Today’s post is by Stephen D’Angelo, president, worldwide field operations at Aviso Inc. Join him in March at the Sales 3.0 Conference, where he will present “Delivering Accurate Forecasts – How Companies Like Dell, Splunk, Zuora, and MongoDB Went from Complicated and Inaccurate Spreadsheets to an AI/Machine Learning Platform.”
As a sales leader, wouldn’t it be useful for you to know if a rep, product line, or business segment is forecasted to miss the number? Wouldn’t you also be interested in knowing by how much – and what you could do about it? All while driving smart pipeline management and deal reviews?
With artificial intelligence (AI) for deal management, you can actually do all that.
The Link between Baseball and Sales Organizations
As an example, recall the bestselling book, Moneyball: The Art of Winning an Unfair Game, published in 2003 and written by Michael Lewis. There’s a reason this story became a bestseller and turned into a major movie starring Brad Pitt as Billy Beane, the major league baseball general manager. This was the fascinating tale of how major league baseball evolved from an old-fashioned, stodgy kind of business to one driven by data and statistics.
Up until the mid-1990s baseball was run by scouts, field managers, and general managers who made game execution decisions based on gut, intuition, experience, and personal bias. None of the decisions were based off of metrics like on-base percentage, total walks, slugging percentage, etc.
Fast forward to today. The most successful teams use guidance from sabermetrics, big data, and AI to complement human judgment. Analytics now drive draft picks, trades, lineups, and any other major decisions. For the latest evidence of this approach, look no further than the 2017 World Series-winning Houston Astros. They successfully transformed their team blending the latest in data analytics with great talent.
What does this have to do with running a high-performance sales organization? When it comes to key deal management processes, the majority of sales organizations operate like the old, stodgy scouts and GMs of baseball’s yesterday. Most rely on the art of the sell – using gut feel and intuition.
New Insights You Can Leverage with AI
Most sales organizations take into account very little data that shows account historical performance. They also fail to use seasonality to guide forecast management, pipeline reviews, or deal reviews. Preparing for each of these meetings can be time consuming and – with gut feeling driving decisions – leaders can’t get an accurate picture of the business.
Sure, data from CRM systems is useful, but most sales organizations have yet to adopt advanced, cloud-based technology or machine learning to assist their teams. Instead, managers ask questions of their reps, assess their truthfulness, integrate involvement with the deals, come up with a swag or confidence level of a forecast number, and predict which deals will close, for how much, and when.
Much like major league baseball moved into the future, it’s time for sales leaders to transition to leveraging the power of big data, machine learning, and AI to drive decision making for forecast management, deal reviews, and weekly sales pipeline calls. Like financial planning, supply chain management, and so many other business processes, shouldn’t sales organizations leverage machine learning and AI to create more accurate forecasts? Don’t our CEOs, CFOs, and shareholders deserve a more accurate forward-looking assessment of the business by leveraging predictions based on several quarters of data pulled from CRM and other sales systems?
I have been leading organizations and sales teams for more than 30 years and I, too, am one of those leaders that had to come to this realization and adjust. Sales organizations must stop using bulky, error-prone spreadsheets as forecasting tools or as tools to run pipeline reviews. Aviso can help you do this. Unlike CRM analytics, spreadsheets, or simple forecasting tools, our platform connects to CRM systems, snapshots data every 15 minutes, and stores it in the independent data store. We see through millions of data points to make sense of predictive signals and provide a series of accurate predictions on day one of the quarter.
In summary, here are the key things you can accomplish for your sales organization leveraging AI, analytics, and machine learning:
- Understand if you’re closing deals fast enough to hit quota – also known as “pacing.”
- Determine if your current pipeline will produce enough revenue to meet quota this quarter.
- Understand whether pipeline is being built and progressing at the proper pace to support next quarter’s number.
- Get an accurate sense of your run rate business – or the amount of revenue you can expect from deals that both open and close in-quarter.
- Receive AI-driven “Smart Selling Signals” on every deal in your pipeline to quickly identify green, yellow, and red indicators so that you can adjust execution and win more deals.
You have great talent on your team. Your sales pros are proficient at selling and negotiating. Now, you can use AI to guide your talent to better assess the likelihood deals will close – and forecast more accurately. You can also stay laser focused on deals that need immediate attention during pipeline reviews, and eliminate any prep required for deal reviews.