used the service since the programme has been introduced.

• Finally, the results from the confirmation process are externally verified by asking the company's internal audit branch to confirm that the change has been successful.

Unless the data are sourced with care and control, there is a chance that the confirmation will be superficial. The data map helps to ensure that alignment is maintained and also helps clients and consumers to understand how confirmation of the change will be managed.