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Do you have access to all your sales performance data? If you have to search for answers hidden across multiple spreadsheets and systems, you may be operating on some erroneous assumptions. The reality is, if you want your sales team to be aligned with corporate goals, you can’t guess your way through sales compensation planning. You must be able to predict future outcomes and prescribe the best next action. Prescriptive plan recommendations don’t rely on fortune-telling. They require an augmented intelligence (AI) tool to revolutionize the way sales compensation plans are created, managed, and optimized.

How accessible is your sales performance data?

Accuracy is the first step in finding insights in your most recent data. If it’s not accessed in real-time directly from the original data source, then you won’t be able to leverage AI. So, while this is a simple question, it’s critical for your ability to make recommendations.

How often are your compensation plans revised?

Traditionally, compensation plans are revisited annually. But does that make sense for your organization? Corporate goals can change quickly, as revenue targets rise. In fact, 92.5 percent of organizations raised theirs in 2016 (1). So, while you have to increase revenue, how will you know how many reps to hire, the quota to set, and what behaviors will deliver results? Without an AI-engine fueled by a complete data set, you won’t. You might as well throw a dart, or pick a number like 47% of companies do today when making mid-year plan changes today (2).

Are your compensation plans optimized?

Whether you have hundreds or thousands of sales reps, compensation plans shouldn’t be the same for everyone. It’s not a one size fits all. This approach is ineffective for many reasons. You also cannot optimize incentives without the right tools. Spreadsheets aren’t going to suffice here. There is already too much room for errors and overpayments. Calculating statistically significant recommendations to impact sales behaviors and revenue isn’t possible in spreadsheets. Only AI accelerates compensation planning and optimization accurately and quickly.

Optimization starts by calculating all the what-ifs in your sales ecosystem. With these plugged in, augmented intelligence can begin prescribing recommendations. AI is not perfect. It requires human insight and an understanding of how you built your plans and the sales behaviors you are trying to influence. AI gives you a starting point for annual planning, guides mid-year adjustments, or simply validates your hunches on full-scale optimization of incentive plans.

What can Augmented Intelligence reveal?

AI and machine learning do all the heavy lifting–calculating statistical significance and making prescriptive plan recommendations with zero guesswork. Interactive visualizations, simple drag and drop, and powerful filters make it easy to understand what sales behaviors you’re driving and how they align to corporate goals. With these tools, you can do more than make those reckless assumptions, including:

  • Discover what it costs to drive sales
  • Clarify what behaviors are influencing sales
  • Identify costly outliers
  • Uncover where you’re just paying for deals instead of performance
  • Determine which commission rules are effective and which aren’t
  • Find opportunities to stretch your commissions budget
  • See which SPIFFs can move the needle with any remaining budget

You can learn all this and more with AI. This type of valuable sales performance data becomes the foundation for year-round planning. Because the truth is your high performers could be a minority. Research suggests only about 57.1 percent of salespeople make their quota (3). To get more sales reps to the top, you must have effective compensation plans at your foundation. You cannot go from tactical to strategic, and predict the future without an effective understanding of how your plans are driving behaviors. Your crystal ball will only be filled with haze.

What if AI doesn’t make a recommendation?

When looking at your data, there will certainly be occasions where a recommendation isn’t provided. This doesn’t mean that you shouldn’t do anything about that particular rule. That’s when you need to dig further. Find out who is participating and getting paid under this rule. What do those sales reps have in common? Regionality? Tenure? There are many possible layers to peel back. This is when it’s time to flex your human insight and analytics muscle to find out if this rule is driving the right behaviors or just costing you money.

Where to start?

It’s time to stop guessing. Act quickly and confidently to impact your business using prescriptive plan recommendations with Thunderbridge AI for Commissions. Get accurate, real-time sales performance data with Thunderbridge Analytics. Enjoy drag-and-drop functionality, filtering, and interactive visualizations. Try it out today with a demo and product tour.



(2)  The Alexander Group, 2017 Sales Compensation Trends Survey, January 2017


Author Bio

Kevin Markl

Kevin Markl has worked with CallidusCloud for six years, evangelizing the Lead to Money suite to align sales and marketing teams, replace disconnected systems, and drive bigger deals, faster. Prior to working at CallidusCloud, Kevin graduated from McGill University and held global business development roles with the US Department of Commerce and Consulate General of Canada in San Francisco. Kevin is a Distinguished Toastmaster, speaking frequently at conferences, and will share how sales operation and compensation leaders are using analytics to guide tactical decisions and drive strategic growth.



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