Improving Sales Force Effectiveness Using Six Sigma

Abstract For effective sales, companies need to differentiate how they allocate their limited sales resources among existing customers, customer service and new business development (prospects). When ranking Customers and Prospects, the common metric is usually either sales or profits. This paper will show how you can blend multiple desirable sales characteristics including Sales Growth, Close Rate, Payment History, Unit Volume, Repeat Business, along with Sales and Profit, to create an "Overall Performance Factor" for each Customer or Prospect. This Overall Performance Factor can easily be sorted to create an objective ranking of best to lowest performance in which you can prioritize and assign the appropriate sales resources to meet the company's objectives. Background Sales Process / Performance Improvement Project Customer Ranking - Shortcomings of the 80/20 Rule Multi-Measure Approach Needed Created a New Customer Ranking System This Property & Casualty Insurance company needed to evaluate their Sales Process. While they were profitable, earnings were flat for the last 3 years and their investors were punishing them with a low stock price. The analysis led to an evaluation of their Independent Sales Force. They sold insurance through independent agencies. These could be sole proprietors who sell one company's insurance products exclusively or larger multi-agent firms that sell multiple, and even competing lines. At the time of this project they had about 2400 independent insurance agencies. These agencies were their "business-to-business" customers. Ranking their independent agencies based on Sales (traditional method) quickly showed itself as being an incomplete view. They were concerned about multiple measures including Sales Growth, Consumer Retention and Profitability. The company needed to do great in all of these measures, plus Sales/Revenue, to meet the earnings growth expectations their investors were demanding. A Multi-Variable-Pareto calculation tool was used to develop a single customer (or independent agency) ranking. This tool used the principles of Pareto Analysis but allowed them to calculate an Overall Performance Indicator based on multiple performance factors. Multi-Variable Pareto Method Pareto Charts were developed in the late 1800's by an Italian Economist, Vilfredo Pareto. He used this analysis to determine that wealth was skewed to a small portion of the population. In his time, 80% of the land in Italy was owned by 20% of the families in Italy. From Vilfredo we derived the Pareto Principal or 80/20 rule. This is commonly used in sales, with 80% of sales generated by only 20% of customers. Pareto Analysis is a great business tool, but there is more to increasing profit than focusing on just sales, or even just profit. There are leading and lagging indicators of profit growth from the customer base. Measures The first step was to determine what measures defined great customers (or great independent agencies). A cross functional Six Sigma Sales team was formed representing Sales Executives, Sales Representatives, Marketing, Finance and Operations. The Insurance Company Six Sigma Sales Team defined great agencies as having: High Sales $ High Gross Profit % High Consumer Retention High Year-Over-Year Sales Growth By defining Sales Growth as important a measure as Sales $ they were signaling to their Account Executives that focusing on smaller but growing agencies was just as important as focusing on larger, low growth agencies. As you will see in the data below, many high-sales agencies had flat to declining sales. Forced Ranking Force Ranking mathematically equates these different measures for the overall calculation. This process simply makes the largest number equal to a 10. Then all other customers are proportioned with respect to the largest. This Factor is used in the Overall Performance calculation. Overall Performance Factor The Overall Performance Factor is a combination of each measure's factor. You can also weight each measure and use this to calculate the overall performance factor. The last step is to sort the customer list based on the Overall Performance Factor. Then you can make prioritization decisions about how to allocate Sales and Customer-Service time. Top Customers - Get them the most focus, time and service Average Customers - How can we move them up? Below Average Customers - Can use multiple strategies such as using an inside customer service rep versus field rep to service this customer, or remediate them Insurance Company - Customer (Independent Agency) Ranking (Note; the data below is an approximation of the 2400 agents) Agent - Revenue - GP% - Retention - Sales Growth - Ranking Factor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ustomer Differentiators The next step was to determine what characteristics statistically differentiated the best customers from all others. The team brainstormed all possible ways to segment customers. There were 72 different possible classifications. Three characteristics were common (based on statistical testing) amongst the best. These were: Did not already sell insurance Had a Business Plan Were in business for 5 - 10 years Results Instead of treating all customers equally, or rewarding sales agencies with high sales, but no growth, this company differentiated how they allocated sales resources to existing customers and prospects. Sales strategies were developed based on the ranking. Different ranks required different action plans to achieve improvement. Following the analysis, they recruited insurance agencies that were similar to the high performers, trained them to match the business techniques that were used by the high performers and provided marketing support that was most highly utilized by the high performers. Six months following the implementation of this project, this Insurance Company's earnings grew by over 26%. For more detailed information about this subject go to http://www.supplyvelocity.com/ for our white papers. Article Source: http://ezinearticles.com/?expert=Mitch_Millstein