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The 7-Step Improvement Process

CSI approach | Value to business | Justification | Benefits | Interfaces to other service lifecycle practices | CSI and organizational change | Role definitions | Service Level Management | The Deming Cycle | Baselines |


Читайте также:
  1. A1 Innovation, correction and improvement
  2. Continual Service Improvement fundamentals
  3. Deming Cycle used for improving services and service management processes
  4. Integration with the rest of the lifecycle stages and service management processes
  5. Process changes
  6. Process Explorer
  7. Process flows and RACI

Fundamental to CSI is the concept of measurement. CSI uses the 7-Step Improvement Process shown in Figure 3.4.

Figure 3.4 The 7-Step Improvement Process

Which steps support CSI?

It is obvious that all the activities of the improvement process will assist CSI in some way. It is relatively simple to identify what takes places but the difficulty lies in understanding exactly how this will happen. The improvement process spans not only the management organization but the entire service lifecycle. This is a cornerstone of CSI.

  1. Define what you should measure

At the onset of the service lifecycle, Service Strategy and Service Design should have identified this information. CSI can then start its cycle all over again at ‘Where are we now?’ This identifies the ideal situation for both the Business and IT.

  1. Define what you can measure

This activity related to the CSI activities of ‘Where do we want to be?’ By identifying the new service level requirement s of the business, the IT capabilities (identified through Service Design and implemented via Service Transition) and the available budget s, CSI can conduct a gap analysis to identify the opportunities for improvement as well as answering the question ‘How do we get there?’

  1. Gathering the data

In order to properly answer the ‘Did we get there?’ question, data must first be gathered (usually through Service Operations). Data is gathered based on goals and objectives identified. At this point the data is raw and no conclusions are drawn.

  1. Processing the data

Here the data is processed in alignment with the CSFs and KPIs specified. This means that timeframes are coordinated, unaligned data is rationalized and made consistent, and gaps in the data are identified. The simple goal of this step is to process data from multiple disparate sources into an ‘apples to apples’ comparison. Once we have rationalized the data we can then begin analysis.

  1. Analysing the data

Here the data becomes information as it is analysed to identify service gaps, trends and the impact on business. It is the analysing step that is most often overlooked or forgotten in the rush to present data to management..

  1. Presenting and using the information

Here the answer to ‘Did we get there?’ is formatted and communicated in whatever way necessary to present to the various stakeholder s an accurate picture of the results of the improvement efforts. Knowledge is presented to the business in a form and manner that reflects their needs and assists them in determining the next steps.

  1. Implementing corrective action

The knowledge gained is used to optimize, improve and correct service s. Managers identify issues and present solutions. The corrective actions that need to be taken to improve the service are communicated and explained to the organization. Following this step the organization establishes a new baseline and the cycle begins anew.

While these seven steps of measurement appear to form a circular set of activities, in fact, they constitute a knowledge spiral (see Figure 3.5). In actual practice, knowledge gathered and wisdom derived from that knowledge at one level of the organization becomes a data input to the next.

Figure 3.5 Knowledge spiral – a gathering activity

People often believe data, information, knowledge and wisdom to be synonymous or at least broadly similar in meaning. This view is incorrect. There is a significant difference between each of the four items.

Data is quantitative. Data is defined as numbers, characters, images or other outputs from devices to convert physical quantities into symbols, in a very broad sense. Essentially it can be defined as a collection of facts, whereas information is the result of processing and organizing data in a way that adds to the knowledge of the person receiving it. Raw data is a relative term; data processing commonly occurs by stages, and the ‘processed data’ from one stage may be considered the ‘raw data’ of the next. Example: The Service Desk and Incident Management collect data on an average of 12,000 incident tickets per month.

Information is defined as a message received and understood. In terms of data, it can be defined as a collection of facts from which conclusions may be drawn. Information is the result of processing and organizing data in a way that adds to the knowledge of the person receiving it. Data can also be qualitative such as comments in a customer satisfaction survey.

By processing data into information it is possible to know the breakdown of which customers are using the Service Desk and the specific issues that are incidents or Service Request s. Example: Further processing of the data into information shows that 32% of all contacts to the Service Desk are ‘How to’ questions, and that 18% of all contacts are true incidents with the organization’s e-mail system.

Knowledge can be defined as information combined with experience, context, interpretation and reflection. Example: based on the data and information, and an understanding of who uses the service, and their reasons for using the service, the impact to the business can be determined.

Wisdom is defined as the ability to make correct judgements and decisions. It consists of making the best use of available knowledge. Example: knowledge about the customer impact of incidents can lead to identifying improvement opportunities such as training programme s or initiating a SIP for improving the e-mail service.


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