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Forecasting Sales from Your New Order History

Forecasting Sales from New Order History

In Parts 1 and 2 of this series on forecasting, Joel Harris details three critical KPIs to help integrators predict future results, followed by how to forecast revenue from your monthly backlog. In this final installment we unlock the predictive value of your new order history.


Does your project new order history chart look like an irregular heartbeat?

And if so, what in the world can this seemingly random data predict about the future?


New orders slide around as customers decide to pull in or push out new projects.


In a project-based integration business, most of us try to forecast new orders from our weighted sales pipeline and then listen every month to our sales team cheer in success because customers pulled orders forward, or moan in frustration because customers delayed orders, (especially large orders).


We often have very little confidence to base business decisions on our sales pipeline, and will miss signals that are important for cash flow management.


“A great pipeline backlog may never materialize and sometimes a weak pipeline yields stronger than expected results.  While I advocate relentlessly for improving your pipeline forecast accuracy, I also recommend using historical data to inform your decisions.”  Joel Harris


How might you be able to use the new order history data to predict future business?


Economists have long used a tool of comparing shorter term moving averages with a longer-term moving average to predict whether the trend is moving toward growth or decline.


I have found this to be a fairly predictive tool to either confirm normal seasonality, or to warn of a change in the business cycle.


It is a very simple exercise.


Take your last five years of monthly new order data and build out a chart that plots the trailing three-month average compared to the trailing twelve-month average for that month.

When you look at the graph, you will undoubtedly note that in periods where the short-term moving average was below the long-term moving average you were headed into a slower cycle. The longer this trend happens the more you should be concerned about a longer slowdown ahead of you.


Conversely, when the short-term moving average is above the long-term moving average, you are headed into growth and expansion.


Integrators leave business opportunities on the table when they are unprepared to staff up to meet demand. When we find our resources fully booked, it is usually too late to start hiring and training to meet that demand, so an opportunity passes us by. Worse, we often find ourselves reacting to the past six months and miss the signal that we are contracting when we thought we were growing.


At the beginning of every month, simply look at your new order history data from the prior month and you may be surprised at how accurately you can begin to forecast the next month’s new orders.

When you combine this with your weighted sales pipeline forecast, you will gain confidence in matching your cash flow management plans to the reality of the market growth or decline.


Joel Harris concurrently serves as a Strategy and Business Consultant with Navigate Management Consulting, and the COO for HB Communications.



Navigate Academy Module 14: Succession Planning & Next Generation DevelopmentDo you want to learn more?

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Title: Succession Planning & Next Generation Development


Keep Reading: Part 1 of this series on forecasting

3 Critical Key Performance Indicators for Systems Integrators


Keep Reading: Part 2 of this series on forecasting

Forecast Revenue from Your Monthly Backlog

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