Crafting an Effective Governance Framework for Business Applications A conversation with Bill Vanderwall, VP of Business Applications at Cision. In the SaaS-driven world, businesses rely on dozens, sometimes hundreds, of applications to run sales, marketing, finance, HR, and customer success. From forecasting platforms to customer success dashboards, SaaS powers every corner of go-to-market. But there’s a hidden cost: sprawl. Too many tools. Too many overlapping features. Too many silos. Bill Vanderwall, former VP of Business Applications at Cision, has seen this story unfold at companies like Netscape, Marketo, and Malwarebytes. He’s helped organizations tame chaotic tech stacks, rationalize spend, and align SaaS with business outcomes. In this episode of The Revenue Lounge, Bill breaks down what a SaaS governance framework really looks like, why companies need one, and how to make it stick. Facebook Twitter Youtube Why Governance is No Longer Optional Bill recalls a time when business units could buy tools without involving IT. Sales teams bought engagement platforms. Marketing bought automation. Customer success bought onboarding solutions. Each tool solved a problem, but together, they created a fragmented landscape. “At Marketo and Malwarebytes, I walked into companies where SaaS applications were being managed by the business. Data didn’t flow. Processes broke down. IT had to step in to bring some order.” Governance, Bill explains, isn’t about slowing people down. It’s about creating balance. A good framework ensures: Tools align with business strategy. Data flows across departments. Costs are rationalized. Priorities are set at the right level. The Two-Tier Governance Model The heart of Bill’s playbook lies in a two-level governance structure — one that balances strategy with execution. 1. C-Level Steering Committee (Quarterly) At the top, governance happens at the C-suite. This steering committee meets quarterly to set priorities and allocate IT resources. Bill recalls his time at Malwarebytes, where the CFO drove discipline with a three-year plan: “We’d identify the company’s top goals for the year — say, improving retention — and then align technology investments to achieve them. The C-level team agreed on the priorities, which eliminated politics and kept us focused.” Governance Flow: Company Strategy → Annual Operating Plan → C-Level Priorities → IT & SaaS Execution 2. Operational Committee (Monthly) Beneath the steering committee sits a monthly operational group. This team handles smaller projects, integrations, and SaaS purchases that don’t require C-suite oversight. Example: When a business unit wanted to adopt Gong, the committee vetted it to ensure fit with Salesforce architecture and estimated IT effort. Once approved, the business team owned administration while IT ensured smooth integration. This layered approach creates agility without losing alignment. https://www.youtube.com/watch?v=LUPp1J3R2io&t=1s Buy vs. Build: Choosing the Right Path For years, companies wrestled with the “buy vs. build” debate. Bill says the equation has shifted: “With so many best-of-breed solutions available today, buying is usually smarter — unless the capability is core to your product strategy.” Buy vs. Build Decision Matrix Criteria Buy Build Speed to Value ✅ ❌ Cost Efficiency ✅ ❌ Strategic Differentiator ❌ ✅ Core Business Function ❌ ✅ Maintenance Burden ✅ ❌ Taming SaaS Sprawl: Rationalization in Action When Bill joined Marketo, he discovered four separate survey tools in use. Governance turned that chaos into a deliberate choice: one enterprise-grade tool, better aligned with business needs. “Having a lot of applications isn’t automatically bad. But you need to ask: who’s using it, what’s it costing, and is there overlap? Rationalization is about making those calls — ideally before renewal cycles.” Best Practices for Rationalization: Inventory applications bi-annually. Track usage vs. spend with monitoring tools. Consolidate overlapping tools. Align consolidation with strategic priorities. The SaaS Sprawl Funnel: 270 Requests → Group by Themes → Prioritize by Impact → Approve via Governance → Rationalized Roadmap Measuring ROI: Beyond Vendor Claims Every SaaS vendor promises sky-high ROI. Bill is skeptical. “Vendor ROI models are fine directionally, but they’re packed with soft dollars. You need to separate hard savings from fuzzy benefits — and focus on time-to-value.” Key ROI Factors: Hard Dollars: License savings, reduced churn, FTE efficiency. Soft Dollars: Productivity gains, collaboration, user satisfaction. Time-to-Value: How quickly can benefits show up? “A little revenue growth can cover a lot of expenses. Time-to-value often matters more than a perfect ROI model.” Data Quality: The Hidden Governance Layer Bad data is every company’s silent killer. Bill has seen organizations simply “live with it.” But governance frameworks can elevate data quality through: Preventing duplicates at the source. Using enrichment vendors like ZoomInfo. Creating data lakes (Snowflake, Redshift) for cleansing and harmonization. Data Quality Levers: Front-End Governance → Enrichment Tools → Data Warehouse → Analytics → Business Impact Managing Change: From Chaos to Control Introducing governance to a free-for-all environment isn’t easy. Bill’s advice: Start with quick wins (fix broken data flows, automate manual processes). Build trust through partnership (don’t be draconian). Celebrate outcomes (show how governance accelerates, not blocks). “At Marketo, we allowed certain groups autonomy as long as they communicated and aligned. Governance isn’t about control — it’s about achieving the same objectives together.” AI, Legal, and the Future of Governance AI adds a new dimension: vendors want access to customer data to train models. Legal wants to block everything. IT sits in the middle. Bill’s advice: Get legal, vendors, and engineers on the same call to negotiate. Clarify data usage rights, anonymization, and safeguards. Accept that not every situation is black and white. AI Vendor Risk Checklist: Will my data train your models? Is data anonymized? What security guarantees exist? Can we opt out? Best-of-Breed vs. Platforms: The Consolidation Tradeoff With budgets tightening, platform consolidation is tempting. But Bill is cautious: “Most companies are still best at the thing they started with. Platforms may catch up, but best-of-breed usually wins — unless platform efficiency outweighs the feature gap.” Template: Platform vs Best-of-Breed Scorecard Criteria Platform Best-of-Breed Cost Savings ✅ ❌ Feature Depth ❌ ✅ Integration Ease ✅ ✅ Scalability ✅ ✅ Innovation Pace ❌ ✅ Vendor Maturity: Balancing Risk and Innovation Should companies bet on a young, innovative vendor?

Forecasting Strategies at Different Company Sizes A conversation with Keith Rabkin, Chief Revenue Officer at PandaDoc. Revenue leaders are constantly under pressure to deliver predictability despite economic headwinds, fluctuating buyer behavior, and increasingly complex deal cycles. In this episode of The Revenue Lounge, we sit down with Keith Rabkin, the Chief Revenue Officer at PandaDoc, to understand how he builds a forecasting engine rooted in operational excellence, strategic RevOps partnership, and deep customer-centricity. Keith’s journey spans two decades, including tenures at tech giants like Google and Adobe, where he mastered the intersection of data, GTM strategy, and customer satisfaction. At PandaDoc, he’s applying that same blend of analytical rigor and human insight to build predictable, scalable revenue engines. Facebook Twitter Youtube From Strategy & Ops to CRO: Keith’s Unique Journey “I think I’m a little bit of a non-traditional CRO.” Keith didn’t take the usual route into the CRO chair. Instead, he rose through strategy and operations roles at Google, where he honed his ability to use data as a decision-making compass. At Adobe, he led GTM strategy and operations for their $9B digital media business, where he first saw how customer-centric data patterns could be used to optimize every element of a go-to-market motion — from self-service sales to channel revenue. What hooked him? The satisfaction of being “obsessed with a number,” he says. Forecasting, for Keith, is a game of patterns and puzzle-solving — and the payoff is not just in numbers, but in the satisfaction of delivering a great customer experience. Public vs. Private Forecasting: Two Worlds, One Philosophy Forecasting at Adobe looked very different than forecasting at PandaDoc. Yet the underlying discipline — inspecting deals, applying data, and aligning cross-functional teams — remains the same. Forecasting Element Public Companies Private Companies Pressure Intense, stock-driven High, but more flexible Methodology Automated, bottoms-up, segmented Manual inspection, rep-specific Timeline Sensitivity Quarterly commitments drive urgency More customer-aligned pacing Discounting End-of-quarter incentives common Long-game view prioritized “At PandaDoc, I’d rather let a deal slip than pressure a customer to close just to hit a quarter.” This mindset allows PandaDoc to prioritize relationships over revenue timing — which, ironically, improves long-term deal value and trust. https://www.youtube.com/watch?v=1cqYn4a_nsU&t=1s The Forecasting Playbook: A Blend of Art and Science Keith emphasizes that while forecasting may appear like a data-driven function, it’s equally about human judgment. Here’s what his playbook looks like: Forecasting Component Description Deal-by-deal inspection Analyze every key opportunity through rep/manager reviews. Historical trends Weigh pipeline based on historical stage conversions, seasonal patterns, and rep accuracy. Manager alignment Collaborate with frontline managers and VPs to roll up forecasts with realism. Gut check Understand rep behavior: who’s conservative, who sandbags, who needs pushback. “You get to know who’s sandbagging and who’s just optimistic. That’s the art.” He holds weekly meetings with his GTM leaders to walk through the forecast. But it’s not a top-down call — it’s a collaborative build-up, followed by his own adjustment based on trend recognition and leader context. The Domino Effect of Dirty Data Bad Close Rate Data → Inaccurate Pipeline Weighting → Forecast MissesUnreliable Pipe Gen Tracking → Overconfidence → Poor CoverageLack of Stakeholder Mapping → Underestimated Risk → Deal Slippage “Bad data is a huge obstacle to an accurate forecast.” Keith’s solution? A world-class RevOps team and weekly “D-DOM” meetings (Data Driven Operating Model), where every GTM leader sees and aligns on the same datasets. This operational cadence makes data central to every action — not just a reporting afterthought. RevTech Isn’t the Answer. But It Helps. While Keith is bullish on RevTech, he’s also cautious. He notes that no tool can replace fundamentals like deal inspection, rep performance analysis, and buyer engagement tracking. That said, RevTech tools have made his life easier in the following ways: RevTech Function Forecasting Value Call & Email Data Reveals real engagement and momentum. PandaDoc Engagement Tracks opens, page views, and forwards. CI Tools Helps uncover true multi-threading. Forecast Software (Under evaluation) Competing tools for visibility and roll-up support. “Forecasting tools are helpful, but the magic is in the intersections — rep + stage + seasonality.” He predicts that AI will soon help revenue teams process these complex intersections more effectively. Deal Inspection Checklist for Complex Sales Champion Validated? Is it a true champion or just a coach? Economic Buyer Identified? Can they sign off? Discovery Depth: Have we uncovered real pain and urgency? Multi-threaded? Are 2–3 stakeholders from different teams engaged? Next Steps Documented? Is there clear mutual action? PandaDoc Activity? Has the proposal been opened and reviewed? “We’ve locked down our stages with no judgment calls — just concrete criteria.” If a deal regresses — for example, the buyer leaves or restarts the evaluation — Keith prefers to roll it back rather than falsely keep it in an advanced stage. Revenue Doesn’t Stop at Closed-Won: Expansion and Renewals PandaDoc’s post-sale strategy mirrors its new business motion — highly structured, data-backed, and RevOps-enabled. Function Role Customer Experience (CX) Drives adoption, feedback, early risk signals. Account Management (AM) Owns renewals, expansion, and commercial negotiations. “We separate value delivery from commercial transactions. That builds trust.” Forecasting on the renewal side follows the same rigor — stage tracking, risk reviews, and AM-manager forecasts. High-risk or high-value accounts get escalated for deeper review. Winback Motion: Closed-Lost ≠ Lost Forever Keith and team recently launched a Closed-Lost Nurture Program: Targeted drip campaigns Scheduled rep check-ins Competitor contract timeline tracking Stakeholder remarketing (when contacts weren’t captured in CRM) “Buyers come in 6–9 months before a competitor renewal. If we stay top-of-mind, we win the re-evaluation.” This motion ensures that timing—not interest—is the only reason a deal is lost. Killing the MQL Debate: Pipeline is the Real Metric Keith doesn’t ignore MQLs, but he’s shifted PandaDoc’s GTM model toward pipeline accountability. GTM Metric Marketing Role Sales Role Shared Outcome MQLs Generate quality leads Qualify accurately Feedback loop only Pipeline Source and nurture Accept and close Joint ownership “Both teams are goaled on pipeline — and both refuse to blame

RevOps Reporting: From Strategy to Execution A conversation with Tyler Will, VP of Revenue Operations at Intercom. Ever built a dashboard that no one ever looked at? You poured hours into it—cleaned the data, crafted the visuals, launched it with flair—and… crickets. We’ve all been there. But for Tyler Will, VP of Revenue Operations at Intercom, that moment of silence is a signal. It’s the difference between reporting for reporting’s sake and reporting that actually drives business action. In this episode of The Revenue Lounge, Tyler pulls back the curtain on how to transform data into compelling narratives that power decisions. From organizing your RevOps team to infusing business acumen into analytics, here’s your crash course in reporting that actually lands. Facebook Twitter Youtube Structuring RevOps for Impact, Not Chaos Tyler doesn’t treat RevOps as a reactive clean-up crew. At Intercom, he’s built a 30-person function intentionally divided into five tightly aligned pods: Core Ops, Planning & Comp, Go-to-Market Analytics, Strategy & Initiatives, and Systems. Each team plays a distinct role, but they’re united by a shared mission—to not just collect data, but to convert it into forward-looking decisions. This structure is what allows Tyler’s team to build reporting muscle across the GTM funnel. Sales planning? There’s a team for that. Forecasting? Covered. Marketing funnel analytics? Embedded. It’s a system designed for flow, not friction. Reporting Starts Long Before the Dashboard One of Tyler’s biggest lessons? Reporting should never be treated as an afterthought. Too often, teams invest months in strategic projects—new comp plans, revamped lead routing, or territory carving—without ever defining how success will be measured. Instead, Tyler’s team builds reporting into the project DNA from day one. That means defining business goals up front, assigning someone to own program execution (even unofficially), and scheduling reviews that extend beyond launch. Reporting, in this model, isn’t just a rearview mirror. It’s the GPS. “Too many projects end at go-live. We build to execute beyond the launch.” https://www.youtube.com/watch?v=GiTGr7rkFUk Dashboards Don’t Deliver Value—People Do Tyler acknowledges a universal RevOps pain: building dashboards that no one uses. The problem isn’t the tool—it’s the handoff. Sales leaders and frontline managers aren’t always trained to extract insight from data. So just delivering a dashboard isn’t enough. That’s why his team doesn’t just build tools. They teach people how to use them. They host sessions, create walkthroughs, and embed reports into the team’s operating cadence. And most importantly, they create accountability. If there’s a pipeline review next Tuesday, you’re expected to know your numbers. “If sales leaders aren’t using the data, that’s on us. We need to teach them how.” Turning Numbers into Narrative Data by itself doesn’t change behavior. What Tyler emphasizes is the need to translate data into a compelling story—one that informs, provokes, and leads to decisions. He uses a simple framework to coach his team: What? (The observation) So What? (Why it matters) What Now? (What we do about it) This isn’t about throwing more charts into a deck. It’s about surfacing meaning. If pipeline is down 30%, what does that mean for Q4 targets? What can the team do to close the gap? “Turning a table into bullet points doesn’t make it an insight.” Business Acumen: The Missing Link in Analytics Analytics teams often sit in their own world, crunching numbers without context. Tyler sees this as a major failure mode. His goal? Erase the line between analysts and operators. At Intercom, they’re embedding analysts directly into core GTM teams—whether that’s top-of-funnel, mid-pipeline, or renewals. He also encourages hiring people with hybrid skills—consultants who can pull data but also drive decisions. The ultimate goal is to stop treating analytics like an academic shop and start treating it like a business partner. “You can’t be stuck in an ivory tower. Analysts need a pulse on the business.” How Cadence Builds Proactivity Tyler’s approach to reporting isn’t ad hoc. It’s driven by a deliberate cadence that ensures his team is always a few steps ahead. Weeks before a quarter starts, his team is already deep diving into next quarter’s pipeline. Mid-quarter, they revisit forecasts and fine-tune outlooks. This cadence creates predictability. It gives leaders enough time to act—not react. Whether it’s campaign planning, resourcing, or sales execution, this forward-looking posture helps Intercom stay agile. “We’re not just reporters. We’re pattern recognizers surfacing risks before they explode.” Working Without Perfect Data Sometimes, you just don’t have the data you want. But that shouldn’t stall decision-making. Tyler leans on scenario modeling and sensitivity analysis to fill in the gaps. For example, what ROI would we get if we reduce churn by 2%? 4%? 6%? These projections give leaders a sense of risk and upside—even when certainty isn’t available. This is also where co-creation matters. Instead of building a theoretical case in isolation, Tyler’s team sits down with stakeholders and builds the assumptions together. That shared ownership leads to greater buy-in. “Even without clean data, we ask: What would we have to believe for this bet to pay off?” How Do You Know It’s Working? There’s no neat dashboard that measures the ROI of reporting. But Tyler looks for three signals: Are people using the dashboards? Are teams acting on the insights? Are results improving over time? It’s not just about engagement—it’s about impact. Did your QBR attendance go up? Did outbound volume increase after an insight was shared? Even if the RevOps team doesn’t get the credit, these shifts validate the value of your work. “If QBRs doubled after your analysis, the insight landed—even if someone else took the credit.” Where AI Fits In AI isn’t here to replace RevOps teams—it’s here to liberate them from the grunt work. Tyler believes AI can play a massive role in surfacing trends, anomalies, and summaries that would otherwise take days to prepare. That frees up analysts to do what they do best: interpret and act. The opportunity isn’t to automate insight, but to accelerate the journey to it. “AI should be the engine. Humans steer the

Strategic RevOps: Harnessing Data for Maximum Impact A conversation with Kelley Jarrett, SVP, Revenue Strategy, Operations & Enablement at ThoughtSpot. If you’ve worked in Revenue Operations over the past few years, you’ve likely felt the shift. The role that once focused on reports, dashboards, and process audits is rapidly evolving into something far more strategic. At the forefront of this evolution is Kelley Jarrett, SVP of Revenue Strategy, Operations & Enablement at ThoughtSpot—a company that lives and breathes data. Kelley isn’t just reacting to the changes in RevOps. She’s shaping them. In this episode of The Revenue Lounge, she offers a refreshingly practical perspective on what it means to drive revenue excellence in today’s go-to-market (GTM) world. Her story isn’t about abstract strategy or shiny dashboards—it’s about building a RevOps function that actually enables growth. One that doesn’t just collect data, but activates it. Let’s unpack how she’s doing that, and what it means for the future of RevOps. Facebook Twitter Youtube The Generalist’s Edge: A Career Built on Connecting the Dots Kelley never set out to be a RevOps leader. Like many of her peers, she entered through sales. Then post-sales. Then marketing. Her journey reads like a tour of the GTM ecosystem—intentionally so. Early on, a mentor advised her to choose between a specialist or generalist track. Kelley picked the latter. And that decision now powers the way she leads. “It’s a no-brainer for me. I’ve always been more interested in how all the pieces fit together.”— Kelley Jarrett, SVP of Revenue Excellence, ThoughtSpot This generalist mindset has made her exceptionally effective in aligning teams around revenue strategy. She doesn’t just understand how sales works—she knows how sales fits into a broader system that includes marketing, customer success, finance, and product. At ThoughtSpot, that mindset is critical. Because RevOps isn’t a back-office function anymore. It’s in the boardroom. Strategic RevOps Isn’t a Trend. It’s the New Default Kelley’s role today isn’t confined to building capacity models or distributing dashboards. She’s embedded in C-level conversations, helping shape the very goals that will drive boardroom outcomes. “We’re not just translating top-line goals into quotas anymore. We’re helping shape those goals—before they’re finalized.”— Kelley Jarrett That evolution isn’t just happening at ThoughtSpot. It’s an industry-wide shift. Titles now include “Strategy & Revenue Operations.” The bar for RevOps leadership is higher. And the best operators are becoming co-pilots to the CRO—not just order-takers. It’s also why Kelley believes RevOps should report into GTM, not finance. While financial alignment is crucial, having RevOps embedded in sales and marketing ensures that the function can reflect both the numbers and the nuance—the things that data alone can’t explain. https://www.youtube.com/watch?v=EfumXL1kkM8 Why Dashboards Aren’t Enough Anymore Despite the explosion of data tools in B2B, most companies still suffer from one pervasive problem: data lag. Kelley calls it “the data backlog.” And she’s lived it. In prior roles, RevOps teams built dashboard after dashboard, only to be asked for new filters, updated logic, or “one more cut” the moment a business user opened the file. “It slowed everyone down. RevOps became a ticketing system instead of a strategic partner.”— Kelley Jarrett To fix this, ThoughtSpot embraced what they’re best known for: self-serve analytics. Instead of centralizing all insights within RevOps, Kelley’s team created liveboards—interactive dashboards that empower GTM leaders to drill into pipeline, campaign performance, and conversion trends in real time. Not only did this remove bottlenecks—it restored RevOps to its rightful place as a strategic advisor, not just a data concierge. The Anatomy of a Strategic RevOps Function A modern RevOps team must evolve beyond reporting. Here’s what Kelley’s team looks like at ThoughtSpot: 🔎 Data Accessibility → Self-serve liveboards instead of static dashboards 📈 GTM Partnership → Active role in shaping quota, territory, and fiscal planning 🧪 Experimentation Culture → Campaign pilots to test what actually works 🔗 Functional Alignment → Embedded in sales, marketing, SDR, and partner teams 🧼 Data Strategy Ownership → A full-time team responsible for governance and hygiene From Static Planning to Dynamic Pipeline Execution The best part of Kelley’s approach? It’s not theoretical. She put it into action. When pipeline generation started to plateau across certain channels, Kelley didn’t call another meeting. She launched a cross-functional initiative called the Integrated Pipeline Plan (IPP)—a pilot designed to test whether tighter alignment between sales, marketing, SDR, and partner teams could move the needle. The team used ThoughtSpot’s liveboards to pinpoint gaps. Then they launched the pilot using a high-visibility moment: ThoughtSpot’s inclusion in the Gartner Magic Quadrant. The results? “Gartner told us it was the best-performing demand campaign for the Magic Quadrant they’d seen to date.”— Kelley Jarrett Even more impressively, sales became the fourth-highest source of qualified leads for the campaign—a clear sign that the integrated approach worked. Kelley’s 5-Step Integrated Pipeline Plan (IPP) Diagnose GapsUse liveboards to identify weak pipeline sources. Secure AlignmentGet sales, marketing, SDR, and partner heads to agree on the problem. Assign AccountabilityAppoint a cross-functional program owner (not RevOps) to run the play. Enable ExecutionArm teams with inspection reports, playbooks, and campaign materials. Measure, Learn, ScaleCompare baseline vs. campaign metrics. Repeat with pillar moments. Clean Data ≠ Perfect Data One of the most candid takeaways from Kelley? Every company—even data companies—struggles with data cleanliness. But rather than chase perfection, Kelley advocates for clarity and accountability. She believes every organization should have: A clearly documented data strategy A team (or individual) accountable for data health A feedback loop from real business execution back to the data team When data issues arise—say, sending invites to the wrong city due to HQ-based geo tagging—those learnings should be captured and fixed at the system level. “It’s not just about clean data. It’s about having a system to improve it over time.”— Kelley Jarrett The Buying Group Shift: Using History to Predict the Future Kelley has been a believer in buying group strategies long before it became a Forrester-fueled buzzword. But her approach is refreshingly grounded. She doesn’t rely solely on intent

The Flywheel Approach to Driving Full-Funnel Revenue Impact A conversation with Anil Somaney, Worldwide Head of RevOps at Island. As go-to-market strategies become more complex, high-performing SaaS organizations are seeking ways to drive efficiency, alignment, and growth at scale. Enter the Flywheel Framework, a powerful operational philosophy championed by Anil Somaney, SVP of Revenue Operations at Island. In this episode of The Revenue Lounge, Anil shares a detailed blueprint of how he builds momentum in GTM systems using the flywheel model. From team structure and metric alignment to the role of AI and data hygiene, this blog explores every insight in depth. Facebook Twitter Youtube The Strategic Evolution of RevOps RevOps has evolved from being a siloed, tactical support function to a strategic leadership role. Anil believes that today’s RevOps leaders must be both: Tactical: Running forecast calls, managing CRM processes, and executing operational rigor. Strategic: Driving long-term GTM planning, scaling transformation programs, and aligning cross-functional teams. “The ability to oscillate between strategy and execution—without treating one as superior—is what defines impactful RevOps.” What’s Driving This Shift? Macroeconomic pressure on efficiency A premium on productivity and resource allocation The disruptive force of AI across GTM motions Where Should RevOps Sit in the Org? Anil has seen RevOps report into CEOs, CFOs, COOs, and CROs. His view? “It matters less where RevOps sits. What matters is whether the team can operate across the full GTM system and serve as an independent source of truth.” Misalignment often occurs when reporting lines influence data transparency. To avoid this, RevOps needs the autonomy to surface the truth—even when it’s uncomfortable. https://www.youtube.com/watch?v=p1a4_qfwcvc&t=6s Structuring the RevOps Organization Anil’s ideal RevOps structure is built on balance: functional expertise with centralized intelligence. Org Model: A. Field Operations (Function-Aligned) Marketing Ops Sales Ops CS Ops Partner Ops BDR/SDR Ops B. Center of Excellence (Centralized Ops) Sales Compensation Territory & Segmentation Insights & Analytics RevTech/Tooling C. Enablement & Transformation Field Enablement Business Transformation & GTM Strategy The Flywheel Framework: Explained The Flywheel is Anil’s mental model for scaling initiatives with compounding impact. It connects: Systems Tools Processes People Data Enablement “Think of it as levers and pulleys. If you align every component correctly, you get outsized output from reduced input.” What Problems Does the Flywheel Solve? Functional silos (marketing optimizing MQLs without NRR impact) Inconsistent KPIs across teams Misalignment of goals and incentives How the Flywheel Works: Start with a single initiative (e.g. new ICP campaign) Map downstream impact across functions Measure results consistently Systematize the process Let the momentum compound Metrics That Matter Rather than drowning in dashboards, Anil advises picking a “dirty dozen” metrics that the exec team reviews weekly. 3-Part Weekly Pipeline Meeting: What happened? (Metric review) Why did it happen? (Root cause analysis) What are we doing about it? (Accountability and action) “Too many metrics distract. Get aligned on a few that matter and meet weekly to interrogate them.” Operationalizing the Flywheel   When launching any new GTM initiative, Anil uses a repeatable checklist: Flywheel Launch Framework: Systems: Is the tech stack ready? Processes: Are SLAs and handoffs defined? People: Do we have the right roles in place? Enablement: Are frontline teams trained? Measurement: What success metrics are we tracking? Infographic Idea: Flywheel Initiative Checklist with the 5 components in a flow. “Every initiative must start with this checklist. It’s how we scale predictably.” The Data Challenge: Clean Enough to Decide Perfect data doesn’t exist. So what does Anil do? Uses 3-source validation for external data Customizes vendors by region (e.g. GDPR nuances) Simplifies internal workflows to reduce user fatigue Builds system-enforced hygiene (e.g. can’t move stage without deal value) “Explain the ‘why’ behind each CRM field. If AEs understand it, they’ll update it.” The Role of AI: Assist, Not Replace Anil shares a jaw-dropping AI demo: a bot that delivers MedPic pitches, builds decks, sends emails, and adapts to multi-threaded buying groups. “AI is evolving fast. But it won’t replace strategic selling. It’s about augmenting reps, not eliminating them.” Where AI Works: Auto-updating CRM fields Initial outbound emails Data enrichment Where AI Falls Short: Building trust with a buying committee Navigating internal conflicts Buying Groups and the End of the MQL “The buying committee is more hidden and complex than ever. The MQL is no longer enough.” Anil’s Take: Buying groups require early-stage opportunity containers SDRs should qualify committees, not just individuals Partnership between BDRs and AEs is critical On Attribution: Imperfect but Important “You’ll never capture the trade show hallway conversation. But you still need to measure.” Anil’s Attribution Principles: Use multi-touch models, even if flawed Apply the model consistently over time Watch for shifts in weighting after new investments Advice for Aspiring RevOps Leaders “Great RevOps isn’t about being a control tower. It’s about getting results through others.” His Guidance: Study strategy (e.g. Art of War for business) Master cross-functional influence Learn to articulate a shared vision Spend more time on upfront alignment   Conclusion Anil Somaney’s Flywheel Framework is more than an operational methodology—it’s a leadership mindset. By aligning systems, people, processes, and metrics into a compounding engine of value, RevOps can become the orchestrator of revenue acceleration. “I love this job. I love the people. And I love seeing my work directly impact the bottom line.” Want to hear more stories from revenue leaders? Subscribe to The Revenue Lounge podcast to never miss an episode! More Resources