The challenges of revenue forecasting

    Written by CloudBlue PSA on 2020-03-25 Last updated 2020-07-01 - 3 minute read

From the middle ages through the renaissance period and even as late as the 18th century, alchemists sought the philosopher’s stone. A magical device, substance, mechanism or process that could transmute base metals into silver or gold.

Volumes were written, secret and complex methods were devised, multiple stages of transmutation were documented all with the single goal of creating something of value from nothing.

Revenue forecasting is actually a very similar quest, the Magnum Opus (Latin, Great Work) of all professional services company’s management teams. The problem of producing a forecast that is worth analysing and using from generally quite base, patchy, incomplete and often stale inputs, challenges everyone.

Logically, they look to a PSA system to generate this forecast in the same alchemic manner that the scientists and mystics of old did for precious metals. However, like those ancients, they are probably doomed to fail as most PSA systems incorporate systemic problems that make this goal basically un-achievable.

Most enquiries from consulting business state revenue forecasting as a key goal, illustrating how universal this quest is.

Why should this be, just why is this problem so tough to crack?

Aside from the fact that a forecast is about the future and so inherently invented, the systemic problems break down into three categories:

  1. State: during day to day operations, people focus on delivery not forecasting. Getting them to focus on forecasting is an exceptional task, not a day to day one. All PS companies will understand the problems of getting people to submit timesheets, exactly because it is an exceptional task. How much harder is it then to have people focus on generating a forecast? Running a report from a system where state is unknown (i.e. where some people will have provided an update and others not) simply generates a meaningless and/or potentially dangerous view of the business. Systems that rely on taking data directly from project plans suffer from the same state issues. If the plans have not been kept up to date (and who can say all plans are always perfectly updated?) then the resulting report is still the data equivalent of base metal
  2. Completeness: is a complex subject as it relates to forecasts. There are naturally three broad definitions for forecasts; committed work; expected work and potential work.
    1. Committed work should be simple, but even committed work suffers from planning fade. A year’s work is unlikely to be planned (i.e. allocated to staff members or teams) a year out. It is far more likely to use rolling forward planning horizons, meaning that committed and contracted work may not appear on the plan just yet and so could be missed from a forecast based on the plan.
    2. Expected work is a really tough one. This is change or growth orders on existing projects. Often more than half the work in hand will be generated by change orders not new business. Projects naturally grow, scope changes, new phases get included etc. but most PSA systems only support contracted work, thus forecasts miss this vital component.
    3. Potential work should be recorded in the CRM system, but adding this to committed and expected work profiles has major issues. It is unlikely to be modelled at the same level of granularity as work in hand, so adding it to the report compromises data quality, plus start date uncertainty makes the resulting analysis problematic.
  3. Ownership: needs to be clear as this ties back to accountability which in turn drives a positive quality cycle. Taking a report automatically from a system undermines accountability and leaves ownership unclear. Unless forecasts have been specifically committed by those in charge of the detail (Project Managers or Sales staff), ownership is not bootstrapped and so the result cannot be relied upon.

A stand-alone project based PSA system will never generate a meaningful forecast for these reasons.

What is the answer?

To be effective and of real value to the management team, forecasts:

  • need to be informed but not driven by plans and opportunities;
  • need to be editable to reflect the latest knowledge, in particular the areas where the plan is inaccurate or stale;
  • need to allow expected work to be captured easily;
  • need to model opportunities in the same manner as work in hand with optionality on start dates;
  • need to have a consistent state point and lastly;
  • need clear individual ownership.

Do all this and your process will produce gold, not yet another lump of lead.

Read More

The difficulties of forecasting professional services revenue
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About the Author: CloudBlue PSA is the most complete cloud professional services automation (PSA) software on the market. Purpose-built with functionality to simplify every need of MSPs and Professional Services Organisations, CloudBlue PSA introduces a state-of-the-art PSA system built for today’s modern service provider. The platform empowers services organizations to scale recurring channel revenue and diminish operational complexity via its advanced product suite, which includes automated billing and reconciliation, an industry-leading customer support center and network operations center (NOC), real-time profitability analysis, and much more. CloudBlue PSA is available globally. Follow CloudBlue PSA on , LinkedIn or Website

Tags: Business, revenue forecasting


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