Your digital transformation programme was rolling along quite nicely, thank you. But then, the project hits an iceberg. No one knows quite how it’s going to pan out, but you look to your project management team because, actually, you do want to know how it’s going to pan out. You want to know when the problem will be solved and – most of all – how it will affect the end date and budget.
In a nutshell, we need to analyse the information we have available (about the programme’s past) and use that to predict what will happen in the future – come up with a bunch of scenarios that will help the business to make some informed decisions. So how do you use your crystal ball?
You start with amalgamating the data – we call this stage the ‘engine room’ – using different tools and processes to extract the data and assure its quality and consistency. You have to validate each information source, finding out what it is, where it’s from and why you need it. Next step is an information map showing the flow of the information, processes and tools that will be used to gather information. The information needs to be ‘assured’ – checked for quality and consistency.
Statistical analysis is integral and how well it is used is as critical as the quality of the data you run through it. Three different types are common. The first is heuristic analysis – using subject matter experts to make educated assumptions about trends and anomalies in the data. The second – content based quantitative – is taking large volumes of data and applying techniques, such as quantitative risk analysis, to present future scenarios and the probability of their occurrence. We need these to help us understand the risk to future targets (e.g. timelines and cost), how big the risk is in scale and probability and the decisions that need to be made to decrease the likelihood of the risk. Finally, content-free behavioural analysis scores the accuracy of previous predictions of the change programme, giving us a level of confidence on future estimates, such as resource.
It’s vital to present the data in a way people can understand – and in project management, there are many ways of reporting that are way too complex. The 3Ts are a useful mantra – essentially, all reports should be able to track (contain historical data that allows you to track milestones completed, resource used etc), target (contain the goals of the project) and trends (best estimates of what is likely to happen). This information should aid decision making – so if the ‘trend’ is someway off the ‘target,’ decisions can be made to bring these closer into alignment.
Of course, this is only the briefest snapshot of what you can do to try and predict the future when your transformation programme hits a brick wall. But no one can predict the future accurately – there will always be variables that crop up that aren’t within your control. Prediction is a combination of art and science and like all crafts, practice makes you if not perfect, then much better at it.