Sales Projections


How much will your sales team bring in this quarter? That question can get extremely complicated and potentially political.

DartCannon helps by bringing probability into the discussion, to help ground the debate in the full possible range of outcomes.

General Process

While this example is for sales, the process is the same for any type of budget:

  1. Identify Line items and Risks
  2. Estimate amounts for each item and probability for risks
  3. Run the simulation and establish targets based on results.
  4. Track actual amounts and amount remaining vs. targets

Estimation basics

Items are line items you want to include in the simulation. Each item has a 3-point estimate of low, high, and most likely. Items are things you are confident will have an outcome, but aren't sure about the magnitude.

Risks are like items but are not guaranteed to happen. For instance, if there is a big deal you're not 100% sure will come in, you'd put it here. Risks and items can be both positive or negative.

Simple Example

Back to our sales example, lets create some line items representing territories:

  • Western District - Between $0.5 Million and $2 Million, with $1M most likely.
  • Eastern District - Between $3M and $5M, with $4M most likely
  • Northern District - A new territory, with some uncertainty around if it will make money at all. On the low side, it might lose $0.4M but has at best a chance to make $1.5M, with a small $0.2M profit most likely.

In addition, there is a distribution partnership being negotiated. At present, it seems like a long shot with a 30% chance of happening, but bringing in between $2.0M and $3.0M in sales, with $2.2M most likely.

Putting this into DartCannon should look like this:

Sales Model


Running this simulation with 10,000 runs provides a result that looks something similar to the following:

Sales Model Results

Remember, your results may look slightly different as simulations depend on randomness. Since we're interested in the likelihood to exceed a given value, we'll be looking at "Left-handed probabilities".

Sales results ranges

So seeing the range of outcomes, we can now have discussions around where goals should be set based on our risk tolerance. For instance, we may want to use the following levels:

  • 25% - A conservative number used for accounting purposes
  • 50% - The internal goal
  • 75% - The target for bonuses

Remember that if the estimates are entered honestly, the ranges are based on uncertainties, so having a goal at 50% may still be fairly aggressive.

Tracking a Target

Once a target has been set, DartCannon can help track to see how likely it is you'll hit that target.

First, you need to turn on allocation tracking - in the menu, flip the switch for "Has Allocation". You'll see that two new columns appear - "Budgeted" and "Used". For our example, the definitions of the columns have changed slightly -

  • Budgeted - The amount of sales we've allocated to each district in sales
  • Used - The amount already sold
  • Min, Likely, Max - The estimate for how much can still be sold.

Lets assume we've targeted $5.5M for our total, allocated as $1.0M to Western, $4.0M to Eastern and $0.5M to northern. At the half way point, sales figures are $, $, and $ respectively. Polling the sales team reveals the following estimates for how much they expect is still possible:

Line Item Budgeted Used Min Likely Maximum
Western $1.0M $0.6M $0.2M $0.5M $1.2M
Eastern $2.0M $1.2M $1.1M $2.5M $3.2M
Northern $0.5M $0.1M $0.0M $0.2M $0.5M

While the sales distribution deal hasn't happened yet, it is looking more likely though the estimate is gravitating towards the bottom of the range.

The new model looks like the following:

Sales Allocation Model

Giving the following results:

Sales Allocation Model

Looking at the results, we can see that there is a 57.7% we exceed our target (and conversely, a 42.3% we don't make it).

Based on that, we can decide if we need to adjust our overall targets or implement some intervention.

Next Steps

  • We've gone this at the level of a sales team, but each district could do the same at a territory level, putting in all known possible deals, etc to get fully vetted ranges.
  • It is clear the results are very dependent on one big deal that makes a large part of the budget. While non-ideal, we can explore the impacts by looking at the results by putting in 0% and 100% as the probability.