Sick of the blame culture? How to Improve productivity in your IT departmentby David Walton (No Comments )
Too often ‘blame IT’ is the default reaction when projects go wrong, but there are ways to protect yourself against these often bogus claims. With decades of experience working on ‘Big 4’ delivery programmes, our in-house expert, David Walton, shares his experience here to help you make sure that the next time it happens you can prove them wrong.
IT departments are often the whipping boy for all other departments in an organization; often unfairly. It’s always easy to blame IT for failings.
The usual complaint is that everything takes too long and costs too much. Despite the unfairness of many of these complaints, it’s incumbent on IT departments to look at ways at being more productive. The problem is that IT only looks for the next silver bullet to improve productivity.
It is valid though for IT to look at technology to improve productivity but there are other ways, which I will describe later, that should be used to identify areas for improved productivity.
In terms of technology, the move that many organisations are making to cloud based solutions should deliver productivity gains. But, there are lots of other areas that IT can look at in order to improve productivity. The problem is that without reliable data it is hard to know where to look for those valuable gains.
Leverage data to enable productivity gains
When I was working in a big 4 Consultancy, we often were brought in to identify areas of IT where productivity could be improved. However, we needed data to be able to do this. As we were not part of the organization, we did not even have the advantage of a ‘gut-feel’ that would lead us to areas where productivity could be improved.
To provide the data on where focus should be applied to enable productivity gains, you need to have a timesheet system in place that provides you with the data you need.
Some organisations, that I have worked at, have a loathing for timesheets and have a culture that almost prevents them being implemented.
Timesheet systems, which are easy to use and are set up correctly, can provide excellent data sets which you can then analyse to see if productivity improvements can be realized.
I know it sounds very basic and not as exciting as Big Data or Agile or AI, but timesheets can provide a goldmine of information that can point to areas where waste or poor productivity is evident.
For example, you may find that too much of the IT department’s time is spent in supporting applications rather than more value-added activities. Analysing the data further may highlight particular system(s) that require high levels of support.
Identifying the root cause of the problem
If you then did a root cause analysis, the problem may be a lack of training or there may be a high level of bugs in the system. Whatever the cause, there may be ways of addressing the high-levels of support so that IT spends less time on support and more time on value adding activities.
I understand that it’s not as exciting a big data or AI, but it could lead to a big increase in productivity.
Timesheet data may also uncover situations where staff members, who should be actively involved in development projects, are instead spending time on other non-value adding activities. This again could be because there is a problem with project planning and people are hanging around waiting for a project to start when they could be engaged on other more productive activities.
These are two simple albeit unglamorous examples of how analysing timesheet data could highlight areas of inefficiencies which can then be addressed resulting in improved productivity.
Of course, the analysis depends on the data in the timesheet system. It needs to be of sufficient quality and at the right level of granularity. Some thinking therefore needs to happen before implementing a timesheet system so that the data is at the right level and can be analysed properly. The other advantage of this type of analysis is that implementing a timesheet system is not a costly exercise and the results may be quite surprising.
Like all good measurement activities the analysis of timesheet data should not be a one-off exercise but an exercise that is conducted at regular intervals; the goal being continued productivity improvements.