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    Under the hood: Bringing science to the art of sales

    May 11, 2018By

    This is the first post in a new Traction blog series called Under the Hood, where we'll open up about our own business; challenges faced, solutions developed and learnings usually meant to be kept internal. We're always looking to enable individuals and organizations and sometimes the best way to do that is by telling our story.

    Data-driven decisions allow you to scale your business with intention and a clear strategy

    Sales has often been considered an art due to its lack of predictability and the interpersonal skills needed to be a great salesperson. There's a lot of truth to that, but analytics are becoming a necessity for sales leaders and business executives to compete in an increasingly competitive market. In the past, Traction often chased the shiny objects, and that allowed us to grow quickly, but only up to a point. As an organization scales you need to be more targeted and focus on the areas that make the most strategic sense. Our industry has grown too, and the bigger it's gotten, the harder it has become to stay in touch with what's happening on the ground. Eventually, you realize data, not gut-instinct, is the best indicator of what's happening in the market.

    Drive change with historical insights

    Diagnostic analytics dig through historical data to understand which processes and causes led to a specific outcome. If a business is looking to improve itself, diagnostic analytics can be incredibly useful. At Traction, we look at historical trends to better understand fluctuations in sales, pipeline growth, close rates and more at a given point in time. In one instance, our diagnostic analytics revealed something we hadn't noticed before — we were becoming less effective at onboarding new sales reps.

    1. Our ramp time for new reps was getting longer.
    2. We weren't seeing the same contribution from our first-year reps that we had previously.
    3. Our sales targets were also too high, so new reps felt like they couldn't succeed.

    Once we'd identified these issues we were able to come up with a plan to redefine our training program to improve on those gaps we'd identified.

    1. We redefined our ideal candidate profiles in the recruitment process.
    2. Our initial 60-90 day onboarding period was restructured to incorporate feedback learned.
    3. Sales expectations for new reps now account for the expanded scope of their role, which included opening new territories and lines of business.

    With these changes in place, we felt more prepared to continue scaling our team, geographies, services and target industries.

    Building an effective predictive forecasting model

    This year, our team was given an ambitious fiscal sales target. We had built our new forecasting model about six months prior and were amazed at how accurate it was. Once we knew we could trust our model, we were able to determine the number of people we would need to onboard each month (with current sales objectives) to hit that longer-term target. When you have clear milestones and measures for success alongside data that tells you whether or not you're on track to achieve those milestones, it's so much easier to rally the business behind you. If we need help from our services general managers we can justify our stance and really help them understand what's going on and why they're needed. As a sales leader it's also a useful motivational tool. We recently experienced a tough month for pipeline creation; but since we'd defined clear pipeline numbers we needed to hit in order to reach our target, it was easier and faster to identify how we could get back on track. The team responded by blowing that pipeline number out of the water.

    The make or break: Data governance and user adoption

    Don't underestimate the impact of being an early adopter in data stewardship and being vigilant and meticulous. The earlier you start collecting clean data that you can learn from, the better off you're going to be. Data is rarely 100% accurate and you need to draw a fine line between structuring data governance for accuracy and structuring it for user adoption. The most common challenges faced by organizations looking to adopt data-driven cultures are cultural resistance (32.5%) and poor understanding of data as an asset (30.0%). As a leader, you need to consistently reinforce and help your front-line staff understand the true value of data by being transparent about how decisions are made and how the data contributes. The most important element of a data-driven culture is change management, and data is a game of compromise. Keep it simple and keep it meaningful. Don't get too greedy.

    It's 2018, let science inform your art

    Interpretation, planning and execution require plenty of gut intuition, but when conversations are driven by data, they're supported by a solid framework of information. I used to walk into a meeting room and everyone would start with a different opinion. You'd constantly hear “I think...” or “my gut sense...” but now you hear “the data is telling us this...” Leveraging data as a guiding point for discussion allows you to hack the process and jump right into your third meeting without needing the first two. Empowering your sales leaders with the data they need to build an effective strategy is one key component of becoming an enabled organization. We'll be discussing the role of the data-driven individual at our upcoming conference, TractionForce. Join in the conversation on June 21 with some of the most innovative thinkers in the business world.


    Join in the conversation as we discuss t he role of the data-driven individual with some of the most innovative thinkers in the business world

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