Managing a sales team is hard. The role of the front-line line sales manager is the lynch-pin of most sales organizations, but the number of tasks that sales managers have to juggle makes it really difficult to know how to answer the questions “How do I get the most from my sales team?” and “How do I remove uncertainty?”
Just think about all of the tasks a sales manager has to balance … hiring, enablement, sales coaching, closing deals, running the sales forecast, managing the pipeline, supporting HQ information requests, and conducting the quarterly business reviews … and that’s when she is not traveling.
Sales managers are encouraged to invest time in coaching to improve the team, or rely on sales analytics to help determine where to focus.
Even though coaching is recognized as being a true driver of sales productivity when implemented effectively, most sales managers don’t employ a consistent coaching practice in their business. In fact 73% of sales managers spend less than 5% of their time coaching.
Some don’t know how to coach, others don’t see the value and in many cases sales managers cite ‘Not enough time’ as a key reason for not engaging in this proven best practice. We think that in fact the real reason is that sales managers do not have the requisite knowledge that equips them to coach effectively and often can’t easily assess what opportunities or sellers would benefit from a coaching intervention.
The math explains this better. Let’s assume that the sales manager has eight people on her team, each working six material opportunities, and a ninety-day sales cycle. That’s 48 opportunities in her universe at any one time. Even if she tries to coach just half of these opportunities effectively each month, spending two hours per opportunity, she runs out of time pretty quickly. How is she to know where to focus? There has to be a way to triage both the opportunities and the sellers so that her time is applied where it has most impact. What matters gets lost in the volume of data or information to assimilate.
We know from studies by IBM and MIT that sales organizations are 10X more likely to be High Performers is they use analytics well. The problem however it that 55% of all analytics projects fail. Failure usually occurs because the scope of the project is too wide, there is little or no connection to business outcomes in the design of the project, and there is a deficit of business domain expertise in interpreting the analysis, linking correlations to causation and gaining actionable prescriptive insights. What mattersget lost in the metrics.
Most approaches we have seen think about data to predict sales performance in three or four buckets:
- Core Data – the data that exists in your CRM
- Situational Analytics – typically represented by reports or visualizations, this tells you what happened in the past.
- Predictive Analytics – based on patterns from the past, what is likely to happen in the future? (Lots of challenges here to differentiate between causation and correlation)
- Prescriptive Analytics – based on the predictions, what should we do about it. (Obviously is the predictions are flawed this is dangerous, and in any case unless there is considerable embedded domain expertise the value of the prescription can be questionable.)
We think there is a critical missing component, and that is Descriptive Analytics, the determination of which parts of the data actually matter. What are the big questions? What data enrichment is needed before the data can be a reliable source for prediction, and ultimately prescription.
We would suggest that a much more valuable approach would be :
- Core Data
- Situational Analytics
- Description Analytics (Big Questions)
- Predictive Analytics, and
- Prescriptive Analytics
We think the solution for the sales manager is in fact a combination of coaching and analytics, not in the classic sense of predictive analytics where big data can get in the way, but rather in metrics driven coaching, leading with the big questions for sales managers as opposed to the big data, establishing what you need to know to determine leading indicators of sales performance risk, at different levels of granularity for sales teams, individual sellers, accounts and individual opportunities.
- Where are there vulnerabilities in my forecast?
- Which deals are at risk?
- Is my pipeline truly a reflection of future business?
- How long does it take to win a deal of this type? How long does it take to lose? (Answer: The sales cycle for a losing deal is usually much longer for a losing deal. Wouldn’t it be good to flag that early?)
Think of it like this. Every sales interaction and every exchange between manager and seller should have a map to follow. The destination must be clear and there should be effective signposts along the way that can quickly identify if you are going off track.
Before you start on your sales management journey you need to know the big questions to ask. Sample big questions might be:
- What are my Must Win deals?
- Are there opportunities in my pipeline that are inactive or stalled?
- What is my actual Win Rate? (measured by dollar value, not count of opportunities)
- What happened to the deals John forecasted last month?
- Are we losing deals late in the sales cycle?
- What is the difference between our performance for qualified opportunities (deals that get to stage two or three in the funnel) and all opportunities.
Once you have figured out the big questions and the signposts that point to the answer then you can easily apply some smart automation to identify the entities on which you should focus.
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Donal Daly is Executive Chairman of Altify having founded the company in 2005. He is author of numerous books and ebooks including the Amazon #1 Best-sellers Account Planning in Salesforce and Tomorrow | Today: How AI Impacts How We Work, Live, and Think. Altify is Donal’s fifth global business enterprise.