The 5 Best Practices for Intuitive Project Forecasting

The processes of forecasting, planning, executing and analysing projects are far more cyclical that you’d like to acknowledge. Think about it. To be able to forecast precisely, you will need accurate data history, and to be able to plan ahead, you need to know current realities well enough. This interdependence therefore must be the foundation for overall project forecasts that help allocate your precious resources, time and budgets to projects that are successful enough.

To help make project forecasting as successful as you’d like for it to be, here are effective practices to imbibe into your organization.

  1. Think long-term

Thinking long-term and planning long-term are two different things, as much we’d bucket them under the same category. With long-term planning that most organizations are too accustomed to do even in the day and age of agility, there is always the eventuality of stale plans that do not fit into the market fluidity you need to prepare for.

However, long-term thinking is the opposite end of the spectrum and focuses on ‘feasibility’ of an idea in an inflation-driven competitive market that is not likely to stay as true to your ‘critical path’ as you’d like for it to. Simply put, a feasibility study brings together technical, legal and financial aspects of the project under scanner and studies all of the various aspects to decide whether or not your project is worth the trouble. In addition to these aspects, feasibility also encompasses operational and schedule feasibility, thereby, aiding both decision-making as well as success of the project.

Thinking long-term qualifies the kind of projects you sign up for and as a result, lets you maximize the return you derive on investment.

  1. Automate and simplify scheduling

Enough has been said about the importance of simple processes and accurate data. Yet the uniformity of processes and the consistency of generated data are both largely elusive to a lot of project management outfits. As a result, the resource constraints that are factored in the beginning of a project and the ones that the critical path actually has to battle with during execution are significantly different. This creates a discrepancy between the projected value and earned value estimates. Ultimately, when the end product fails to deliver the value it was originally supposed to, this points to poor forecasting.

Alternatively, standardizing data generation norms for project resource scheduling will help make your base estimates, just as consistent too. That way, you know exactly how long project A took and you can have logical demand forecasts for projects that are similar in scale and function. In addition, the cycle of finding available resources within time and allocating them should be automated based on project demand and capacity, as well as the priority you associate with all those projects. Scheduling not only checkboxes an item off your list, but ensures that this item is delivered in the most efficient way possible which ties back to improved forecasting and resultant project success.

  1. Stay flexible with plans

Drawing back to point 1, planning must accommodate for the future as well as the current set of activities planned. This means, your project forecasting has to adopt a certain fluidity in the way that it distinguishes between demand and capacity. This fluidity can be bucketed under risk breakdown structure that is found as a part of the feasibility study or it can be a purely financial assessment that you consider as you study markets, inflation or a sudden influx of revenue.

Project forecasting must account for the velocity with which digital businesses operate today. Factors to study include shifting portfolio priorities, dynamic budgets and an evolving approach to resource allocation – one that factors in the contractor driven, hyper specialized gig economy dominating most industries. It also helps to have what-if analysis factored in so that you still can forecast the areas that get affected with the long-term decisions you take on seemingly ‘small-scale’ segments. After all, a project is nothing if it not a closely sequenced set of activities.

  1. Draw accurate reports in real-time

The natural progression from unified and accurate data collection is that of utilizing real-time reports. Real-time data is perhaps the only way to have some kind of grasp over your project’s realities given the complexity of businesses and the sheer volume of changes that occur. To go a step further, the nature of the real-time assessments you draw should tie-in financial, HR, operations, business development among other segments to give you a realistic as well as a holistic overview of your project status.

Data must evaluate hiring expenses and process budget on terms that validates the project’s business case and provides enough scope for the project to remain profitable even as payrolls face market changes. This will also need to access the time taken for project completion and then determine the kind of workforce alignment that you want to achieve. Such numbers cannot reflect days or week later. They all need to be generated in real-time to substantiate your forecasting and base decisions on more than ‘gut instinct’.

  1. Unify data for maximum impact

We’re currently surrounded by a sea of data. Data from the past, data to put future in perspective and then of course, the realities of on-going activities. However, the numbers themselves make little sense when they are on different realms. Unifying your history with your execution status as well as utilizing this heap for forecasting is a way to ensure clarity and success within the execution process.

In addition, it is necessary to unify data from across different departments and then utilize this data to verify your decisions, or weigh-in the ‘what-if scenario’ in case of changes to payroll costs, project performance or the program shifts in priorities. To clarify, this unification also helps you secure data given how having too many avenues to access valuable data is too a risky a bargain. Protecting data is, after all, your way of ensuring its safety for tomorrow’s forecasting decisions as well as respecting employee/ client privacy.

Project forecasting relies on data and agility significantly more than it did earlier. Your demands, in that case, rely on the systematic flow of information you create as well as the sophistication of tools that you are willing to invest in. Settling for free tools may not always be the optimal way out.

Article by: Aakash Gupta

2018-12-18T12:51:13+00:00October 15th, 2018|