Sales Forecasting Made Smarter - How AI Improves Data Accuracy and Rep Accountability

October 23, 2019 | 4 minute read
Michelle Brusyo
Director, Product Management, Oracle Sales
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In this five-part series, Sales Tools Made Smarter, we'll explore how advances in sales tool technology are driving today's planning and performance management for leading sales professionals. Part one examines new considerations and requirements for successful sales forecasting.

When Q1 hits, the pressure is on for sales teams to work toward their goals. It is on sales operations and leadership to use historical and current data to establish reasonable quotas. There’s a science to creating goals that are realistic, yet motivating, especially as market trends emerge and demand fluctuates more rapidly.

But the reality is, 71% of companies don’t have their compensation plans, territories, and quotas ready on day one of their fiscal years, according to WorldAtWork! In fact, it can take months to produce these plans, leaving sales teams stalled and frustrated.

Sales ops leaders need a better, smarter way to identify their goals and priorities, and communicate them throughout the organization. Moreover, they must adopt better tools and processes to gauge how reps are performing and effectively refine quotas based on market, territory, and team shifts.

What’s Veering Sales Organizations Off Course?

The tools that sales ops have in place for tracking budget, headcount, territory, quota attainment and pipeline often fall short. Three common pain points that set sales organizations off course are:

  1. Culture: Given the performance-driven nature of sales, reps are always thinking about their quotas. This makes shifting direction and focus extremely difficult because they’re still using traditional tools and tactics to track their progress. Another, more significant cultural issue at play is that reps have a survival instinct to protect their data, born from mistrust due to deal and contact theft. As a result, they are far less likely to share updated contact and deal information with the broader team.
  2. Manual, disparate processes: Given the deep-rooted cultural issues that plague some sales organizations, reps are far more likely to jot down notes in a notebook or use their own private spreadsheet to track opportunities. Disconnected data, disparate tools and apps permeate the sales organization, prohibiting leadership from having a centralized, real-time view of performance and buyer engagement throughout the entire sales process.
  3. “Shallow” data: Over-reliance on different systems leads to a significant data accuracy issue. Opportunities aren’t updated in an accurate or timely fashion. Since sales organizations still rely on pipeline data to develop forecasts, that data is inherently inaccurate because reps largely use their gut instinct to determine whether a deal will actually close. Think about how many times sales reps have noted that a deal will close “any day now.” That day typically never comes because buyers are considering several solutions at the same time. Five reps at five different companies may think this buyer is likely to close, but only one can win the deal. These false projections lead to inaccurate forecasts and unmet quotas.

AI to the Rescue

Artificial intelligence (AI) can help sales ops develop more accurate and actionable forecasts. Using machine learning, forecasting technology can update forecasts based on specific behaviors or “red flags.” For example, if a deal is pushed several times, the system may indicate that it’s unlikely to close and remove it from the forecast. That way, leadership and sales won’t be thrown off if it falls through. 

Additionally, an AI-powered forecasting solution can offer more in-depth planning capabilities. It can integrate with ERP, HR, and financial data, so executive and sales leadership can predict how the organization is likely to perform by rep, product, and territory. These more robust reports can reinforce priorities, empower sales to change direction, or provide valuable insights that will enable other areas of the organization to contribute. For instance, if sales are lagging in a specific territory, marketing and sales can collaborate to implement more targeted advertising and content campaigns to help generate interest and fill the pipeline. Or, sales and customer success reps can align to identify clients that are due for renewals and use data to have informed conversations that will drive cross-sells and up-sells.

Perhaps most importantly, AI can help improve organizational alignment and rep performance. Real-time forecasting insights keep everyone on the same page. Executive leadership has transparency into actual performance and up-to-date forecasts, so they can see how the business is really doing. This creates a clear call-to-action for sales to stay on task and conduct the appropriate follow-ups with prospects in the pipeline. After all, even deals they’re “sure” are going close only really have a 20% to 25% chance of closing. If opportunities fall through—and they will—sales has the opportunity to engage other areas of the business (marketing, customer success, etc.) and develop an actionable plan for achieving their goals.

Better Forecasts, Better Performance

There are many solutions that aim to help businesses improve the quality and accuracy of their forecasts. However, they’re typically using pipeline data to fuel their AI predictions. As we noted earlier, relying solely on pipeline data to develop forecasts is extremely problematic and can lead to larger issues for your business.

There is a better option available. Oracle helps sales teams sell smarter, using Predictive Planning & Performance Management that combines historical, trending, and predictive analysis. These insights empower your sales organization to evolve from outdated, intuition-based planning to data-centric processes that create more accurate territory plans and quota models. Learn how Oracle can help you harness the power of AI and embedded customer data management to improve data quality across planning, incentives, quotas, and territories—and, in turn, optimize sales performance as new market trends and opportunities emerge.

Click here to learn more about Oracle Sales Planning and Performance Management.

Michelle Brusyo

Director, Product Management, Oracle Sales

As GTM Strategist for the Oracle Sales portfolio, Michelle Brusyo leads a team focused on the trends, challenges, opportunities, and innovations that drive one of the most crucial roles in business – sales.

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