The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Company Leaders
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Overview Sales forecasting is a science and an art. It is the combination of information and metrics, intuition and best practices. However, sales forecasting is most commonly associated to the standard grading methodology of the particular customer relationship system that is being used (Salesforce.com, Oracle, Microsoft, etc.). In reality, how do key sales leaders become high performing accurate sales forecasters? In addition, how do companies effectively utilize sales forecasting information to increase overall organizational performance? Here’s what we’ll discuss in this session: State-of-the-art forecasting strategies, best practices, and key metrics The interconnection between product complexity, company lifecycle stage, and accurate forecasting Mitigating downside risk and triangulation strategies to determine the truth Deal inspection and vetting sales rep forecasts The different types of sales forecasters; exaggerators, sandbaggers, and Heavy Hitters The difference between snapshot, intra-department, and inter-department sales forecasting
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The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Company Leaders
- 1. The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Company Leaders
- 2. 2 Please send questions using the online interface Attendees muted upon entry Webinar Notes
- 3. 3 Featured Speakers Steve Martin Author, HBR Contributor & Thought Leader in Technology Sales Brian McCarthy Vice President Sales Birst
- 4. 4 Agenda Birst Overview of Sales Forecasting The Art and Science of Sales Forecasting Demo Q&A
- 6. 6 Improving sales forecasting requires advanced analysis – across multitude of areas Historical Rates average win rates based on opportunity stage and days into the quarter Rep Performance hiring cohort, territory, ramped status, tenure, etc. Upsells customer satisfaction levels, product, sales channel, etc. Deal Characteristics buyer activity, industry, compelling events, movement, competitor, etc.
- 7. 7 ... and data from multiple sources, analyzed over time and in context of different business roles VP Sales Sales Managers Sales Reps CFO VP Marketing VP HR VP of Services / Support Customer Success Management / Rep Forecast Booking per Product Discounts Ratio to Deal Size Compelling Events Buyer Behavior % of Quota Achieved Deals Won vs. Competition Birst Cloud BI and Analytics • White space analysis, upsell, … • Pipeline movement, velocity, … • Rep performance on forecast, ….• Deal Scoring by buyer behavior, events, competition, …
- 8. 8 Steve W. Martin’s slides
- 9. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent About Steve W. Martin… Sales Training Win-Loss Analysis and Sales Effectiveness Consulting Sales Performance Research www.stevewmartin.com Heavy Hitter Book Series
- 10. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Sales Forecasting Challenges Salesperson Company MacroCustomer
- 11. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Sales Cycle Complexity Forecasting Challenges Lower Complexity Higher Complexity Point-Specific Sales Platform Based Sales Enterprise Sales Forecasting Complexity
- 12. ForecastingForecasting From the SalespersonFrom the Salesperson PerspectivePerspective
- 13. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Sales Research High Performing Salespeople Research Forecasting Research
- 14. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent The Sales Process Network Communications Company Advertising Agency Services CompanySoftware Company
- 15. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent What is the Forecast? Sales Rep Perspective Unqualified Prospect Initial Communication First Call Develop Solution Present Solution Customer Evaluation Present Proposal Verbal Commitment Negotiation Contract Process Signed Contracts Sales Process Weighting Factor 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
- 16. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Take the Test: Sandbaggers, Heavy Hitters, and Exaggerators Which of these statements describes your forecasting philosophy best: A) I prefer to under-commit and then over deliver results B) I constantly analyze my forecast and strive for perfection C) I sometimes tend to be a little too optimistic 25% 56% 19%
- 17. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Optimism Versus Pessimism
- 18. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Forecasting Research At the end of the past two quarters, my forecast was: 3/31 12/31 11% 8% Significantly lower than the actual revenue number 22% 15% Slightly lower than the actual revenue number 41% 44% Very close to the actual revenue number 22% 25% Slightly above the actual revenue number 4% 8% Significantly above the actual revenue number
- 19. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Forecasting Research 26 - 50 Hours 50+ Hours 22% 8% 32% 38% 11 – 25 Hours 1 – 10 Hours How many hours do you spend calculating, revising, and confirming your forecast during the quarter?
- 20. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent High Performing Salespeople Research 0 20 40 60 80 Salespeople <75% Salespeople 100%+ Salespeople <75% Salespeople 100%+ Salespeople <75% Salespeople 100%+ What describes your use of internal systems? I am a power user who takes full advantage of my company’s technology and internal systems I am knowledgeable about my company’s internal systems and use them frequently I only use our company’s technology and internal systems because I have to Percentage of responses
- 21. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Forecasting Research Rate how accurate your revenue prediction is at these moments on a scale of 1 (low accuracy) to 5 (high accuracy) Day 30 Day 60 Day 75 Day 90
- 22. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Forecasting Research
- 23. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Product Fit Questions Standard Business Qualification Questions Standard Questions About Selection Process Formal and Intuitive Qualification Product Fit Questions Standard Business Qualification Questions Standard Questions About Selection Process Specifications Features & Functions Business Benefits ROI Information Presented Information Gathered Via Formal Qualification Triangulation Techniques Salesperson Intuition Sales Cycle Patterns Personal Relationships and Internal Coaches Information Uncovered Intuitive Qualification Biases & Favored Vendor Personal Agendas Standing in Account Competitor’s Actions What to do Next and What to Watch Out For Techniques for Intuitive Qualification The Logic of Selling The Human Nature of Selling
- 24. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Forecasting Research My forecast is based upon ____% Logic and ___ % Intuition 20% Logic - 80% Intuition 30% Logic - 70% Intuition 40% Logic - 60% Intuition 50% Logic - 50% Intuition 60% Logic - 40% Intuition 70% Logic - 30% Intuition 80% Logic - 20% Intuition 90% Logic - 10% Intuition 100% Logic
- 25. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent High Performing Salespeople Research How many years have you been in sales? Over the course of my career, I estimate that I have made the quota I was assigned ___ % of time
- 26. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent High Performing Salespeople Research 0 10 20 30 40 50 60 Salespeople <75% Salespeople 100%+ Salespeople <75% Salespeople 100%+ Salespeople <75% Salespeople 100%+ Salespeople <75% Salespeople 100%+Daily – all the time Frequently – multiple times a week Once in a while – once or twice a week Infrequently - a few times every couple of weeks or month Percentage of responses How often are you in contact with your sales manager?
- 27. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Research: High Performing Salespeople Most Important Least Important
- 28. ForecastingForecasting From the SalesFrom the Sales ManagementManagement PerspectivePerspective
- 29. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent High Performing Sales Organization Research
- 30. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Forecasting Types: Intra-Department Forecasting
- 31. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent 0 5 10 15 20 25 30 35 40 45 Underperforming Average High-performing Underperforming Average High-performing Underperforming Average High-performing Underperforming Average High-performing Underperforming Average High-performing Nonexistent Well-documented (written) Closely monitored Informal Strictly enforced Percentage of responses How Structured is Your Organization’s Sales Process?
- 32. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Forecasting Type: Snapshot Forecasting
- 33. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent At your Organization, Salespeople are Consistently Measured Against their Quota and Held Accountable 0 10 20 30 40 50 Underperforming Average High-performing Underperforming Average High-performing Underperforming Average High-performing Underperforming Average High-performing Underperforming Average High-performing Strongly agree Neither agree nor disagree Disagree Strongly disagree Agree Percentage of responses
- 34. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Forecasting Type: Inter-department
- 35. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Deal Inspection: Measuring Account Control Rapport Low High High Low Deal Information Competitive Competitive Account Control Blind
- 36. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent When the Purchase Decision is Actually Made “The company that we were leaning toward at the beginning came out on top.” “There was a company that I liked at the beginning and we were just not going to give it to them. So we went through the whole procedure making sure all the boxes were checked off by a panel of people.” “Our favorite came through.” “It was down to the wire, the other vendor had equally much experience and similar capability.” “Based on a number of factors, yes, we had a favorite vendor going in and they won.” “It became apparent quickly that it would be a two horse race.” When did you realize what solution you Wanted to buy? Early in the Sales cycle In the middle of the Sales cycle At the end of the Sales cycle 30% 25% 45% Win-Loss Analysis Comments
- 37. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent High Performing Salespeople Research 0 10 20 30 40 50 60 70 Salespeople <75% Salespeople 100%+ Salespeople <75% Salespeople 100%+ Salespeople <75% Salespeople 100%+ When working on a new account, when are you likely to lose during the sales cycle? Early in the sales cycle Middle of the sales cycle Near the end of the sales cycle Percentage of responses
- 38. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Win-Loss Research – Turning Point Recognition Time Investment CustomerCommitmenttoSolution
- 39. www.stevewmartin.comSteve W. Martin Copyright 2015 © May not be copied without written consent Final Advice… Salesperson Too Nebulous Too Granular Your Sales Process Forecast Amnesty Win-Loss Analysis From the Customer’s Perspective…
- 41. 41 Birst Offerings in Sales Analytics • Sales Analytics Accelerator for Salesforce – Pre-built data model, reports & dashboards • Sales Forecasting Solution • Connectors – Salesforce.com, Oracle CRM, Netsuite, SAP, Eloqua, Marketo, Google Analytics, and many more…
- 42. 42 Demo
- 43. 43 Learn more • Learn more about Birst – www.birst.com – Live Demo: www.birst.com/livedemo Every Tue/Thu at 11 AM PT
- 44. 44 Thanks
Editor's Notes
- Everyone in sales is turning to analytics and business intelligence to do their forecasting, to understand whether they are meeting their quota, hitting their numbers or not. However, accurate forecasting depends on a lot of things. For one, you need your historical information – to apply your past win rates to opportunities in this quarter – so you need a lot of historical snapshots - but you also want to apply certain rules to your data. For example, you would only want the win rates of those opportunities that were in the same day of the quarter as your current deals. This is just step one. You also want to look at your forecast according to your per performance, and that data depends on your rep’s hiring cohort, their training, their tenure. You also want to look at your deal characteristic. For example, be able to score your deals based on the type of buyers you have, or the industry they are in, of if there is a certain competitor in the mix or whether the customer has attended a certain marketing event. Your upsell forecast depends on your customer sat scores or the products they have bought before. A lot of that data exist in a CRM system. But in reality you can not rely on only 1 source of data. Life would have been very simple if you had 1 Uber source of data. Typically there are multiple sources that you need to rely on.
- If you want to look at your current pipeline, yes, that exist in your CRM system – but the CRM system does not store your historical data. Instead you have to take a snapshot of the pipeline once a week into Excel and do some Excel kung fu to do your trend analysis. Also as we talked about it, not all your data is in your CRM system. For example, the prior purchases of your customers, the products they bought or to do white space analysis, you need to bring data from your ERP systems like SAP or NetSuite. Your marketing data, the types and quality of the leads you have, the characteristics of your deals, how active / engaged they are, is in marketing systems – like Marketo, Eloqua, Google Analytics / Omniture. Your rep performance, the background of the reps, their experience level, their hiring dates, their tenures, that information is in an HR system like Success Factors. Your comp plans – and to analyze the impact of your comp plans on sales performance, you need to bring in data from Excel or Xactly. How do you that? You need a system that allows you to bring multiple data sources together, be able to give all your users single and consistent insights, and be able to not just look at current data, but be able to analyze data based on previous snapshots. We believe that system is Birst. Birst allows you to do bring many sources together. It also automatically stores historical data and creates time series analysis on it to help you do trend analysis and see pipeline movement. It also gives you a single, trusted information set that acts as your system of record for your organization.
- So with that, let me turn the table over to our guest speaker, Steve W. Martin to share with you some best practices for doing forecasting based on your sales maturity level and product complexity.