How are your teams forecasting work? How do you anticipate a budget when you’re not sure what you’re going to spend in a fiscal period?
Hi, I’m Peter Nichol, Data Science CIO.
Today we’re going to talk about capacity-based funding. This is a concept that many have heard of but few leaders execute effectively.
What is capacity-based funding?
Capacity-based funding is more agile and iterative than project-based funding and uses team size rather than project size to determine funding parameters.
To better understand capacity-based funding, we’ll use project-based funding as a reference. Project-based funding is the funding of a single initiative. You have an annual review cycle in a project-based funding model, almost like an annualized budget cycle. Many leaders would argue that not only is project-based funding inefficient, but it never did work.
There are three main areas where capacity-based funding differs from project base funding. First, it has a more extended period of estimation. In this new model, we’re funding a product team. This is a group that’s focused on a strategic or a multi-year initiative. This funding is also provided for a longer time—typically, 12, 14, or 18 months. Second, you don’t measure the costs, and you’re also not calculating the actual spend over time. Dropping these labor-intensive tasks frees up the team to focus on the actual product work and high-value-added activities. This shifts the focus away from operational tasks toward activities that directly add value to our product. Third, teams operate autonomously. The team members work in their little sphere and are focused on delivering a product. The team doesn’t ask for permission. They don’t escalate questions about the direction or which feature is more important. These teams are decision-makers. They analyze, interpret information, decide, and move on. Operating on their principles and norms removes much of the bureaucratic red tape that traditionally slows down high-performing teams.
The influences that press on capacity-based funding models
As soon as leaders hear that costs aren’t tracked, other questions get raised—mainly, “How do we influence the outcome and performance of teams using a capacity-based funding model?” There are a few different questions to ask to determine this:
- How much?—i.e., work volume or total hours
- How often?—i.e., work priority
- How many? i.e., team size
The first thing to determine is how much. Here we’re talking about the total work covered by the team. Another way to look at “how much?” is to consider the total hours of work (our capacity) over a given period. Often, this period extends over six months or a year. The second thing to know is how often. What’s are the frequency parameters under which the team will operate? Is this a team that meets once a year for three weeks, or is this team funded through the entire year? The concept of frequency is tightly coupled with the idea of priority. What’s the priority for the work the team is expected to deliver? The third determination is how many. This question refers to how large the team is. What’s the size of the team and the number of dedicated resources? What’s in scope (how much) and what’s the priority (how frequent) that will drive the team size (how big)?
What are the challenges with capacity-based funding?
With these benefits, it would be easy to assume that capacity-based funding is a utopian model and that everybody should move to this model. Well, it’s not all roses. There are several reasons why leading product initiatives with capacity-based funding models is difficult for executive leaders. Here are a few of the big hitters:
- Work delays are easier to hide.
- Shifts in priorities have a cost.
- Buckets of funds are harder to see than in a focused project.
- There may be a shift in portfolio leaders to manage new factors.
First off, it’s tough to identify work delays using this model. If you have project funding, it’s usually funded for a defined scope. However, with capacity-based funding, elements could be in scope, quickly determined out of scope, and then included back into the initiative’s scope. With this scenario, it’s tough to determine the original state of the ask and what the decision-making was to get to our current scope. There’s no way to track changes in a capacity-based funding model, unlike the change management we have in conventional project-based funding. The concept doesn’t exist because we’re not tracking expenses, and we’re not tracking the effort—or, more specifically, the dollars involved in that work product. So not having the specificity can be a big challenge if leadership continues to ask for the deltas; i.e., how we got from there to here.
Second, we aren’t tracking any financial spend. This results in not having a low-level (line-item level) of financial details to explain variances. For example, if leaders want to know how much functionality “A” costs to cost allocate to a business unit, we won’t have that detail. Of course, the team could develop some assumptions, but none of these will be tied to real numbers. Now, if leaders need that information tracked, it can be followed. But, if that’s the case, you’ve chosen the wrong tool for your financial planning. The absolute truth is that you’re not in an agile environment. You’re operating a waterfall methodology and pretending to be agile. I’ve been a leader operating in these types of environments, so take it from me: This makes everyone’s life miserable. This hybrid model is the worst of both approaches. It saps energy from the team and slows down team velocity.
Third, the team must have the autonomy to operate. This requires less—not more—oversight on the team. This also introduces more leadership challenges depending on the team members. This model works great for high-performing teams that gel and work well together, but it creates problems for younger and more immature groups.
How can portfolio leaders get ahead?
As we start to get into the details, we quickly run up against how we lead these opportunities. There are three strategies I want to share to optimize teams using capacity-based funding models.
Time series analysis
Time series analysis helps to analyze how long each segment takes to complete. By using this approach to forecast future performance, you’re able to determine the efficiency of your overall process.
Pipeline analysis brings in the cycle time for all the steps of the process. This analysis offers insights about specific pieces that make it through the pipeline and those that don’t. This step helps to provide a mid-point check of the efficiency of the flow or value stream.
Value leakage identifies where value was lost. Quite often, we’re managing pipeline throughput (outcomes) and interim milestones. This could be process gates or milestones in the middle of our plan. Unfortunately, if we only focus on the end game, we miss areas where value dripped out of our process.
It’s excellent if your process is efficient. However, ultimately, we need to measure the cadence (speed) and outcomes (value delivered) resulting from our process.
Now you’re empowered with new insights and tips for managing a capacity-based funding model.
If you found this article helpful, that’s great! Also, check out my books, Think Lead Disrupt and Leading with Value. They were published in early 2021 and are available on Amazon and at http://www.datsciencecio.com/shop for author-signed copies!
Hi, I’m Peter Nichol, Data Science CIO. Have a great day!