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Forecasting Accuracy, Part 2

Posted in: Cloud9 by Swayne Hill on April 24, 2009

This month’s Cloud9 Expert, Scott Roose from inContact, Inc., had some insightful things to say about forecast accuracy – a topic that I discussed here in a post last week. Scott, who is Director of Business Analytics, said they recently improved forecasting accuracy by more than 60%. Cloud9 would certainly like to take all the credit for that, but if you go back and read my post on ‘Why Does My Sales Forecasting Suck?’, you’ll see that forecasting accuracy is not a math problem and can’t be solved with a magic pill.  It is a management problem that starts by applying best pipeline management practices. In the Meet The Expert Forum, Scott fielded questions after the Webinar and said this about forecasting accuracy:

Our forecast accuracy has gone from being off as much as 50% to less than 20%.  It used to be said that the sales forecast was unreliable, now our executive committee uses it every month and quarter.  Not all of this is due to Cloud9; like every other data analytics / reporting tool your forecast is only as good as your data.  If you have bad data then you have bad forecasts.  Therefore, you have to commit to a standardized process and regular rep / manager reviews to get better data.

Cloud9 helps us dramatically increase the pipeline forecast visibility which helps apply the right focus and pressure to drive accurate data.

I really couldn’t have said it better myself.

Scott is a great example of what’s happening in sales operations today.  In the same way they’ve harnessed Salesforce to improve sales team efficiencies, they’re leveraging Cloud9’s on-demand performance management solutions to improve management effectiveness. 

 

 

 

Why Does My Sales Forecasting Suck?

Posted in: Cloud9 by Swayne Hill on April 16, 2009

My sales forecasts suck!

Pardon my French, but that’s something we hear from our customers every day. The frustration they face with forecast accuracy is of course compounded by today’s economic environment, placing a big executive-level bull’s-eye on their performance.

Even in good times, big companies spend a lot of energy triangulating their sales forecasts - and with good reason: if you don’t have clear visibility into where your revenue will come from, effective resource allocation is often nothing more than a happy (or lucky) accident. The problem is that clear visibility is a pipe dream for most sales organizations these days. Sophisticated analytic models require heavy IT involvement and support and that’s just not in the cards; IT shops are hunkering down just so they can deliver the core compliance systems enterprises must have. Extra IT bandwidth and capital budget? No.

One of the trends we’re seeing is a focus on improving pipeline management practices. With better visibility into day-to-day changes, sales teams become more proactively engaged in managing risks and exploiting opportunities, the drivers for forecast accuracy. A quick check of the rep and managers forecasts against historical stage-conversions trends and off-pipe revenue trends adds to confidence in the numbers, but it’s the up-stream practices that really drive results.

To improve your forecasting accuracy, follow these three steps:

  • Proactively engage in pipeline management, detecting change and taking early corrective action
  • Compare rep-level rollups on amounts by forecast category (commit, likely, best case, up-side) with manager override
  • Verify these two data points against your historical sales-stage-based conversion rates and trend the gaps to increase accuracy over time

All of this is within your control - no IT required. The key takeaway is forecast accuracy is really a pipeline management challenge. Sure, use data to arrive at a verifiable patterns. Triangulation, however, is a management process, not a CRM process nor a math problem. Accurate sales forecasts are an outcome of good pipeline management practices.