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Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
Drilling Down Into Big Data to Manage Variable Incentive Risks
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Drilling Down Into Big Data to Manage Variable Incentive Risks

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As a CFO, you are accustomed to checking ratios in regards to expenses, COGS, net income and more. Comparing ratios from publicly available information is a key part of the monthly, quarterly and …

As a CFO, you are accustomed to checking ratios in regards to expenses, COGS, net income and more. Comparing ratios from publicly available information is a key part of the monthly, quarterly and annual review of firm performance. Some information, however, is not as easily visible when peer comparisons are being made. Take the over $800 billion spent annually on sales compensation. Visibility to variable compensation ROI is hard for companies to measure, let alone drawing comparisons against the marketplace. For example:
- Do you know what percentile you are paying your sales reps compared others in your industry?
- How does your quota setting practices match up to your industry peers?
- What is the optimal compensation plan for your industry?
This session will share new insights into how companies are leveraging empirical big data from Xactly to check their plans, spending levels, and performance to analyze benchmark internal performance against the peers.

Speaker: Marisa Massie, Controller, Bazaarvoice

Presentation delivered at ProformaTECH 2014 - http://www.proformatech.com
Track: Change Anticipation & Readiness | Session: 3

Published in: Business
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  • Welcome to this session on how you can leverage big data – your own and others – to manage variable incentive risks.I am so pleased to be here to discuss two topics that I am quite passionate aboutbig data and Incentive compensation – And talk about how they can be combined to take your compensation program to a new level and maximize the value of the sales comp $$ you spend every year.Currently, I am Controller at Bazaarvoice, where I joined shortly after the 2012 IPO, to bring SaaS business leadership, salesforce.com best practices, and public-market scalability to BV.
  • I worked at salesforce.com for 6 years – from $500M to $3B.I was Americas Controller for two years. I was the Sr. Director of Sales Comp Operations for fours years during which the commissioned team grew from 1,500 to almost 4,000 participants. The number of plans tripled. We moved from 200k credits a month to over 1 million.I worked directly with the Vice-Chairman of Sales and the international sales leaders to design and deliver comp plans and the underlying systems. We were breaking new ground in Saas sales compensation models including renewals, new products, new selling models and channels, and acquisitions. My team lead the design of the end-to-end systems integrating salesforce from account lead opportunity into Xactly sales comp and provided the big data that enabled the success of our plans.As we in finance know – we’re downstream from a lot of processes.I had to start upstream with the Sales Strategy team, the territory management team, opportunity management, products/pricing, sales ops, all the way through to invoicing and comp. – by showing how this integrated design added value to their analytics – they really embraced the integration and accelerated our efforts. This also gave me a unique perspective on the highly effective data architecture and integrated systems design.I have worked across several industries, Wireless, biotechnology, Agriculture Biotech, and started my career at E&Y focusing on venture capital, venture-backed businesses and M&A. I mention that to reinforce that the topics we discuss today are industry-agnostic. We all need great salespeople.
  • Shopping is different. Consumers can have any virtually any piece of information about a brand, product or service at their fingertips at any moment.. Many research products before ever setting foot in a store or are using retailers as a showroom to research products and then turn to Amazon to make their purchase. This trend is only going to get bigger.In fact, according to Forrester research, more than half of all retail sales – online and offline – will be influenced by Internet content in the next 3 years.
  • One of the key drivers of this change in consumer behavior are Millennials – people raised in a world of social networking, mobile devices and constant access to the Web – people who have no idea what the world was like before the Internet. Also called GenY, this group is going to have more spending power by 2015 than any other generation in history. But that’s not the only reason why they are a critical generation. Other generations are mimicking their behavior. They are leading the change and setting the trends in the way people want to engage with brands.And they have a very specific way in which they want to be engaged with your business. To reach and influence them, you need to host, join, and amplify their conversations. You need to learn and use their language. You need to create experiences that reflect their unique identities and make it easy for them to share those identities with the world. You need to give them engaging, useful content that lives everywhere they do. And you need to be authentic, accessible, and interesting. We know this because we’re obsessed with Millennials. We’ve shared a lot of what we’ve learned about them in reports like The Conversation Index, and we work with experts like Jason Dorsey. Our Millennial insights have appeared in Forbes, AdAge, TheNextWeb, Econsultancy, eMarketer, and on The Early Show, to name a few.
  • The intersection of technology and consumer behavior helped create a perfect opportunity for Bazaarvoice to reach people with the right information at the right time in their shopping journey.Bazaarvoice is based on a simple truth; when people talk to each other, people buy stuff they are happy about because they trust the opinions of others. We see a day when all voices are connected and, together, help the marketplace function better. That’s what our name means: the “voice of the marketplace.” We’ve built a network that connects businesses together to amplify the authentic voices of people wherever they shop – online, in-store and mobile. We help people decide what do to with their hard-earned money. Our technology helps people spend their money more wisely.
  • To see the power of the network effect, the content in our network gets viewed 400 million times every single day. Last fiscal year, our clients’ content was viewed 145 billion times. And since we started our company, content in the network was been viewed 425 billion times.
  • Clients who carry the Bazaarvoice Authentic Reviews Trust Mark are sending a signal to consumers that the review content they see is safeguarded – by a neutral 3rd party – with sophisticated fraud detection technology and industry-leading best practices.
  • Some of the world’s most respected businesses across a variety of industries work with Bazaarvoice. We help marketers and advertisers provide more engaging experiences, drive product innovation and performance, make better merchandising decisions and build brand advocates and loyalty.
  • Regardless of business = Sales comp common constructsBasis applies to all = 3 measures, (pressure to expand to 4 or 5)Two areas drive pressure on hunter vs. farmerIncrease customer service and retention =Land and Expand = Leverage integrated tools = =SaaS movement acceleratedUser interface requirements = data on-demandE.g., see sales next dayCRM and Sales CompCRM feeds to invoicing systemBig DataPlan performance = measure success of the plan Did sales meet the quota == but what about all the other measures?
  • ……but how do you know it’s working and when and how to adjust?[investing in systems gets you there…]TRANSITION: How do you know it’s working? Invest in the SystemsSo how you get all this great data?As CFOs and financial leaders, we are responsible for the financial success of the company and contribute to every line on the P&L. With Sales Comp equal to 15 to 25% of Revenue, this makes it one of the three of the biggest investment decisions a company can make. An excellent sales comp plan is one of the most direct contributions a CFO can make to the Top Line. Investing wisely to create a successful sales compensation plan that motivates the right behavior and establishes accountability is one of the most direct drivers a CFO can use to contribute to revenue.What is the most difficult about the Sales Comp plan is that you only really get one shot at it a year. And if you find yourself tinkering with it during the year, its usually in reaction to a plan gap, is expensive and can distract the sales team. And if you do business in any countries with “Works Councils” it can be a challenge, to say the least, to go back to them during the year.So, how do you get it right the first time?
  • What does “Managing the Variable Incentive Risk” really mean?Like most companies, regardless of industry / selling model, Everyone has experienced sales compensation challengesSome phrases that may have already jumped to your mind areGame the planSales made their OTE, great Presidents club in Hawaii, but we missed the revenue targetLove the big deal, but HOW much did that sales guy get paid?You have the opportunity to change the conversation to one of partnership with sales leaders to launch a sales commission plan that successfully both manages the financial risk and pays for performance.
  • Measure what you manage – not a typo – We know that the FP&A team is checking on revenue goals and the cost envelope.The Sales team is check on OTEThe Comp team is executing on the plan.But what about measuring ALL those critical elements that you spent so much time negotiating?Did you really minimize the risk?Are we getting those behaviors so necessary to meet our company revenue / product goals?For example – plan may pay more on annual up-front invoicing – is that translating into the billing dollar volume you were planning?This is the area of greatest opportunity to add value to the sales team and to the business. -- Validate the ROI of the money paid for these drivers.
  • Question #13: Marisa, I’m sure the audience would enjoy your thoughts on how to empower employees in the field to act on the sales performance data they access. Similarly, how would the CFO manage their accountability in this regard? Three measuresAssuming that Tend to focus New business – sales focus, make club, promotionsBest sales managers most value to the business and the sales team
  • Regardless of business = Sales comp common constructsBasis applies to all = 3 measures, (pressure to expand to 4 or 5)Two areas drive pressure on hunter vs. farmerIncrease customer service and retention =Land and Expand = Leverage integrated tools = =SaaS movement acceleratedUser interface requirements = data on-demandE.g., see sales next dayCRM and Sales CompCRM feeds to invoicing systemBig DataPlan performance = measure success of the plan Did sales meet the quota == but what about all the other measures?
  • Question #7: Marisa, back to you with a key question: Companies talk about Big Data, but where is it when it comes to sales compensation? Is there a way to connect the dots?Respondent: MarisaData fidelity – rely on data calculated by the system, SOX, objective dataSaaS Tools = Data ArchitectureCRM (opportunity) – rich data around customer, who booked the deal, campaignOrder system (Customer details and what was sold) – actual revenue driver, verifiable, lots of SOX controlsSales Tool (Comp) – Feed core data in organized fashion – more control, connect the dots, same dataBiggest root cause of lack of clarity and analysis is data transformationData transformation = data loss
  • CRM / ERP tools are more robustInvest in the data architecture – brings it all together – removes dependency on sales manually input and operates on rules, flexibility, system of record,For those folks that are more deeply in design or systemsTalk more
  • Regardless of business = Sales comp common constructsBasis applies to all = 3 measures, (pressure to expand to 4 or 5)Two areas drive pressure on hunter vs. farmerIncrease customer service and retention =Land and Expand = Leverage integrated tools = =SaaS movement acceleratedUser interface requirements = data on-demandE.g., see sales next dayCRM and Sales CompCRM feeds to invoicing systemBig DataPlan performance = measure success of the plan Did sales meet the quota == but what about all the other measures?
  • Partial Xactly SaaS data set (1200 reps)Optimal: reps near the orange curveIn red: overpaid & under performingIn blue: underpaid - at risk of leaving
  • Regardless of business = Sales comp common constructsBasis applies to all = 3 measures, (pressure to expand to 4 or 5)Two areas drive pressure on hunter vs. farmerIncrease customer service and retention =Land and Expand = Leverage integrated tools = =SaaS movement acceleratedUser interface requirements = data on-demandE.g., see sales next dayCRM and Sales CompCRM feeds to invoicing systemBig DataPlan performance = measure success of the plan Did sales meet the quota == but what about all the other measures?
  • Transcript

    • 1. Drilling Down Into Big Data to Manage Variable Incentive Risks Marisa Massie Controller, Bazaarvoice
    • 2. Common Ground Across Industries Big Data SaaS and Sales Comp Leader Success in Subscription Economy: Role of the Controller 2 © 2014 Proformative
    • 3. By 2016 an estimated 52% of total online and offline retail sales will be influenced by Internet content(1) 3 © 2014 Proformative 1.Source: Forrester Research
    • 4. Millennials Trust & influence. 51% 59% 84% Trust strangers’ opinions over friends and family. List internet as their main news source. are influenced by UGC. Confidential and Proprietary. 4 2012 study by Bazaarvoice and The Center for Generational Kinetics © 2012 Bazaarvoice, Inc.
    • 5. Bazaarvoice powers a network that connects brands and retailers to the authentic voices of people where they shop. © 2014 Proformative
    • 6. Content syndication across the Bazaarvoice network Brand content can be displayed across multiple retail sites Brand X
    • 7. 400M Average impressions served per day in FY2013 145B 473B Impressions served in FY2013 Impressions served since inception
    • 8. Global blue chip client base Retail Technology Consumer Products Travel and Leisure Financial Services
    • 9. Evolution of Sales Performance Management Big Data Plan Performance Integrated SaaS Tools CRM & Sales Comp 3 Measures Hunter vs. Farmer © 2014 Proformative 10
    • 10. Invest in the Top Line Top 3 Investments Cap Ex Sales Comp  IT Sales Comp 15-25% of Revenue Get the comp plan right  deliver the top line 11 © 2014 Proformative
    • 11. Invest in Sales Comp – dramatically higher ROI • Measure Plan Success • Deliver on key metrics • Pay for real performance Invest in Excellent Data What is the right Data to invest in? • Lead data-driven decisions • Benchmarking • Predictive Analytics 12 © 2014 Proformative
    • 12. What is Plan Success ….vs Saleperson Success? Salesperson Success Plan Success • Made Quota – Going to Club • Company hit sales targets • Right markets, right markets • Made OTE • Paid on big deals 13 © 2014 Proformative • Achieved on all 3 elements • Not through SPIFFs, exceptions, etc. • Paid without caps for the right deals
    • 13. Managing Variable Incentive Risks “Game the Plan” “Commissions paid, sales targets missed” “Risk from Blue Bird deals” 14 © 2014 Proformative
    • 14. It All Seems so Simple When We Start CFO Sales Revenue Goals Behaviors Markets Products Profitability Cost Envelope 15 © 2014 Proformative New Business Products Renewals Target OTE Commission Plan Quota Rates
    • 15. When Does it Get so Difficult? Experience Sword 16 © 2014 Proformative
    • 16. What are the Battlegrounds? PLAN ELEMENT TRUST How many measures? Build two measures into one Only Three Leverage Policy Payout Curves Capped curves drive sales to next year Keep selling Bluebird Capped payments Manage the rate per credit Quotas Midyear quota reset Splits w/o quota 60% hit quota Overassign wisely “Outside Plan” 17 COMPLEXITY SPIFs, quarterly bonus, new logo, product 2-3% OTE [across the business] © 2014 Proformative
    • 17. Measure What You Manage CFO EVP Sales Revenue goals Behaviors Markets Products Profitability Cost Envelope 18 © 2014 Proformative Products Renewals Multi-year Quarterly consistency Professional Services Outclauses Target OTE Club? Commission Plan Quota Rates
    • 18. Fast Feedback Reinforces Behaviors Selling New Products 50% Everyone Wins © 2014 Proformative Renewals Contract Length 30% 20% Collaboration Longer, but not too long
    • 19. Measure the Effectiveness of Your Plan • Cost per revenue $$ or product? • Include everyone paid on the products • Desired deal structure? • Product mix • Contract term • Cross-account customer profitability? 20 © 2014 Proformative
    • 20. Insights & Benchmark Examples • Executive • • • • Quota Setting Quota Modeling Quota Distribution Productivity by Product, Region, Rep • Finance • • • 21 Sales Comp Profitability v (Spend/Revenue) Spend by Plan Spend by Role © 2014 Proformative • Sales Ops • • • • • Model Comp Plan Payout Curve Benchmarking Payment Triggers Model Crediting Effective Commission Rates • IT • • • Data Quality System Usage Distribution Processing Distributions
    • 21. How do you Invest in Excellent Data? 1. Tie all commission credits and payments to specific transactions 2. Architect your data across CRM, Sales Order and Comp ecosystem 3. Measure ALL payouts 22 © 2014 Proformative
    • 22. Evolution of Sales Performance Management Big Data Plan Performance Integrated SaaS Tools CRM & Sales Comp 3 Measures Hunter vs. Farmer © 2014 Proformative 23
    • 23. Connecting the Dots to Big Data Opportunity Quote Product Pricing Payment Sales Comp Quota/Commissions 24 © 2014 Proformative
    • 24. 1. Tie all Payments to Transactions Order line details drive credit calculation Order info, order start date, order end date, term, product ID, account or order ID Leverage your comp system to calculate the credit and retain „references‟ to opportunity, contract and account Data transformation = data loss 25 © 2014 Proformative
    • 25. 2. Robust Data Architecture Value-add data resides everywhere Account & Territory Parent Territory Region 26 © 2014 Proformative Lead Opp‟ty Order Source Sales Team Product Inside sales Partner Support roles (e.g. SE) Terms New or Renew Comp Credit Tie to Order / Oppty / Account CRM Comp Tool
    • 26. 2. Automate and Enrich Data SPIF Object Account & Territory Comp Product Family Lead Deal Object Opp‟ty Account Team for Splits Role-based share 27 © 2014 Proformative Order Credit Type Comp Credit Commission Event Object
    • 27. 3. Measure All Payments Trade-off „discretionary‟ items to fund more impactful design elements • Outside of Plan elements: Professional Services • Expensive add-ons: SPIFs, Quarterly bonus, • Unplanned expense: Exceptions, adjustments Create Unique tracking IDs for these in Comp System All Payments through Comp Team 28 © 2014 Proformative
    • 28. Payback is Data-driven Decisions • Maximized investment in highest value plan elements • Robust risk modeling and forecasting • Effective sales performance management • Motivated sales team 29 © 2014 Proformative
    • 29. Evolution of Sales Performance Management Big Data Plan Performance Integrated SaaS Tools CRM & Sales Comp 3 Measures Hunter vs. Farmer © 2014 Proformative 30
    • 30. Benchmarking Opportunities Compare through ‘independent’ sources • Benchmark vs. self • Prior year Plan Design Success • Monthly progress of current Plan • Benchmark vs. others • Organize data to enable benchmarking 31 © 2014 Proformative
    • 31. Quota Attainment vs Industry Benchmark 65.00% 70.00% 60.00% 50% 50.00% Benchmark 35% 40.00% 30.00% 20.00% 20.00% 15% Attainment 15.00% 10.00% 0.00% Attainment 0-80% 32 © 2014 Proformative Attainment 80%120% Attainment Over 120%
    • 32. Payout Curve Benchmark 250% PAYOUT % 200% 150% 100% 50% 0% 0% © 2014 Proformative 50% 100% 150% ATTAINMENT % 200% 250% 300%
    • 33. You‟re Not Alone… Sibson Software Sales Comp Forum • Renewals comp in „Hunter‟ Plan • Crediting new products • Goal for 100% attainment / club • Blue Bird Clauses • SaaS vs. Software Sales comp 34 © 2014 Proformative
    • 34. Benchmarking – Data Driven Decisions • Start by analyzing your own performance • Identify highest value areas • Reach out to data sources 35 © 2014 Proformative
    • 35. What‟s next? Where do you go from here?  Assess commission data quality  Evaluate plan effectiveness at same level you designed  Look for benchmarks in preparation for next year‟s plan Invest in the infrastructure 36 © 2014 Proformative
    • 36. Evolution of Sales Performance Management Big Data Plan Performance Integrated SaaS Tools CRM & Sales Comp 3 Measures Hunter vs. Farmer © 2014 Proformative  Measure Plan Success  Start Benchmarking    Specific Transactions Architect Data Measure ALL   Define Plan Success Design with trust 37
    • 37. Xactly Solutions 38 © 2014 Proformative
    • 38. Questions Marisa Massie @marisamassie marisa.massie@bazaarvoice.com http://www.linkedin.com/in/mmassie 415-728-2932 Subscription Economy: Role of the Controller Zuora – Subscription Economy - eBook 39 © 2014 Proformative
    • 39. Drilling Down Into Big Data to Manage Variable Incentive Risks Marisa Massie Controller, Bazaarvoice

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