For Professional Services Firms, Superior Capacity Planning Is Essential
The best capacity planning for business services doesn’t happen simply by studying the sales pipeline, and it doesn’t happen in a vacuum.
The best capacity planning for business services doesn’t happen simply by studying the sales pipeline, and it doesn’t happen in a vacuum.
Covid-19 has affected all facets of business, and Professional & Business Services (PBS) organizations were some of the first impacted by the pandemic. As their clients seek to recover, PBS firms must learn from their recent experiences to not only improve their operations, but also to ensure they are ready for future events. Doing so will require the right insights, systems, and technologies.
That’s where capacity planning enters the picture. With new remote delivery models, delayed or canceled projects, and other pandemic-related impacts, superior capacity planning is more important than ever.
How many resources do you need in a week, a month, or a season from now? Anyone tasked with capacity planning at a professional services organization knows that question is enough to keep you up at night. The sales pipeline might provide something of a clue—but often not enough. Warm leads go cold and deals fall through or—on the flip side—tepid talks suddenly turn red hot and there’s a monster contract to be dealt with.
The unpredictability of the sales pipeline can make planning, managing, and forecasting resources difficult. And that can set off a domino effect of issues: too many unbillable resources sitting around not generating revenue—or backlogs, customer complaints, and project delays because there’s too much work and not enough resources to execute against it.
Many professional services organizations look only at their sales pipelines when trying to plot out their future resourcing—and then teams are frustrated that it feels like a guessing game that they’re guaranteed to lose. To elevate personnel planning beyond gut feelings and darts thrown at a wall, consider shifting toward a services-demand planning approach. That means first considering other factors that may impact demand:
Can you mine internal data for insights on projects and contracts that closed during this period of the past few years? Are there certain staffing levels that are historically low or underutilized during this period? If so, how could that impact whether you begin ramping up or holding off on hiring senior talent or more task-based junior staff?
It’s not uncommon for one company to have multiple business models, from monthly retainers to hourly consulting fees to contingency fees to temp-to-hire arrangements. Multiple project types create a much more complex forecasting environment, but with the right tools, it’s easy to turn data into insights and see which project types in the pipeline are more likely to come to fruition.
Are some possible projects on-site and others virtual? Does some client work require extensive travel? While that might not influence whether or not a deal is inked, it can have a big impact on what the personnel plan looks like and should be considered early in the forecasting process.
Urgency and a compressed schedule can mean a client is more likely to say yes to a contract—but it can also send your team scrambling to execute the hours if you’re not properly resourced. During capacity meetings, keep a sharp eye on any timelines that buck the usual cadence for that reason.
This is where “gut feel” used to creep in. After a certain number of years in the business, you would start to get a sense of how often certain types of deals were going to come through. But financial tools have become so easy, powerful, and intuitive that you can now get weighted probabilities for each lead in your sales pipeline in a matter of minutes—based on past leads and closed deals—so you can swap that fuzzy math for an accurate estimate.
The best capacity planning doesn’t happen simply by studying the sales pipeline, and it doesn’t happen in a vacuum. It’s a real collaboration among finance, sales, and operations—so you can finally break the endless spin cycle of laying off and then ramping up resources and instead deliver better, more accurate forecasting.
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