Data Capture Projects: Asking the Right Questions

Large complex international ICT projects are often initiated following data capture projects or commence with an initial data capture phase to validate in-going project assumptions and clarify or refine project objectives.

When some companies execute an international ICT project they are able to follow their company’s enterprise-wide standards and practices. They will most probably have a framework for the initial data capture phase of the project, the topic of this article.

These companies will most probably have in place a number of quality standards (e.g. ISO9000) and infrastructure processes (e.g. Capability Maturity Model Integration (CMMI)). If this is the case for your company you may wish to skip this article.

Unfortunately many global or regional CIOs have a practical difficulty as they have to deal with different standards and processes put in place by each of their business units or countries.

In addition, most enterprise-wide project teams will have local participants from across their company with wildly different experiences. This may create additional complexity where they have little in common if there is no strongly binding company culture or common processes.

In short, the global or regional CIO almost invariably lives with a complex array of standards, processes and personnel, and may benefit from Information Framing as a simple ‘first principles’ approach when planning enterprise-wide projects.

 

Information Framing for Data Capture Projects

For large continuous improvement, and even transformational change projects, large companies often start with a new project initiative by trying to understand what they have today. Sometimes a detailed baselining project is undertaken as described previously (here).

To provide the subsequent project design phase with a solid foundation, it is common early in the project to challenge and validate the ingoing project assumptions at an appropriate level of granularity.

Perhaps the most ideal approach would be to use semantics, that is to develop an appropriate set of assumptions for each objective then ‘flip’ each assumption to form a hypothesis to be tested, then validating (or invalidating) the hypothesis by collecting and analyzing the appropriate data. The validated assumptions form the foundation for the project and the invalidated assumptions provide new knowledge for management to assimilate. In practice, operations staff do not execute the assumption development or flipping process easily, probably as the level of semantics required is not a regular skill needed for their daily job.

Information Framing is a more practical approach to improve project assumptions and objectives for data capture projects, typically more complex ICT projects. With Information Framing, business questions are used to validate the ingoing project assumptions and project objectives. Operations staff develop questions that link assumptions or sub-objectives to collectable data.

Key advantages of Information Framing are:

  • improved project transparency through project objective mapping to the data to be collected
  • reduced project acceptance and political issues by reducing the number of “wrong” questions being asked
  • reduced level of data collection, as only the most relevant data is collected
  • reduced complexity in the data analysis phase – as the use of the data is pre-mapped’, reducing the effort and reliance on the discovery of data patterns
  • reduced likelihood of project delays and resource cost blowouts due to better planned data collection and analysis phases.

The main disadvantages of Information Framing are:

  • reduced level of data collection may require a later data collection exercise – although containing the level of data collection is usually an advantage
  • the weakness of Information Framing is that the process of framing questions introduces bias (Levin et.al. 1998), however awareness of the framing can reduce the number of “wrong” questions being asked
  • actual data discovered may only provide approximate or indicative information (not binary validation or invalidation) of the initial project assumption.

 

WARNING: As the disadvantages of Information Framing above suggest,  it is most handy, and may be limited to, the initial data capture design phase of a project where the environment is very complex. Like all such tools, before electing to use this tool you must assess your environment and specific circumstances to ensure it is a suitable approach for your situation.

 

This simple Information Framing approach was adapted from the idea of answering questions for assessing maintenance actions (Moubray, 1997, ISBN 0 7506 3358 1), and the typographical work of Levin and others.

This approach was used during my employment at BHP Pty Ltd to help steel plant maintenance engineers capture the baseline and current equipment condition as part of the annual planned maintenance cycles. I have since applied the same simple approach to ICT baseline and due diligence projects during my employment at Deloitte and BT.

Information Framing is a technique covered further in an upcoming My Kitbag Guide. Please use ‘Contact Us’ to get in touch if interested.

What are your experiences in gathering project information in the initial phases of a project?