Predicting Victory: How Bike Racers and Sales Pros Break Away from the Competition


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Wheels of Bloor Racing - Bruce Bird

Bruce Bird at the KW Classic 2011

The book and movie, Moneyball, popularized the David vs. Goliath story of the Oakland A’s, who pioneered the use of data and analytics to make decisions on how to build, train and play a winning baseball team. Applying data-driven insights to achieve superior performance has become widespread in sports.

You might be surprised to learn just how scientific bike racing has become, how much data is available and how pivotal the resulting insights are for staying ahead of the pack. For example, professional racers and avid amateur riders are now using power meters. These meters tell the rider exactly how many watts their legs are generating. During a ride, you can use this information to gauge how deep into your reserves you are reaching and how much you may have left in the tank. But the biggest advantage comes from analyzing the data after the ride – the second-by-second telemetry on Speed, Heart Rate, Power, Cadence, Torque, Altitude, Location, and Temperature. (See Figure 1)

Cycling Telemetry screenshot

Figure 1: Example Telemetry showing analysis of a ride. The graph shows power (watts), heart rate (bpm), altitude (m) at one second intervals.

The raw data is loaded into a program to analyze a single ride or race. It can also be combined with other rides over time to build a detailed profile of the rider, informing them of their strengths and suggesting paths to improve performance and results. The data provides so much insight that riders often joke that they do not need to race anymore; they can just compare profiles to see who is better suited to the course and the conditions. This is an exaggeration, but underlines just how much can be understood from data. For example, a rider’s peak 5-second power output would tell them how they would fare in a sprint finish. By contrast, a rider’s power-to-weight ratio is an accurate predictor of their climbing prowess. Based on these numbers, a rider with a poor sprint but an excellent sustained power-to-weight ratio might launch an attack on a climb, far from the finish, in the hopes that they will break away from the pack and avoid sprinting against powerful sprinters.

Paolo Eugeni in the Springbank Classic 2011

The avid use of data and analytics for sports insight was not the case not too long ago. The state of bike racing when Lance Armstrong decided he wanted to win the Tour de France was steeped in tradition but not necessarily science. Sure, there was tribal knowledge, but a truly scientific approach had not been tried. If Armstrong was going to be the most successful rider in Tour de France history, he would need to employ revolutionary methods. Rigorous training and exceptional talent were not enough.

Armstrong used data extensively and pioneered a systematic approach to bike racing. He knew at the time that he was powerful and could win on moderately hilly courses. However, he also knew that the Tour is won in the high mountains, so he dropped body weight and likely some overall power, in order to improve his power-to-weight ratio for the Alpine and Pyrenean climbs. Fifteen years later, even amateur racers apply a much more scientific approach to training. The sport has become data-driven.

Like high-performance bike racers, high-performance sales pros apply a data-driven approach to “win” and crush their targets. Data-driven selling refers to the use of big data, science and analytics to guide the daily actions of B2B sales professionals. Guided by analytical insights about their customers, sales reps make superior decisions on which accounts they target and how they engage with purchase decision-makers.

1st place in the 2010 Canadian National Road Race

Big Data has created an exponential growth in the amount of internal, external and social media data on companies and decision-makers. The ‘secret sauce’ is the application of predictive analytics (advanced mathematical algorithms) to transform this abundance of data into deep, real-time insight about customer needs and behavior. This enables inside and field sales people to fine-tune their day-to-day actions (i.e., Who should I call? What should I say?) based on data-driven evidence.

Contrary to popular belief, many bike racers dedicate their wins to the strengths and performance of their entire racing team. Each rider plays a particular role in contributing to the overall success of their team; in fact, when a rider wins, the prize money is split equally amongst the teammates. The science helps elevate the performance of each individual rider to achieve superior team outcomes.

This is the same in B2B sales. A high-performing team excels at transforming each individual sales pro into an A-player. Peak performance is achieved when each sales pro is as informed as possible about which accounts in their territories are most likely to be receptive and what kind of engagement and messaging is most likely to open doors and lead to opportunities. Science creates an entire team of high-performance sales pros can now beat personal sales records by hyper-focusing on only those customers and prospects truly worth selling to. In bike racing and B2B sales, the performance difference between teams who rely on data-driven sight vs. gut-feel is extraordinary.

Lattice Engines is a proud sponsor of the Wheels of Bloor cycling team. Stay tuned for more updates on the team’s wins and progress.

Interested in data-driven selling? Click here and learn how to infuse more science into your sales efforts.

Republished with author's permission from original post.

Ian J. Scott
Dr. Ian J. Scott is the VP of Customer Solutions for Lattice Engines. Prior to that, Ian served as CTO for Angoss. During his career, he has conducted quantitative risk assessment for UBS and also worked for CFM, a Paris-based hedge fund. Dr. Scott holds a Ph.D. in Physics from Harvard and a B.Sc. from McGill.


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