Becoming a Predictive Sales Organization: Best Practices from the C9 Community

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Becoming a Predictive Sales Organization • 2

Table of Contents

Patrick Hurley | General Manager of the Americas, Acronis

Lars Nilsson | VP Field Operations, CloudEra

Loren Alhadeff | VP Corporate Sales, DocuSign

Mark Goode | SVP Global Sales, DSI

Joe Dillon | Director of Sales, eVault

Steve Rutledge | VP Global Sales Operations, Genesys

Jeanne DeWitt | Director of Enterprise SMB Sales for the Americas, Google

Vikas Bhambri | VP Global Sales Consulting and Sales Productivity, LivePerson

Bill Kiedaisch | Director Global Sales Analytics and Opportunity Management, Pitney Bowes

Patrick O’Leary | Senior Director of Strategy and Operations, Yahoo

Contributors

Introduction: The Emergence of the Predictive Sales Organizations � � � � � � � � � � � � � � � � � � � � � � � � � 3The Predictive Sales Process � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 4

Quarterly Business Review: Better Outcomes with Less Effort � � � � � � � � � � � � � � � � � � � � � � � � � � � 4Pipeline Review: The Spine of the Predictive Sales Process � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 6Forecast Meeting: Seamless Outcome of a Healthy Pipeline � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 7Coaching for Continuous Improvement � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 9

The People: Reactive vs� Predictive � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �11The Sales Executive � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �11The Sales Manager � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �12The Sales Representative � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �13

Summary: The Predictive Sales Organization � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �14About Our 6-Part eBook Series Contributors � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �15About C9 � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �16

Becoming a Predictive Sales Organization • 3

Two decades ago, companies started to embrace Sales Force Automation (SFA) as a key means of standardizing sales process. As a result of this effort, many sales organizations were able to more rigorously define the ideal selling motion, centralize data related to the selling effort and streamline and automate various parts of the sales cycle.

Despite these benefits, most companies continue to struggle with fundamental sales challenges in the areas of sales productivity, quota attainment and forecast accuracy. Consider the findings of CSO Insights:

• The amount of time sales reps spend engaged in customer-facing selling activities has declined from 47% in 1998 to 37% in 2013.

• Only 63% of sales reps met or exceeded quota in 2011 and 2012. This number has dropped to 58% in 2013.

• In 2013, 46.5% of forecasted deals actually close as predicted.

What savvy sales leaders have come to recognize is that sales processes are notoriously difficult to automate and measure since they depend on highly dynamic variables ranging from fluctuations in the economy to the psychology of sellers, buyers and competitors. Conventional sales organizations built on rigid sales processes and static systems don’t manage this variability well. They attempt to drive future performance by enforcing inflexible process based on past results. But when the past doesn’t repeat itself (and it typically doesn’t) inefficiencies and uncertain outcomes are an inevitable result.

In the wake of these revelations, a new type of sales organization is emerging. Known as the “Predictive Sales Organization,” it more effectively manages uncertainty by leveraging the power of big data and predictive analytics. Like its predecessor, the Predictive Sales Organization is process-based; but it’s also much better equipped to identify emerging patterns and adapt processes accordingly. To do so, it synthesizes real-time signals from multiple data sources to construct a panoramic view of revenue progression across Sales, Marketing, Service and Finance. Armed with this broad perspective, it can better understand revenue trajectory, anticipate the most probable outcomes, and make real time modifications to process and behavior to capitalize on emerging opportunities while mitigating evolving risk.

Currently C9 is engaged with hundreds of the world’s most successful companies to equip their sales teams with predictive sales capabilities. In the process, we’ve collected data and stories that describe how Predictive Sales Organizations operate. This eBook distills the best thinking on the subject. It’s divided into two major sections. The first describes how the leaders of predictive sales organizations view their roles differently than conventional sales leaders do. The second section describes the way these leaders have operationalized the use of predictive insights in their regular meeting cadence to adjust strategy, modify behavior on the fly, and achieve better, more predictable results.

Most, but not all of the participants in this eBook are C9 customers. But each is innovating the discipline of sales and each acknowledges the fundamental role that predictive analytics plays in that innovation.

Introduction: The Emergence of the Predictive Sales Organizations

Becoming a Predictive Sales Organization • 4

The Predictive Sales ProcessSales organizations manage their process by a set of routine meetings held at different levels in the organization and at different cadences. In this respect, there is little difference between a conventional and a predictive sales organization. Both will have forecast calls, pipeline reviews, and quarterly (or bi-annual) operating meetings. However the format, content and potentially even cadence of these meetings are frequently very different between a conventional and predictive sales organization.

Quarterly Business Review: Better Outcomes with Less EffortOperating reviews (often conducted quarterly and abbreviated as “QBRs”) are intended to help sales leaders review performance against the annual plan and create action plans to close gaps or adjust targets. In a conventional organization, the QBR is a preparation-intensive meeting that pulls team members out of their selling motion for days or even weeks at a time. Furthermore, meeting discussion is typically spent on review and validation of results, rather than actionable outcomes. Although meeting organizers might well have good intentions, the goal of driving discussion to discrete actions is very difficult to achieve.

Joe Dillon describes a QBR approach embraced by many organizations he’s observed, “Many companies do very detailed quarterly business reviews that require individuals to put together a plan that is then amalgamated into a team plan. This then gets rolled up to a regional plan and then all the regional guys fly to one place and talk through all this stuff. In my mind this is less effective because you end up with a week of regurgitating a lot of information that’s already known followed by 12 weeks of the salespeople ignoring the outcomes and going off and doing their own thing.”

A predictive organization spends less time preparing for meetings and less time reviewing results in the meeting, because they have been tracking key measures all along. Participants always have access to precise forward-looking

performance indicators and an ability to pivot across multiple perspectives of the organization. As a result, time spent in QBRs can be dedicated to training, sharing best practices, and collaborating.

Trusting the NumbersIn a conventional sales organization, particularly one with less mature processes and data environments, people spend considerable time assembling data and discussing territory reviews during the QBR. Even in organizations that invest heavily in weekly reporting, leaders might see the operational review as a means for getting the “real story” behind the numbers. This is usually because “the numbers” they see in their reports are too late, too high-level, or just not believable because they fail to link to live data.

Becoming a Predictive Sales Organization • 5

In a Predictive Sales Organization, sales reps engage in data-driven discussions throughout the quarter. Accordingly, when it comes time to do operating reviews, there is no mad scramble to update opportunities. Similarly, sales managers don’t need to make last-second requests of sales operations for trend analysis, year-over-year comparisons, or stack-ranks of rep performance. Preparing the data is as simple as opening a dashboard. Mark Goode, SVP of Sales and Marketing at DSI Global explains, “Generally, we don’t spend too much time on the numbers during the QBR because we talk about them on a weekly basis during pipeline calls. Instead, we make sure that these business reviews provide a collaborative environment where we’re able to identify the activities that will ensure that upcoming quarters and years are successful. Numbers are important and necessary but they are only as good as the action they drive.”

More Precise ProjectionsConventional sales projections often lack objectivity and credibility. They are based on what individual reps aspire to achieve and how well their managers are able to discern truth from fiction.

Advanced technology is capable of fine-grained segmentation, which enables probabilistic analysis on every deal in a pipeline. When reps and managers are able to discuss future outcomes in terms of probability, rather than aspirations, projections become more precise, more believable, and more actionable.

Vikas Bhambri describes the benefit of scoring 100,000 accounts based on a probabilistic model designed to fit each of their core target verticals. “It helps us define which market segment they belong in, but more importantly, it helps us understand how we want to prioritize going after them and what resources we want to use.”

Smarter, Faster Resource AllocationsIn a conventional sales organization, leaders allocate resources annually, during a many-month planning ritual that involves every corner of an organization. Because of the cost and complexity of aligning resources across regions, lines of business, and channels, it is difficult to change these plans throughout the course of a year.

Predictive Sales Organizations strive to downplay annual planning cycles in favor of more agile and continuous planning throughout the year. They use modern technology that makes it easier test scenarios, forecast outcomes, and track results across dimensions of the business before rolling them out. With more confidence in the changes they want to make, resources can be realigned during the course of the year. While mid-year adjustments have been relatively common for some time, quarterly and even more frequent resource changes are become commonplace. At DSI Global for example, Mark Goode and his team were able to increase agility in this way: “What we used to do on an annual basis, we now do on a quarterly, or even weekly basis,” says Goode.

Quarterly Business Review CONVENTIONAL PREDICTIVE

Preparation Disruptive Continuous ■ Update CRM ■ Live Dashboard ■ Extract to XLS ■ Drill-down to Data ■ Summarize in PPT Projections Aspirational Probabilistic ■ Scenario-based

Resource Static, Single Dimension Dynamic, Multi-DimensionalAllocation ■ Geography or ■ Geography and ■ LOB or ■ LOB and ■ Channel ■ Channel

Discussion and “Rear-View Mirror” “Forward-Looking”Outcomes ■ Territory Review ■ Territory Plan ■ Root-Cause Analysis ■ Marketing Plan ■ Top 3 Account Plans ■ Sales Training

Becoming a Predictive Sales Organization • 6

Pipeline Review: The Spine of the Predictive Sales Process The term “Pipeline Review” means different things at different levels of an organization. For the front-lines, the pipeline call is a weekly discussion between a manager and one or more reps about key deals and the health of the pipeline. For the executives, a pipeline review is a less frequent (often monthly) discussion about pipeline trends and broader implications for the forecast.

The conventional pipeline meeting is typically light on metrics and often devolves into discussions of a few specific deals, guided by the interests of the meeting leader. Meanwhile, a predictive sales organization uses detailed metrics to structure the meeting and focus discussion on the highest priority activities. Pipeline metrics that complement the experience and judgment of the sales team can transform a pipeline review and deeply impact the effectiveness of the sales organization.

Overall Health Index

The most advanced predictive sales organizations use a composite index to gauge quality and health of the pipeline. The pipeline health index informs forecast confidence and is factored into sales rep performance evaluations, MBOs, and commissions. Indexes consider metrics above and beyond size of pipeline. Steve Rutledge refers to the pipeline categories in use at Genesys as “the Four V’s: Volume, Variety, Viability and Velocity.” He explains, “What started off as an experiment has now become a framework that helps us be more comprehensive and sophisticated in our pipeline reviews.” Other leaders have developed similar frameworks: Common across them all are notions of composition, velocity, and probability … in addition to size.

Composition of PipelineA healthy pipeline, much like an investment portfolio, should contain a mix of opportunity types. Rutledge explains, “We have five main products and we want to know if our people’s pipelines have a decent amount of activity across all of these products. We’re also looking for situations where reps are systematically ignoring certain products.” Building a pipeline with a range of products and customers minimizes risks that a single offering could become more difficult to sell because of increased competition or reduced demand. It’s also important that a pipeline be optimized for deal size. Success shouldn’t be too dependent on a few huge deals or too many small deals.

Pipeline VelocityThe rate of change in opportunities is a powerful indicator of risk in the pipeline. Leaders know how on-track deals behave, and they are constantly evaluating deals to determine which are sidetracked. For example, they know typical time per stage and they know which people are needed from the customer to get through certain stages. Good sales managers in conventional organizations rely on their experience and intuition to ferret out these indicators and manage accordingly.

In a predictive organization, deals that aren’t tracking are automatically flagged by analysis systems. An automated approach is especially critical in organizations where sales managers track the progression of hundreds or

Becoming a Predictive Sales Organization • 7

thousands of deals. Jeanne DeWitte, Director of Enterprise Sales at Google, works with a sales team that manages hundreds of opportunities at a time. “When you have 200 opportunities you can’t just memorize all of them, so that’s where the software comes in. We do a lot of predictive modeling. That helps us figure out where someone sits in the buying process. We can also track how quickly they are moving through the pipeline and use this information to prioritize which deals we focus on.”

Probability of CloseManagers know that the best deals exhibit a balance of give and take between the prospect and the sales team. They know that when deals are repeatedly pushed, or when their value is frequently changed, they are also less likely to close. Patrick Hurley, GM Americas of Acronis, describes their recipe: “If an opportunity is above a certain age or opportunities are being pushed more than two or three times, we know that it has a very low likelihood of actually closing.”

It is very difficult for managers to know and keep track of all these indicators, though. In predictive organizations, software tracks known indicators, and machine learning can be used to identify new indicators. Indicators are analyzed to provide an objective probability of a given deal closing. Sales managers can use this information to more effectively steer energy to the highest probability deals.

Combining Art and ScienceIn a predictive sales organization, experience and intuition are still valuable

— in fact, machine-generated probabilities are compared to personal assessments filled out by reps and managers. Where there are discrepancies, leaders have an opportunity to probe. In some cases, a predictive score might be a better indicator of reality. In others, a rep’s judgment might be better. What matters is the contrast and subsequent questioning that brings more understanding.

Mark Goode explains: “You take one’s personal opinion and you combine it with the facts offered up by data scoring; that’s where art and science really

come together. There’s no substitute for the experience a veteran sales professional brings to the table. But when you combine perspective with data, that’s when you hit the home run.”

Forecast Meeting: Seamless Outcome of a Healthy PipelineIn a conventional sales organization, pipeline reviews and forecast calls tend to be redundant—rehashing the same details regarding the sales team’s favorite opportunities. In predictive sales organizations, the forecast call is distinct from the pipeline call and its explicit purpose is to put teams on record for committing to a number. Everyone from the team is on the call so that collectively the team understands how they are tracking and are motivated to deliver.

A lot is at stake in a forecast meeting. Inaccurate forecasts can not only lead to bad decisions, but reps and managers can also gain or lose huge amounts of credibility based on the accuracy of their “call.” As Joe Dillon says, “It’s pretty painful for a person when the forecast he’s been defending all quarter doesn’t come to fruition—it often triggers performance improvement plans and termination.” Given the criticality of delivering an accurate forecast, predictive organizations seek out tools that ensure precision.

Pipeline Review CONVENTIONAL PREDICTIVE

Measures ■ Coverage Ratio ■ Coverage Ration by stage ■ Velocity ■ Objective Probability ■ Growth Trend ■ Year-over-Year Compare

Discussion Why did that deal push? Where is the risk? How to close the big deal? What are the highest value activities?

Becoming a Predictive Sales Organization • 8

Defined Forecast CriteriaPredictive sales organizations take great care to clearly define criteria that help sales people decide what should be “committed” to the forecast and what should be designated as “upside.” Conventional organizations might have well defined forecast criteria, but their systems often don’t contain all the key data required to quickly make forecast determinations. As a result, criteria are not rigorously considered.

Predictive organizations track and measure detailed criteria to remove ambiguity from the process. Dillon explains, “We have the checklist in our CRM that systematically walks you through every question you need to ask yourself as you are forecasting.” This type of discipline helps individual reps benefit from clear understanding of process and how their performance is to be measured. The organization benefits from more consistent performance across groups and time periods.

A Streamlined Roll-upConventional organizations require considerable manual intervention to aggregate individual rep forecasts into company numbers. These organizations often don’t have suitable technology platforms. They rely on spreadsheets, email, and analysts to collate results. Some conventional organizations have forecasting systems, but they can’t use them effectively because reps don’t keep their opportunity records updated. One manager commented, “We want to be all in the system, but we haven’t gotten there yet. Because we still [forecast] with spreadsheets, it would be too onerous to generate new forecast on a weekly basis. That’s a problem we need to address.”

In a predictive organization, the forecasting process is streamlined such that an entire organization can roll up “the call” in a matter of hours. Leaders are confident that numbers are accurate and reflect the latest developments in the business. Yahoo is a great case in point: Patrick O’Leary, Senior Director of Sales Operations and Effectiveness, observes that since Yahoo has been able to automate the roll up process, their world-wide organization can submit a comprehensive forecast in a single morning.

Bill Kiedaisch from Pitney Bowes offers another secret to rolling the forecast up quickly and efficiently—rigorously scrub the pipeline first. “If you get the pipeline right, the forecast naturally follows,” he says. “Every other week our CEO, CFO and BU heads meet to dig into the pipeline and then every Tuesday a package goes out to all of the sales execs and finance that shows how we’re trending and where we think we’ll land.”

One Data Set with Multiple PerspectivesConventional forecasts that are manually collated typically focus on one perspective of the business. For example, the forecast might show a regional perspective that works well for sales but doesn’t serve product teams, industry business units, and other groups. These other groups need to cut data along different dimensions.

Becoming a Predictive Sales Organization • 9

A predictive forecast can be pivoted along multiple dimensions based on the distinct needs of a varied audience. For example, deals can be aggregated by account, product, geography, or industry and viewed in terms of count, revenue or margin. The ability to roll up sales forecasts and then instantly pivot the data eliminates the need to manual curate a host of spreadsheets. Companies save time and resources and achieve much better alignment among organizations when everyone’s using a common forecast to drive decisions.

A sales leader describes his process for rolling up a multi-dimensional forecast in a real-time system: “[We] are able to break it down by opportunity, by region, by product, etc. We validate what’s in there and then we are able to capture what is a commit, an upside number, and a best-case number. Then we flag specific deals that have significant impact to the number for the month.”

Seeing the Forest AND the Trees A conventional organization is typically less concerned with getting precise roll ups of specific deals, figuring that across a large number of deals they will be right and wrong roughly equally. The overall forecast is “good enough.”

A predictive sales organization is not content with aggregate level forecasts because an aggregate forecast doesn’t help people in the field make operational decisions. They want a forecast that traces back to specific deals, and that considers a number of predictive factors such as:

• The cyclical or seasonal nature of their business

• Current state of a prospect’s business or market

• Historical forecast accuracy of individual reps

• Deal by deal pipeline behaviors

Having deal-level projections based on a variety of internal and external variables gives executives understanding of dynamics in the field and more faith in their overall forecast.

Coaching for Continuous ImprovementAs people’s expectations and relationships with work, management, and technology are evolving, best practices in performance management are also changing. Performance measurement and periodic performance reviews are cornerstones of the conventional sales organization. While necessary, they are increasingly viewed by modern workers as distracting and not designed for their own professional development or benefit. Predictive organizations recognize this evolution and are adapting technology and systems accordingly.

Behavioral Coaching Predictive sales organizations decompose selling processes into sequences of activities that depend on specific skills and aptitudes. They use machine learning to highlight behaviors that make successful reps successful and construct a skill matrix that draws explicit links between behaviors and outcomes. Patrick Hurley describes the skill matrix in use at his company: “There are numerous segments we look at in terms of phone skill and soft skill, as well as the standard metrics like dials, talk time, etc. Using this matrix we coach different tactics to set meetings and position solutions in the right way for different verticals. We need to get them past being just a keyboard operator. The matrix resonates with them, which is why we take it from assignment to assignment.”

Forecast Review CONVENTIONAL PREDICTIVE

Technology ■ Manual Roll Up ■ Automated Workflow ■ Excel and Email ■ Link to Deals ■ Aggregate Numbers ■ Real-time Pivots

Preparation ■ Ambiguous Criteria ■ Well-defined Criteria

Frequency ■ 2-6 Times per Quarter ■ On Demand

Becoming a Predictive Sales Organization • 10

Self-Assessment and Peer-FeedbackIn a conventional organization, coaching is the domain of the sales manager and is applied to struggling reps. In extreme cases, reps only get coaching after they’ve been put on a formal “development plan,” a decidedly negative event.

Predictive sales organizations espouse a different model, where everyone has room for improvement and everyone participates in skill building exercises. This change is emblematic of a broader paradigm shift from top-down hierarchical structures to collaborative work units. Joe Dillon describes how eVault uses team-based quotas and highly visible stack-ranking reports to drive the sharing of best practices within their organization: “There are 19 or 20 different metrics that are measured. And all of the sellers are stack ranked against one another across all these different metrics.” The theory is that stack ranking makes it easier to self-diagnose and seek needed help.

“And with team-based quotas a senior person may be doubling or tripling the productivity of a newer person, but they are also the mentor sitting

right beside the newer person. They care very much that that newer person becomes successful quickly, because they are dependent on that newer person’s productivity.” The sales manager’s coaching role in this type of environment is important, but the onus for improvement is spread to the wider team.

Continuous Feedback vs Review CyclesMonolithic performance review processes are disruptive to normal business operations and their impact on performance is questionable. Predictive sales organizations attempt to make small but continuous improvements to rep behavior rather than striving for radical behavioral modifications once or twice per year. Mark Goode of DSI Global explains his philosophy: “I tell all my managers, ‘Talk to your reps every day about how they are progressing deals through sales stages and the best practices they are using to do so.’ If we do that, every rep is clear on what they need to do to grow.” The most predictive organizations are experimenting with completely non-invasive, low-touch systems that identify cues generated by reps in the normal cadence of using their CRM, social, email and calendar applications.

Coaching CONVENTIONAL PREDICTIVE

Measures ■ Quota Attainment ■ Quota Attainment ■ Pipeline Health ■ Deal Management ■ Skill Development

Frequency ■ Quarterly, Bi Annual, Annual ■ Weekly/Continuous

Discussion ■ Review of Performance Gaps ■ Root Cause Analysis ■ Directed Selling Activities ■ Assign Improvement Tasks ■ Driven by Managers ■ Conducted by Peers

Becoming a Predictive Sales Organization • 11

In any organization, people drive success. Their aspirations, goals and day-to-day concerns must be reconciled with ever-shifting roadblocks to productivity and performance. In a conventional sales organization, systems and processes often contribute to the boundaries that keep people in reactive mode. The Predictive Sales Organization empowers sales executives, sales managers, sales representatives, and sales analysts to recognize when current processes fall short and to adjust as necessary to ensure the best outcomes.

Loren Alhadeff, VP of Corporate Sales at DocuSign, explains, “As we continue to grow the business, the data and analytics behind our costs and growth drivers are becoming forefront to me. Information that helps us predict potential roadblocks and obstacles ultimately allows us to eliminate them wherever possible.”

Bill Kiedaisch, Director Global Sales Analytics and Opportunity Management at Pitney Bowes, echoes these sentiments, “You need systems to provide visibility into both your short and long term business. In in both cases, you need perspective on specific actions you can take to maximize results.”

The Sales ExecutiveSales executives are faced with an increasingly global, competitive and complicated landscape that challenges them in the following new ways.

Delivering on New Types of Sales TargetsAccelerated product release cycles are forcing sales leaders to show results against a more dynamic and diverse portfolio of revenue streams. New business models that depend on recurring and consumption-based revenue are making churn and customer satisfaction first-class metrics by which sales leaders are evaluated. Pressure to do more with less means that “sell at any cost” directives are being tampered by margin-based incentives. Traditional sales organizations tend to structure the forecasting processes, reporting

mechanisms and compensation around top line growth. Consequently, they find it challenging to manage this range of new variables. By contrast, Predictive Sales Organizations balance the need to generate immediate sales with other strategic priorities such as market share, geographic expansion, and bottom line growth. Because they employ technologies that allow them to connect longer term outcomes with current behavior, they can play both the short and long game simultaneously. For example, they may choose to comp more generously on deals closed in nascent industries to establish a beach head in what are anticipated to be highly attractive markets.

The People: Reactive vs� Predictive

Becoming a Predictive Sales Organization • 12

Managing Increased ComplexityThe challenge of balancing top line growth with other strategic priorities is compounded by operating in global environments where insights are buried under complex geographical, product, and organizational hierarchies. In the face of limited resources, traditional organizations often gloss over nuances that distinguish the different facets of their business. But in the end, there are no shortcuts. As Joe Dillon, Director of Sales, at backup and storage vendor eVault describes, “Selling software in Europe is vastly different than selling it in North America. You can’t just build one peanut butter plan and go to market with it.” Predictive Sales Organizations augment the experience and judgment of managers and executives with systems that use machine learning to proactively identify and expose relevant insights. Such systems can identify emerging patterns such as changes in customer demand or a divergence in buying behavior between two regions, and proactively alert relevant parties.

Building a High Performance CultureOld sales organizations have a basic understanding of how to excel in managing talent, coaching, enabling the sales team, and implementing the latest sales methodologies. The Predictive Sales Organization sets itself apart by turning each of these elements into metrics that can be tracked and measured. This means that data is becoming the defining factor of success in each of these areas. For example, Mark Goode, SVP of Sales and Marketing at DSI Global, sees data and analytics as the way to transform sporadic success into consistent performance. “There are lots of talented salespeople out there who get thrown off because of their own personal biases. But if you have the right analytics on top of your opportunity management system, you can eliminate the subjectivity. The sandbagging and speculative conversations stop and you quickly get focused on what really moves the needle.”

The Sales ManagerSales managers are tasked with driving sales results of a team, developing individuals on the team, and relaying insights from the field to sales leadership. While they have always had a need to prioritize time and improve insight about their team activities, predictive analytics are becoming critical to the sales manager’s job function in three key ways.

Managing Risk AND the “Number”Sales managers are routinely asked to forecast the results they will achieve in a given period. In a conventional organization, the manager must apply her own judgment on top of individual rep predictions to come up with her own assessment of the anticipated outcome. But applying judgment calls on top of judgment calls leads to consistently bad forecast accuracy, which damages credibility, hampers decision-making and drags down performance. By contrast, predictive sales organizations demand that sales managers develop quantitative understanding and be able to communicate the risk behind “the number” in the forecast.

Becoming a Predictive Sales Organization • 13

Driving System AdoptionEven in the most mature sales organizations, conventional sales managers struggle with CRM adoption, many citing usage rates of less than 50% by their team members. In the predictive sales organization, sales managers acknowledge their role as the key driver of system adoption and are adept at finding the right combination of carrots and sticks to incent their teams to use systems effectively. Steve Rutledge, VP of Global Sales Operations at Genesys, says, “We have reps that live and breathe in our CRM system, and we’ve found that the sales manager is the biggest determinant of whether a rep uses the system properly.”

In addition to relying on managers to drive system adoption, Predictive Sales Organizations use data science to make systems even more relevant to the end user. For example, they’ll expose opportunity scores to encourage reps to focus on the most winnable deals or use predictive product recommendations to help reps uncover deals they may have otherwise never pursued.

Developing for the FutureSales managers are responsible for developing team skills to ensure sustained success. This requires attention to more than just results in the current period and the simple tallies of activities that conventional sales automation systems provide.

Sales managers must rely on intuition and exhaustive attention to the nuances of the sales process to understand the real story behind the numbers. A sales executive at a professional services firm comments, “A big part of what we do is look for patterns, and we look for common missteps across the organization. Then we bring that down to the field rep level and find the situations where they are extremely strong … or where they aren’t.” Predictive organizations are finding ways to support sales managers in this process by detecting patterns in the data, and presenting managers with blueprints for rep development. The sales executive explains: “There is a Venn Diagram. One circle represents selling opportunity and the other represents selling skill. Systems can find where the two circles overlap and help leaders correctly align reps with the best opportunities to close business and learn new skills.”

Curating Better DataConventional sales organization often look to sales operations to solve issues related to data quality. But since they lack direct influence over data inputs, Sales Operations must often resort to heroic acts involving many long hours of manual data crunching in Excel and PowerPoint. One sales operations executive admitted, “there was a time when we’d spend nearly 500 man hours per week reconciling data and preparing executive reports.”

In predictive sales organizations, managers and reps take primary ownership over data quality. Predictive analytics flags inconsistent data and these anomalies are discussed and resolved during pipeline and coaching calls. As managers and reps constantly engage with the data, data quality is naturally and continuously maintained, and analysts can apply more energy to their roles as strategic advisors to leadership. Vikas Bhambri, VP of Global Sales Productivity at LivePerson, noted, “I would say our sales teams, our business systems teams, our analytics teams and our data scientists are all constantly working in partnership to figure out what is the best way that we can create a reliable view of the data and then give each group their window into that data.”

The Sales Representative The sales representative’s most valuable asset is time. One of his main challenges is to decide how to balance time spent in creating new pipeline, advancing and closing deals, and building skills. In the Predictive Sales Organization, predictive analytics are becoming a critical tool to help sales representatives set priorities and find that balance.

Pursuing the Right DealsClosing a deal is tangible, exciting, and cause for celebration, but is it always worth the cost? Pursuing a long-shot deal consumes excess time of a representative, pulls resources from other teams, and sometimes results in unconventional agreements that serve neither party well.

Becoming a Predictive Sales Organization • 14

Conventional sales organizations allow their representatives to get pulled into these situations more often than they should, because they don’t get warning indicators early enough in the process to surface anomalies and undesirable outcomes. One of the hallmarks of a predictive organization is that they provide these early warning indicators, helping reps to revisit important steps in the sales process that may have been skipped and indicating when they should walk away from the wrong deals. One sales leader explains: “It’s critical to find opportunities in the pipeline that have [jumped stages too quickly], because that typically indicates that there haven’t been critical steps taken. Once we are moving into solution agreement with the prospect, we must prepare the product and implementation side for the incoming business. We’ve got to have all the pins knocked over ahead of time… before we get to that point.”

Sustaining a Healthy PipelineUnder constant pressure to deliver results in the current period, investment in pipeline development often plays second fiddle to closing activities. Conventional sales organizations will monitor pipeline size and coverage ratios, but too often the quality of pipeline is overlooked by reps. “There are a lot of people that throw multipliers out,” says Lars Nilsson, VP of Field Operations at CloudEra. “They talk about industry standards like 5x or 4x coverage ratio. I think it’s one of the most misunderstood metrics in the business. High coverage ratio targets encourage reps to add more low quality deals to the pipe. But when it’s done right, I’ve seen coverage ratios drop while close rates increase.”

Predictive sales organizations achieve sustained growth and consistent results by quantifying pipeline quality and driving reps to positive pipeline management behaviors. “What I’ve always strived for,” continues Nilsson, “is complete adoption of a methodology that reinforces effectiveness across outside reps, inside reps, OEM reps, sales engineers--anyone involved in the sales cycle. When the entire team takes a consistent approach to qualifying, pursuing and close business, that’s when you get consistent results.”

In the face of today’s dynamic selling environment, conventional sales organizations struggle. Rigid process, retrospective data and ad hoc application of selling methodologies don’t produce reliable and repeatable results. Successful sales leaders, by contrast, are finding ways to leverage predictive analytics to create flexible, agile organizations that consistently meet or exceed revenue targets. The Predictive Sales Organization departs from convention in a number of areas including coaching, forecasting, talent development, pipeline management, and CRM adoption. By incorporating predictive insights into their standard operational cadence, the best sales leaders can see farther and respond to shifting sales insights more quickly than ever before. In the process, they tap new sources of growth and competitive differentiation.

Contact C9 to participate in local executive forums or learn more about how C9 solutions can help your organization.

Summary: The Predictive Sales Organization

Becoming a Predictive Sales Organization • 15

Patrick Hurley | General Manager of the Americas, AcronisPatrick is a top-performing sales director with experience managing SMB, Enterprise, Federal, and SLED software sales teams. His experience includes hiring and cultivating successful sales representatives, developing internal processes, analyzing tends, and driving accountability across an organization consisting of inside & outside sales professionals.https://www�linkedin�com/in/phurley1

Lars Nilsson | VP Field Operations, CloudEra Lars is a results-oriented Inside Sales & Sales Operations Vice President with 20 years of management and leadership experience building sales organizations and generating demand for products in enterprise software and hardware organizations. He has built inside sales teams, created and implemented processes, systems, and infrastructure that boosted sales force productivity and efficiency, enabling those companies to accelerate growth, increase market share, and meet strategic objectives while ensuring financial and corporate compliance. https://www�linkedin�com/pub/lars-nilsson/0/16/a35

Loren Alhadeff | VP Corporate Sales, DocuSignLoren has extensive sales leadership experience building sales organizations from scratch as well as improving and accelerating the growth of existing sales teams and processes. He has practical experience and solid understanding of a vast range of business-management applications including market analysis, marketing, team-building, and quality assurance; the teams he has managed have sold to prospects/customers ranging from small and medium businesses through to the executive/enterprise markets. https://www.linkedin.com/pub/loren-alhadeff/2/a14/1b

Mark Goode | SVP Global Sales, DSI In addition to his current role at DSI, Mark has held various leadership roles including VP Sales (Americas and North America), VP Global Sales, and SVP Sales and Marketing. His previous experience includes leadership roles at Siebal Systems and SAP; at SAP he was responsible for key global accounts, including Hallmark, Bunge, Monsanto, Koch Inc, Dean Foods, Monsanto, and Energizer Holdings. https://www�linkedin�com/pub/mark-goode/22/3a5/213

Joe Dillon | Director of Sales, eVaultJoe’s experience includes leading and developing sales teams in start-up and large enterprises. More than 43,000 companies rely on EVault® Cloud-connected™ backup and recovery services, which seamlessly integrate on-premise and online backup data protection for fast, local data access and ensured Cloud-disaster recovery. https://www�linkedin�com/in/joedillon

Steve Rutledge | VP Global Sales Operations, Genesys Steve is a seasoned, senior sales operations executive with international experience in B2B Software and SaaS; he specializes in turn-around and high-growth endeavors. He consistently enables sales organizations to achieve superior results and has an execution-based approach to sales operations that provides measurable and consistent results to field sales and to clients. https://www�linkedin�com/in/stevevrutledge

Jeanne DeWitt | Director of Enterprise SMB Sales for the Americas, Google (formerly) Jeanne DeWitt worked as Head of SMB Sales, North and Latin America where she ran a 60-person sales team across new business acquisition and account management, as well as direct and channel sales. Previously she was Head of Google Apps SMB Sales, Japan and Asia Pacific as part of an 18-month assignment to execute a strategic growth initiative. Currently she is Chief Revenue Officer at UberConference. https://www�linkedin�com/pub/jeanne-dewitt/6/518/903

Vikas Bhambri | VP Global Sales Consulting and Sales Productivity, LivePersonVikas is transforming the way LivePerson sells through Sales Operations, Sales Productivity, Sales Development, and Sales Consulting teams. For the past 18 years he has advised the world’s biggest brands on the implementation of technology to better engage with their customers.https://www�linkedin�com/in/vikasbhambri

Bill Kiedaisch | Dir. Global Sales Analytics & Opportunity Management, Pitney BowesBill is responsible for the Global Sales Management System at Pitney Bowes, which is comprised of three groups: Salesforce.com and Siebel CRM for sales and marketing; Business Support and Governance; and Insights and Performance.https://www�linkedin�com/in/billkiedaisch

Patrick O’Leary | Senior Director of Strategy and Operations, YahooPatrick has held the positions of Director of Sales Strategy and Operations and Director of Global Sales Business Ops at Yahoo. Previously he was Director of Strategic Planning and Operations at Autodesk. https://www�linkedin�com/pub/patrick-o-leary/1/58/177

About Our 6-Part eBook Series Contributors

Becoming a Predictive Sales Organization • 16

About C9 C9 delivers predictive sales and marketing applications that increase revenue, generate more precise forecasts and mitigate pipeline risk. By combining data science with products that improve sales and marketing execution, C9 enables leading companies like Yahoo!, Pitney Bowes and Google to drive predictable growth.

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