The work related to a valid and accurate revenue forecast using the Opportunity Object in Salesforce is one of the most valuable components of the platform. Let us take a deep dive into the details.

If you are a Salesforce organization, you may have an approach to revenue forecasting that is unique to your organization. We use organization because there are revenue forecasting techniques for non-profits who need to forecast donor collections which are treated like revenue. So, from the standpoint of the mechanics of Salesforce, these transactions have similar characteristics.

In last week’s article, I shared the reconciliation of a revenue forecast. I highlighted, at a high level, the standard components that are used in determining the accuracy of the forecast. Now, let’s take this a step further.

Let us start with the workflow of an opportunity. In Salesforce, the Account, or customer, is where the recordkeeping begins. The Account contains the many attributes of your customer like address, how you may have sourced the customer, the status of the customer, and so on. In addition, there are the key contacts to the account; those individuals that you work with and their specific information like contact information, social media information, and recorded historical activities and meetings that have taken place with your contacts. In addition, you may have your accounting information such as sales that report into your Account from another system to have sales, product, and service information related to this customer thus giving you a full picture of your account.

Now, we need to understand where the next revenue will be coming from. Typically, in Salesforce, the object called Opportunities is used. Opportunities are related in the database to the Account and the Contact. Opportunities are organized by stages of the progress towards a sale by using the standard field called Stage. The Stage field is designed around your typical deal progress from the beginning where awareness of the deal is learned all the way to the day that the contract is inked. The Stage field comes with pre-loaded values or you can customize these values with you own stages. Here is a typical layout of an Opportunities Stages:

As you can see, these stage values are listed in the order of the deal progress. There is the stage name, an API name to be used in the software language to reference, the Type, the Probability, and the Forecast Type. Each of these columns show the values in the fields related to the stage. In this example, if there is a single opportunity that is in the Prospecting stage, management has agreed that there is a 2% probability that the deal will close. In other words, 2% of all deals that begin for this company in our example will result in a closed sale based on the sales history. This varies based on each business, of course, but the logic is based on history and the information that is gathered on the opportunity in this stage and compared to previously won and closed deals.

Let us look at the individual components that may be part of the Prospecting stage in our example. We use “two plays” in our Prospecting stage, Account Research and Initiate Contact. Each play has a set of parameters that must be learned (prospected). These parameters may look like this:

The answers to these questions are captured in the Opportunity record in these fields. When captured they are benchmarked against the historical answers for this specific stage to determine if they match historically and if so, then the probability of 2% will most likely be accurate since the values would be matched to opportunities that closed historically with the same or similar values. In this example, if Account size in number of meters typically has 100 or more meters for the opportunity to advance but the actual value captured is less than 100, then the probability that this deal has a 2% chance of advancing to a close is already off track and less than 2%. The same logic is used for each field in each play. The sales manager then can review the information in the Prospecting Stage to determine how well a specific deal is matching up to the historical values of past deals

When the opportunity is setup in Salesforce, there are two standard fields to help with the forecast of revenue, Amount and Expected Revenue. For an early stage opportunity, there may not be any value yet because it is too early to know the amount. If so, then Amount would show zero and the Expected Revenue the same. If, however, the product that they want has a price of $1,500 and they needed 2 items, then the Amount would show $3,000 and the Expected Revenue would show $60.

The affect is that for early stage forecasting, $60 dollars can be added to a period’s revenue forecast if the anticipated Contract start date is within the reporting period. In other words, if this deal begins on January 1 and has a projected contract start date of March 31, the revenue forecast will include $60 for this early stage deal based on the parameters captured in the plays of the Prospecting Stage.

This logic is used for each stage for each deal and the calculations roll down the same way through each set of “plays” per opportunity stage.

This is how we help customers design and organize their revenue forecast within Salesforce.

When we think of the accounting process of reconciliation, we typically are thinking of the reconciliation of the balance sheet accounts. After all, the working capital side of a business is closed out annually and the earnings or losses are swept into retained earnings. The FASB requirements and standard practices of reporting for organizations.

But back on the working capital side of business where operations take place (Sales and Expenses), there is a far more important reconciliation process that is imperative to the life blood (cash) of a business. This reconciliation centers around the most important account in the chart of accounts, revenue.

Yes, sales reconciliation is full of bends and twists. We read about it every day, organizations missing the mark on sales forecast. Do you ever wonder why this occurs?

At White Rock, we work in Salesforce.com every day and we serve our customers who use it for tracking customer activity, recording opportunities for leadership, and addressing the anticipated sales transactions in the organization. The revenue may be derived from services, products, or donations.

What we know about the system processes that we build is that there is a defined and predictable relationship between the data recorded in an opportunity’s stage of the sale and the forecast category. For example, an organization may have a five-stage sales process like this:

• Initiate
• Discovery
• Prove
• Propose
• Negotiate

These stages would be related to a forecast category setup maybe like this:

• Pipeline
• Best Case
• Commit
• Likely to Close

There is a percentage that is assigned to the stage to represent how likely that opportunity will be to get booked as a sale. These percentages are determined based on history and sales management’s sales process activity criteria. Here is an example of how this all comes together in Salesforce.com:

Stage                     Probability of Close                         Forecast Category

Initiate                  10%                                                        Pipeline

Discover               20%                                                        Pipeline

Prove                    50%                                                       Best Case

Propose               70%                                                        Best Case

Negotiate            90%                                                        Commit

In this example, if we have a deal that is in the Prove stage, then management has determined that 50% of the time, half the deals, will close when they reach this stage and they are categorized for Forecasting purposes as a best case. If the total value of those deals is $2,000,000 then experience says that $1,000,000 will result in booked sales.

Now the tricky part. What “moves” a deal along in these stages that provides the forecast outcomes? Well, sales activity on behalf of the sales team, of course. It is assumed that the activities are accurate and well-defined to result in a predictable probability of booked sales.

But what happens if a salesperson is “pushing” the input of data to better reflect a deal’s progress to help the in-process performance look better? Of course, then, we have a padded prediction. If management is not testing the sales activity inputs and puts an inherent trust in the values provided in the sales activity, then a risk is now set in a deal’s outcome. There is a mismatch now recorded in the deal tracking system between the buyer’s view and the seller’s view. Here is where the reconciliation of forecasted revenue breaks down.

This is where organizations should focus their reliance on the type of sales activity that is required in a specific stage of a deal/opportunity. We see so many times where there is poorly defined or subjectively defined activity requirements that are not really supporting a buyer’s behavior. As a result, quarterly forecasts become overstated and unreliable or, even worse, dangerously reflecting the value of future cash flows.

We believe that proper processes and tools that can be associated with long cycle sales are the most important, tactical weapons against this risk. We work with several organizations that focus on this and, in fact, we have developed applications native in Salesforce.com to help leaders have reliable sales forecasting.

We recommend that these types of tools be leveraged to provide a more objective set of activities that are related to the buyer’s journey and behavior. Using them will thwart the subjective input of data that can skew the success of a deal. We invite you to learn more about how White Rock can help you ramp up and conquer the risk and dangers of over-stated progress of deals in your organization.

The proper reconciliation of revenue in an organization is so vital to a healthy predictable cash flow. The setup of the Opportunity object in Salesforce.com utilizing the standard fields Stage and Forecast Category are vital. If this is an area where you think your organization can improve, please give us a call.

Reporting the revenue forecast in Salesforce.com is vital information for predicting Sales, budgeting operational support and planning cash flow. The sales team is hard at work moving deals to close and staying on track while management is reviewing these deals to determine how viable and credible the forecast will be for the specific reporting period. Let’s take a deep dive into a simple illustration of how this gets done and what the components are of the forecast.

The deals, or Opportunities, as the standard name goes in Salesforce, are the records stored in the database that show how well a deal is progressing towards the expected close date and amount of the sale. Each deal has some standard fields that are used to reflect and calculate this important milestone. Here is a summary of these standard fields that help with the forecast report:

• Opportunity Name – the identifying name of the specific deal
• Opportunity Owner – the rep that is working the deal and owns its success
• Stage – the progress point of the deal (refer to last week’s article for more details)
• Opportunity Amount – how much the deal is worth in dollars
• Close Date – the date that the deal is expected to close and become a sale
• Probability – the percentage used of deals in a particular stage that close historically (refer to last week’s article)
• Forecast Category – the value assigned to a stage when reporting sales pipeline results

NOTE: If you didn’t read last week’s article, this would be a good time to refer back so that the calculations are clear as we present the reporting of opportunities below.

The critical computation for the forecast is related to the Opportunity Amount, the Stage, and the Probability. Because management continuously reviews the percentage of deals that close based on information gathered that is related to a “good” deal and a “not-so-good” deal, the probability represents what the likelihood is that a deal will close with the details of each input about the deal. Here is an example of a typical forecast report:

As you can see from the example, the Amount column represents the total expected revenue to be generated from the deals in the list while the Expected Revenue is related to which stage the deal is in and the probability associated with that stage based on historical outcomes. For example, the first deal in the report for XYZ Corp, shows a deal that is valued at $1,500 but because it is so early in its stage, the deal probability is only 10% based on experience. The basis of the 10% can be further adjusted if the parameters of this specific deal are not in line with what historical deals may have had too if they are vastly different from past deal parameters.

Let’s dive into parameters now. These parameters are custom defined attributes of a deal based on sales leadership’s knowledge of their product and services. Each stage has a set of specific parameters that must be articulated to a prospective customer to learn whether they are a true buyer.

Suppose we look at all the stages in another deal example. Looking at each stage below, we have a specific set of actions and information that must be captured by the rep from the prospect by stage to give credibility to the overall health a deal. Here is a table of what this might look like:

Stage – Prospecting
Parameters to learn in this stage:

• Reception to Elevator Pitch – pitch the deal
• Size of organization – how big is the org – are they the right “fit” for our product/service
• Has a compelling driver for product/service – what is the pain point that they are experiencing
• There is a project sponsor and budget – can they fund this project or get funding – what is the cost of doing nothing?

Stage – Discovery
Parameters to learn in this stage:

• Define current problem – size up the problem and the effect on the organization’s operation – what is the metric
• Where is the pain felt from the problem – which area of the organization is experiencing the problem
• What other options are being considered for the solution – competitors

Stage – Solution/Presentation
Parameters to learn in this stage:

• Share solution options and successes from them – present the solution and pricing
• Implementation timeline presented and solution demonstrated – how will the solution get implemented and how long will it take
• Feedback on demonstration – what is the reaction and next step from the prospect and the sponsors

Stage – Negotiate and Close
Parameters to complete in this stage:

• Submit final adjustments and contract for signing – any discounts, other terms and conditions to consider pushing the deal through
• Plan implementation – bring the players in for the implementation game plan
• Get documents signed and hand-off to production – ink the deal!

Each of these parameters for the stages in this example are key turning points (tipping points that take the deal to the next step/deal velocity) for the deal to progress and move forward. As each of these parameters are learned, completed, and evaluated for quality related to the history of similar opportunities, the probability is established based on the answers to each of the parameters. For example, if in stage Prospecting, it is learned that there is no funding for the deal, then the chances will be very low to zero that this deal will progress, so it would fall “outside” of the “normal” historical deal flow for this stage.

We invite your feedback and ideas to share related to the revenue forecast. Please contact us with your comments and questions.