I love to live in the world of data. There are not many things that can track the impact of information and behavior the way that data mining and analytics can. As this is my first contribution in this format, I wanted to write a general resource for how I manage a large sales team by balancing a creative approach with deep analytical data.
One thing that anyone who works with me will tell you is that I know my numbers. Thanks to a fully customized version of Salesforce.com and a few other metric tracking applications, I can paint a very clear picture of where my team has been, where we are today and where we are headed in the future. Below I will detail the major categories where I crunch data to measure job performance, skill level, business growth and efficiency:
The expectation of a sales professional on my team is to meet a minimum threshold of metric requirements. Those requirements include outbound calls, quotes generated and a revenue and gross profit quota (among other things). Establishing the baseline for these expectations required a lot of due diligence. In a standard eight hour work day that should be split efficiently into blocks of time for making calls, building quotes and doing administrative work; how much time and effort should be devoted to each of these things? For instance, if a sales rep spends all day on the phone then they will get behind on quotes and closed deals that need to be written up and processed.
First a baseline has to be established. How long does an average call last? How long does it take to generate a quote? For each closed won deal, how long does it take to process that order?
Once that information has been established then the expectation can be placed on the rep with confidence. I can defend any metric expectation with the data behind it. In this case, the average call was 2 minutes long. It takes 15 minutes to generate a quote. Now that the CRM has been customized and automated it takes 5 minutes to process the order and transcribe all pertinent notes into Salesforce.com. Because I ask the team to be creative and strive to build long lasting relationships, the metric requirement is not as aggressive as the quota requirement.
The team is asked to make 50 outbound calls a day, generate 5 quotes and spend no more than 2 hours a day on administrative work. Of course all of these metrics are minimum requirements because in an eight hour work day, much more work than this can be done. If a rep makes more than 50 calls, generates more than 5 quotes and manages to stay ahead of their daily pace to achieve quota, that rep is generally very successful. If a rep struggles to meet the minimum requirements, coaching is needed to help them understand the importance of meeting the metrics and efficient time management skills.
Once a rep has a handle on their metric responsibilities, we move on to pipeline management skills. The pipeline consists of all levels of interactions with prospects and clients that move in the direction of generating new revenue for the company. The pipeline assigns a value and a projected closed date to every opportunity which paints a picture that can be broken down from annual revenue to daily expected revenue.
The strongest reps on the team have a pipeline that is at least three times the amount of their targeted quota. Accelerating the pipeline beyond that size allows for a greater chance of achieving accelerated goals such as quarterly bonuses. If a rep closes 10 opportunities a day on average, there should be at least 30 opportunities in the pipeline for that day.
The way I like to break down the pipeline is into prospects (which should have a dedicated time to be called each work day), recurring buyers (who should have an established pattern) and opportunities to expand existing business. We work in a recurring model in an inside sales organization. That means our active client base buys from us repeatedly and the sales reps must maintain that business while looking for ways to grow and expand it. Managing a large territory of existing business requires much more pipeline detail. Predictive buying patterns are established over time and that raises the expectation level of providing exemplary service.
One universal sales tool is the closing ratio. Over the course of time quotes are tracked to measure the time table and closing ratio. A rep with a high skill level has a high closing ratio. A rep who puts out a large number of quotes but does not close them has a lower ratio and requires coaching on either when it is appropriate to quote a prospect or on using closing tools for earning the business.
I generally take the numbers from one month to a quarter and generate a report on closing ratios as a team and then for each individual. I assess the team in this way so that I can rank them against each other and against the team average. Then I am able to leverage the skill sets of the best closers to help train and motivate the other members of the team to reach at least the status quo.
Average deal size and gross profit are two of the most important pieces of data I need access to in order to best do my job. The size of an average deal is very telling in the types of business that are being won and how aggressive each sales rep is when closing business in their territory. A rep whose average deal size is well below the average of the team is likely leaving a lot of money on the table.
Reps who have the largest average deals have often found creative or persuasive ways of bundling products and are more successful at expanding business within their territory.
Gross profit is the bottom line of everything we are hoping to achieve as a sales organization. Gross profit is what my company walks away from the deal with and reps who have very low gross profit margins are too often selling on price instead of the myriad of other professional sales tactics that they have been taught.
Understanding each territory and the gross profit margin that they are capable of as well as putting together a plan for growth is how a rep achieves year over year success in sales. If the gross profit is below expectation, an action plan can be put together using specific data. A rep can bundle the products so that if some have a low margin, there are higher margin products that can be built into the deal to balance the overall margin. With an understanding of cost, price point, competitor pricing and profit expectation; a plan can be developed for hitting any specific goal.
Time management was addressed briefly in the metric expectations portion, but it is something that can be effectively broken down like any other data. Hours of the day can be analyzed. What is the most effective time to be on the phone with clients? Which hours of the day are best to be off the phone to work on quotes and processing orders? What is the balance of time spent on and off the phone to achieve specific daily revenue goals? What is the cost of the rep by shifting in and out of each mode?
These questions can all be answered by reviewing the data provided by 90 days of work and research. On a team of 12 reps making calls into a specific time zone, we can track when the most actual phone connections are made (which has generally been found to be early in the morning and late in the afternoon with plenty of exceptions based on vertical markets). We can also track when the reps are the most productive during the day. Do they require 2 cups of coffee to get started? Do they run out of steam before the end of the day because of the energy they expend on the phone?
Once all of these questions have been answered, the data can be reviewed and some general conclusions can be made. After 90 days, I put together a “suggested” time management schedule setting up call blocks, prospecting hours and administrative time. After each quarter, this schedule can be reevaluated and then enhanced based on the success (of lack thereof) of each member of the sales team.
This is my basic approach to using analytics and data to build a plan for success for each member of my sales team. They understand the expectations and that their work is being examined in order to constantly evolve our processes for higher efficiency and stronger performances.