Demand management begins with balancing the available resources against the volume of work. Organizations must first identify the projects that require resources, prioritize them and then match the skills with the resources. It involves scheduling, assigning and evaluating resources to ensure they are the best-suited for the task. To ensure that the promised value is delivered, it is crucial to regularly audit the process. This requires the ability to accurately forecast the labor and resources required for projects.
We have identified four areas that should be evaluated in resource forecasting. This will allow you to be ready for any output level. These steps include data, accountability and analysis. Let’s take a closer look at each.
Sales data, resource data, and more
Data is the foundation of demand management. Your data will show how many resources were used on previous projects. It will also help you determine the amount of resources and time you’ll need for a future project. You can use sales data to estimate the number of projects you should expect to complete so that you can plan for the resources.
Sometimes, your sales pipeline information may be incomplete or inaccurate, which can reduce confidence in the data. To get an accurate forecast, however, you don’t necessarily need to have perfect sales data. The myth of a “perfect sales forecast” should be discredited. Demand forecasting requires a lot of data. Approximately 80% of your data comes from a backlog and not future sales. This is work you have already done and not speculation. Future sales data is important, but it is not the most important piece of forecasting.
Data is often not in a usable format. This is one of the biggest problems with data. Sales teams may give future sales opportunities in dollar figures without specifying the time or resources required. It is important to determine WHO, WHAT, and WHEN the resource requirements should be defined.
An organization can define the data they need to be able to get useful and actionable information that will help them determine how much time and resources they will need for a given project.
Before gathering data, these mechanisms must be in place to define data collection. Project portfolio management software is crucial to organize data and distribute tasks.
Accountability for data
When we refer to accountability, we mean the people responsible for data ownership and management. If accountability is not clearly defined, it is easy to see the wrong people trying the data together, which can lead to inaccurate forecasts. Because they have the most client-facing insight, it is important that data collection be held accountable to the demand facing organizations such as your sales team.
Not only should the data be compiled by the right person, but also the reporting of the data must be established. We don’t want data to be shared in a casual or speculative manner. Stakeholders should have more formal meetings to discuss data and ask questions to get a clear understanding of what is a realistic expectation for work coming out the sales pipeline.
It is important to show the cause and effect of the proposed demand on each stakeholder when stakeholders meet. To put it another way, discuss the consequences of your salesperson’s success and the resources needed to prepare. Sometimes, the data is not available.