One of the needless failings of the project and portfolio management (PPM) process is how easily we get stuck with bad decisions, as a result of flawed analysis.
It’s easy to make mistakes in this field if you don’t get some proper financial advice and cost forecasting and estimating right.
Take budgeting. There’s an important distinction to make when it comes to costing. There’s a difference between financial analysis and economic analysis. In other words: “Are you looking for the affordability of a project or product or are you looking at what is the best value for money, the economics of it?” To be blunt about it: what’s the best bang for the buck?
The economic analysis is there to provide us with guidance in terms of which option is preferable, which is the best value for money, but it’s no good just taking the best option without being able to afford it. You must also ensure that over the foreseen financial years of the project it is actually affordable to do the project. It’s a combination of the two and it does depend on what the question is when project staff come to see you.
Avoid mistakes with estimates
People often think of hardware and the tangible things in a project, things that they can hold, touch and feel, but a lot of people don’t consider software estimating, an area which people are not often familiar with. Estimating the cost of software is equally important and increasingly it’s a big part of projects these days.
Also, there’s operating and support costs, and logistics costs. Again, people tend to focus on the acquisition side. What it is they are trying to buy? Without considering the true life cost of the project. What will it actually cost to maintain it (e.g. the spares, the repairs and so forth)?
It’s also important to pay attention to the process. Often there are frequently weaknesses in terms of processes that people apply. Obviously, a lot of people see estimating as just a case of adding items up. If you can apply a spreadsheet to a list of the costs at the map, then they think they can do estimating.
Getting the cost and schedule numbers right
But if you’re going to do an estimate that is credible and justified then really what you need to do is apply various techniques. Those techniques classically are parametric analogies and analytical techniques. So, if you use three or more different types of estimating methodology, then you can get that a lot more confidence in the numbers that you’re generating.
A lot of people look at the accuracy of the estimate and ask a question: “Is this within plus or minus 5%, plus or minus 10%? What’s the tolerance band around it?” But you can have a tolerance of plus or minus 10% on an estimate only to find that that point estimate is completely in the wrong place. I think looking at various methodologies gives you confidence, it gives you that added feeling of assurance that the estimate has some credibility about it.
Avoiding common pitfalls in cost forecasting
Estimating is classically considered a bill of materials, a detailed estimate that you have and you can see the design as established and known. Forecasting tends to be looking into the future, trying to predict what the future budget needs to be. When are we doing cost forecasting, we typically look at two or three decades and try to establish what might the replacement be for the product or service that we are using today. A lot of that is about technology, trend analysis and looking at historical trends by learning from a normalized database of historical information, doing regression analysis and statistics to try to establish what might the cost be of the service or the product at some point in the future.
Forecasting is always a particularly tricky area. Naturally, you would expect a greater tolerance of error around cost forecasting. Cost estimating is more near-term. The key is to have a single view of both your current and historical PPM data at your fingertips. If you don’t have good data, you won’t be able to make good decisions. It’ll just be a shot in the dark.
Cora PPM can integrate financial data, helping users to improve financial forecasting accuracy and reduce financial report cycle times. To find out more why not request a personalized demonstration here.