According to the Sales Operations Center of Excellence, 54% of sales operations departments are less than 3 years old. Sales operations is one of the youngest roles in any sales organization, but with the on-going growth of data and technology, it’s evolving at lightning speed.

Since Xerox pioneered the role in the 1970s, sales operations has become responsible for a growing scope of tasks including supporting sales processes, maximizing the quantity and quality of sales data, generating forecasts and defining and measuring KPIs.

And now a perfect storm of sales drivers is giving way to the next evolution of sales and a new role needed to support and drive this function.

The Science of Sales

As Base CEO Uzi Shmilovici put it in his keynote at the 2016 Forecast Conference, the Science of Sales can be defined as using scientific methods to collect and analyze sales data in order to scale sales in a rapid and predictable fashion.

While similar methods have already gained widespread popularity in organizations like marketing and support, Shmilovici explains that there are three key drivers currently spurring sales to turn to this scientific approach:

Ability to collect data: consumer-grade, mobile sales applications have made it possible for reps to enter and access data anytime, anywhere.
New data technologies: new technologies make it possible to perform large-scale data analysis in a real-time and cost-effective manner.
Market dynamics: not only are buyers becoming more educated, but the growing number of sales tools on the market makes competition more intense than ever before.

These trends require and enable sales teams to take their performance to the next level by scientifically prioritizing initiatives that drive growth in actionable and quantifiable ways. For example, consider the following question: if you want to increase sales by 25% next quarter, what do you need to do?

To answer this question in a meaningful and strategic way, you must start with a mathematical relationship. Fortunately, the sales funnel, by definition, can be described mathematically using fairly simple formulas. Usually, sales operations plays a key role in defining the sales funnel, optimizing the conversion rates, etc.

But this is where it gets tricky: when you start thinking of all of the dimensions or factors that can impact your sales. Simply looking at your sales funnel by the dimension of industry can generate a dozen or so different scenarios and levers that can be pulled to alter your sales outcomes. Enter the Sales Scientist, a new role dedicated to maximizing revenue through scientific analysis of sales data and the generation of actionable and prescriptive insights.

It’s easy to see that sales science is a natural extension of sales operations. And that, in many ways, sales ops is actually responsible for laying the organizational groundwork for sales scientists to successfully analyze and improve performance.

Whether you’re looking to transition from sales operations into sales science or simply want to step up your ops game, here are three areas where sales ops leaders can set their companies up for sales science success.

CRM Adoption

Having a high volume and quality of data is critical to the science of sales, and this starts with CRM adoption. Unfortunately, 74% of sales teams using CRMs report poor adoption rates. So how can you as a sales operations leader determine whether CRM adoption is an issue in your organization and begin taking the necessary steps to fix it?

– Pull a quick log from your CRM to see what percent of the team is actively and consistently signing into the platform.
– Spend some time shadowing different members of the sales org, from BDRs to AEs to management. How much time to they actually spend in the CRM? When managers do their forecasts or have one-on-ones with reps, are they using the CRM, or are they using spreadsheets?
– Try creating a few quick lists and reports. How much data is returned to you? This will be indicative of how much information is being entered into the platform.
– Look at your data export. Do you notice that the first list items are being selected the majority of the time, or that reps are consistently picking “other?” Are close dates being added retroactively? If so, your team might be using your CRM, but they are not doing so effectively.

If you notice any of these red flags in your organization, don’t panic – there are plenty of things you can do to turn things around.

Sales Process

If you’re in sales operations, you already know that a good sales process is the backbone of any successful sales organization. As such, much of the science of sales is dedicated to helping companies measure, scale and optimize their sales processes. And the more refined the process, the more granular and impactful your scientific sales insights will be.

Here are a few critical areas where sales processes are typically in need of some fine-tuning.

– Keep your process buyer-focused. Too often, companies create sales processes that lay things out the way that they wish they would happen. In reality, a sales process should be reflective of your customer’s needs – not your needs.
– Qualify the right buyers. Not all leads are created equal, and knowing which to focus on and which to walk away from based on past successes and failures is key. Make sure your sales process features the questions that you need to ask to identify and build profiles for these buyers.
– Ensure every scenario has a follow-up action. Just because someone doesn’t answer your call or respond to your email doesn’t mean that that opportunity is dead. Don’t leave things open-ended or up for interpretation; give reps a set list of steps to follow regardless of outcome.
– Know when handoffs should occur. Sometimes certain information and steps can be overlooked if not everyone on the team is 100% sure who owns which parts of the process. Be sure to document this information and that your team knows exactly where handoffs should happen.
– Focus on the most impactful part of the sales funnel. As tempting as it may be, avoid zeroing in on the bottom of the sales funnel. Instead, dig into your process in the early and middle funnel stages to identify and define the activities that will ultimately generate revenue.

Data Strategy

To have the right quantity and quality of data available to extract any meaningful insights, you must have a plan in place. And this doesn’t mean capturing every tidbit of information in your CRM. It means being smart and strategic about the data points you collect by making sure that each one has a purpose.

Any successful sales data strategy must be rooted in the discipline of the Scientific Method. Every sales leader has certain observations and assumptions about what’s going on with his or her sales performance, but the key difference between the art and the science of sales is taking a step back and testing and analyzing these hypotheses.

This can be accomplished in 3 steps:
1. What are your key goals and challenges? Ask yourself why these challenges are occurring and what can be done to achieve these particular goals. For example, why are deals from one territory closing less frequently than others?
2. Create a list of hypotheses about how these things might happen. After doing some research, we came to the conclusion that poorly trained reps, tough competition, seasonality and lack of rep activity could all be reasons why deals from one particular territory are closing at a lower rate than those in other territories.
3. Determine and collect the data points you need to prove or disprove your hypotheses. If I want to determine whether or not reps in this territory are not actively chasing these leads, what are some of the data points I should be collecting? I should definitely be monitoring the number of calls and emails sent each day, both for this team and all others so that I can compare. I should also look into number of meetings booked, time to first action, and number of outreach attempts before unqualifying a lead for unresponsiveness.