CASE: E-359 DATE: 02/23/10
Claire Magat Raffaelli prepared this case with the help of Kirk Bowman, Lecturer in Management, and James Lattin, Robert A. Magowan Professor of Marketing, as the basis for class discussion rather than to illustrate either effective or ineffective handling of an administrative situation. Copyright © 2010 by the Board of Trustees of the Leland Stanford Junior University. All rights reserved. To order copies or request permission to reproduce materials, e-mail the Case Writing Office at: cwo@gsb.stanford.edu or write: Case Writing Office, Stanford Graduate School of Business, 518 Memorial Way, Stanford University, Stanford, CA 94305-5015. No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means –– electronic, mechanical, photocopying, recording, or otherwise –– without the permission of the Stanford Graduate School of Business.
OPTIGEN
Achieving success as a public company requires the ability to make accurate revenue forecasts. This is easy to forget when your company is beating its projections quarter after quarter. Firms in this overachieving position run the risk of assuming invincibility; it often takes an unexpected miss to shed light on problems lurking beneath the surface.
— Steven Thayer, OptiGen cofounder
INTRODUCTION
It was October of 2006 and Robert Campos, CEO of OptiGen, was preparing for a series of meetings with investment banks to discuss the prospects for an IPO. OptiGen had benefited from industry momentum that year as several technology companies experienced highly successful IPOs. This was OptiGen’s opportunity to follow in their footsteps. Management had begun meeting with investment banks, driven by the goal to go public before the window to IPO closed. As Campos thought ahead to the challenges that the company faced, he could not help but consider how much more straightforward things had appeared when he joined the company in 2004. At that time, OptiGen was a darling of the wide-area network (WAN) optimization industry, having surpassed all expectations in its first 18 months of sales. Campos had been so impressed by the startup’s potential that he, himself, had approached the management team about the CEO role. Back then, it appeared as though nothing could get in OptiGen’s way. Two years later, however, the company was facing a series of intimidating hurdles. To have a chance at a successful IPO, Campos and his team would have to fix two key, interrelated problems: a broken forecasting process and inconsistent quarter-over-quarter revenue growth. OptiGen had just missed its operating plan for the second time in the span of three quarters; if this happened again post-IPO, the company’s value would almost certainly tumble precipitously. The miss was a symptom of a larger problem: internally, there was little relationship between the forecasts provided by the sales team at the beginning of any given quarter and the operating plan set forth by management. In addition, Campos would need to
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address the company’s saw-tooth sales track record. While company sales looked superb on an annual basis, results had dipped every other quarter for the past year. Even though OptiGen had survived forecast inaccuracies and bumpy sales up until now, going public would require a pattern of sequential quarterly growth that moved consistently up and to the right. Campos would need to work closely with his VP of sales to bring predictability to the company’s operations. One of the most important priorities pre-IPO would be building a forecasting model that relied on information other than the highly subjective assessments of the sales force. The fate of the company rested heavily on the management team; if they could not fix the intra- quarter variability and forecasting inaccuracies, OptiGen would never reach its full potential. With an IPO in the near horizon, the situation was precarious. Even against the backdrop of great success, loyal customers, and industry acclaim, it was clear that before going public the company had to make some difficult decisions in addressing these significant challenges.
FOUNDING STORY
In February of 2002, three colleagues at the foundering Internet infrastructure start-up Flexpower recognized an uncertain future and began discussing the possibility of starting a company together. Patrick Stone, Lester Niles, and Steven Thayer had enjoyed the ride, but as the dot-com bubble burst and companies like Flexpower closed up shop, they knew that it would soon be time to transition to a new opportunity. Even though none in the trio had ever founded a company, all three had been moving towards this goal with their latest career choices. When Flexpower did indeed close, they followed their entrepreneurial instincts and decided to start something new. Thayer described his reasoning:
I had always dreamed of starting something on my own. I left my role at EMC to go to a start-up raising its third round of financing. I then moved on to Flexpower to gain experience with an even younger company. I needed to see how each stage worked before starting my own company. By 2002 I was ready.
The team began meeting at Stone’s house in the suburbs of Boston. They brainstormed around solving one of the many IT problems facing companies. One of the ideas that emerged was to develop an innovative and comprehensive solution to the problems plaguing wide-area networks (WANs): poor performance, IT complexity, and high cost.1 Technological advances had improved users’ ability to access data and use applications rapidly across their local-area networks (LANs), as well as store large amounts of information economically. However, these same applications and storage technologies often led to slow performance, data inconsistencies, and management complexities across WANs. Application and network limitations included the effects of “latency” (the time it takes for data to travel distances across a WAN) and “chattiness” (the numerous interactions between clients and servers that are often required by applications or network transport protocols to complete an operation).2 The combination of latency and
1 A WAN is a data communications network covering a broad geographical area (often across metropolitan, regional, and national boundaries). This contrasts with a local-area network (LAN) which is limited to a single building. WANs are used to connect LANs and other types of networks together so that users and computers in once location can communicate with users and computers in another location. 2 Riverbed S-1 Filing, April 20, 2006, p.2.
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chattiness caused poor performance and downtime, posing serious business challenges for companies relying on their networks to be efficient. Demand for WAN optimization products, as they were called, was driven by the increasingly geographically distributed nature of organizations and employees, the growing dependence of businesses on application performance and real-time access to data, and the increasing desirability of consolidating IT resources to achieve cost, management, and data protection benefits. In the past, WAN optimization vendors had introduced partial solutions to improve WAN computing, such as incremental investments in bandwidth and IT infrastructure resources. The team dreamed of offering a comprehensive solution that reduced the need for WAN bandwidth and consolidated geographically dispersed IT resources, while offering LAN-like performance of applications and access to data over the WAN.
The Competitive Landscape
As testament to the potential promise of the wide-area distributed computing market, several start-ups had recently launched: Peribit Networks and Riverbed Technologies. In addition to a large number of small, private companies, the team would face competition in the future from established players such as Cisco Systems, Juniper Networks, and F5 Networks which were looking to enter the space, likely through acquisition.
LAUNCHING OPTIGEN
On June 10, 2002, the trio of Stone, Niles and Thayer decided to pursue the WAN optimization opportunity and named their new company OptiGen. The team strongly believed that industry trends would support increased investment in improving WAN performance. As companies became more geographically dispersed, their IT costs were rising with increased remote computing. Application traffic such as internet and intranet access, file and database access, voice and video, and email, all competed for limited bandwidth. Giving superiority to one application led to disruptions to others. OptiGen believed that their solution could minimize the IT needs of branch offices as well as accelerate application speeds, improving the productivity of remote employees. The team’s goal was to develop an easy to manage product capable of scaling across networks of all sizes and applicable to the WAN computing needs of a wide range of industries. One of the first steps the team made was to pitch their rough idea to a few venture capital (VC) firms, which helped flesh out a strategy that targeted the enterprise customer segment. Next, they conducted interviews with prospective customers to gauge interest in the product. The feedback they received from large enterprises was that business-critical network solutions would never be trusted to a start-up. The threat of disruption to dedicated systems core to business operations—for example, a bank’s transaction processing system, or an airline’s reservation system—was too costly to contemplate. Downtime and reduced performance in these systems would be directly measured in lost revenue. As such, large enterprises were unlikely to purchase an unproven product, even though they showed interest in the technology. As a result, the team changed course and set its sights on the mid-market. According to Thayer:
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Although it was disappointing to hear that the large firms were unlikely to buy from us, the high end market was already starting to get crowded anyways. In the end, we decided to go after the mid market. We hoped to transition to sell to large enterprises once we had a proven product.
After refining their pitch, OptiGen received a term sheet for $10 million (with a $10 million pre- money valuation) from two venture firms in the fall of 2002. They closed the Series A, hired ten new employees, and moved into an office in Framingham, Massachusetts. Stone was named president and CEO, Niles CTO, and Thayer VP of products and strategy. The team spent the rest of the year continuing their diligence and developing hypotheses around a go-to-market strategy. The following year was spent developing the product. OptiGen grew to 40 employees, and by fall of 2003, it was time for another financing round. The team raised $18 million from a third technology-focused venture firm and its original investors. Customers began lining up in anticipation of the first product launch. Soon after, OptiGen’s VCs determined that the company needed someone with sales and marketing expertise to lead the company. The board hired Mark Kingston of Digital Equipment Corporation to take on the role; Stone became executive vice president of business development.
Go To Market
Working with VARS The decision to focus on mid-market companies dictated several elements of OptiGen’s go-to- market strategy. First, the entry-level product would be priced at $30,000, as opposed to the $120,000 price point appropriate for enterprise customers. Second, OptiGen would rely on channel partners rather than selling entirely direct, since the OptiGen team felt that regional resellers were the best way to address this market. Whereas direct, relationship based selling was critical to success with large enterprises, the team felt a pure direct sales model would be inefficient in the mid-market. OptiGen would need to partner with value-added resellers (VARs) to sell its products through to the end customer. The VAR’s role was to assemble and sell systems solutions for particular applications. For example, if a company needed an e-mail system that supported 1,000 people today but was capable of growing by 200 people a quarter in the future, it might work with a VAR. The VAR would help the company build the entire system, complete with servers, a network, and storage. In this case, OptiGen would provide the network optimization solution to a VAR, who would convey its features and functionality to the end customer. The team began working with WAN experts to refine the product specs and understand the priorities of their end customers. They also engaged in conversations with VARs to validate the opportunity. One challenge that the team faced was the complexity of the technology. OptiGen worried about whether the VARs would be able to articulate a highly technical message to their target audience, the IT professional. Having worked with VARs in the past, Thayer knew that the VARs would push whatever products were selling best, which could include competing products and services. He concluded, “If we wanted to sell product effectively and keep our cost of sales low, we had to keep the product simple.”
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Passing on the OEM Another decision that had to be made was whether to work with an original equipment manufacturer (OEM), who would sell the OptiGen appliance as part of their own product offerings. At first, the team believed a partner would be necessary and began discussions with one of the interested players. This particular company suggested OEMing (or rebranding) OptiGen as their low-end solution. Concerned that they were being undervalued, the team discussed the implication of such a move. Partnering with an OEM would mean sharing its product roadmap, which was a risk. Knowing they might be pushed in a direction which could compromise their potential, the team decided to pass on the offer.
CRITICAL HIRES
The founding team had decided not to make hires in sales and marketing until the company had a product ready to sell. It was now December of 2003, and the first WAN acceleration product was only a month away from release. The first of two crucial hires was VP of marketing. The team hired Carl Evans, who brought with him a decade of technical marketing experience, into the role. The second was hire was for VP of sales. The criteria for qualities needed in the new head of sales were discussed extensively throughout the team prior to making a hire. Thayer described their approach:
We wanted someone who could figure out how to sell the product, but who wouldn’t ramp up our spending too quickly. We didn’t want to burn all of our cash on a sales team that we couldn’t afford. We interviewed a few individuals from larger competitors who would have built an infrastructure that we wouldn’t have been able to support at that time; we would have collapsed under our own weight. We needed a hunter: someone who was cunning, innovative, and who would look for the angles.
Through their networks in the northeast, the team found an individual named Todd Klein who fit the bill. Klein had spent the last ten years at several different technology start-ups and was full of ideas around how to get the OptiGen product out to a broad set of end customers. After being hired, he immediately brought in two field sales reps and sent them out to test the waters.
EARLY SALES
After the first OptiGen product was released in January of 2004, Klein turned his attention to building a sales model. The early model paired a sales reps and a systems engineer (SE) together and assigned them a region in the U.S. Once a territory become successful, it was split up and the incumbent team would shift into a smaller region. Klein started by focusing on New England, as this was home to company headquarters and was also where the beta trials had occurred. During this time, the field team began aggressively recruiting VARs. Each pair was responsible for identifying, recruiting and signing VARs in their territory (as well as prospecting potential end customers). Evans recalled, “It was absolutely essential that we recruit resellers with the right set of skills.” These skills included the ability to configure and demonstrate the product in front of an audience. Once a VAR signed up as a partner, OptiGen provided marketing material
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and training sessions to get the channel partners comfortable making product presentations. It typically took three to four months to do the sales, technical, and demo training and ramp up the VAR on sales calls. Over the course of this period, OptiGen spent up to $20K on travel expenses for each of its field teams. Evans explained:
This was part of taking care of our VAR network. It was really important to feed and train our VARs so that they would become self-sustaining. For every ten VARs that we trained, seven or eight would drop away unsuccessful. They would produce a single deal and then walk away; we would never see them again. The other two or three would flourish and be successful. We had to show the VARs how to sell the product (and also show them the money) in order for them to continue to chase it.
Boundaries were set around the VARs in order to keep things running smoothly. When a VAR had a potential sale, they would register the deal into the OptiGen CRM system and would receive a 40-point discount for doing so, if the opportunity was not already registered by another VAR. VARs who made sales without registering them in the pipeline received a smaller discount of only 15 points. This essentially blocked VARs from chasing the same deals; it also provided data that could be used in forecasting. As the channel started to ramp up, Klein’s field team split their time between working with VARs and reaching out to customers for direct sales. Sales reps were paid on net revenue to OptiGen, so there was an incentive for them to take deals direct rather than give the 40-point discount to the VARs in their territory. For example, if a $50,000 deal went through a VAR, the rep would get credit for $30,000 against his quota. If the rep took that same deal direct, however, he would get the full $50,000 credit minus any direct discount that was negotiated (with an order this size, a 15 point discount was typical). This created channel conflict that became increasingly disruptive as the size of the channel grew. The attractiveness of the indirect model economics depended on the productivity of the VARs. Because VARs sold a range of products, they typically had a wide network of customers to call on. That said, they often carried other WAN acceleration products beyond OptiGen’s. Each VAR would register an average of two customers a week. Typically only 25% of all deal registrations would close, most often with the support of OptiGen sales reps. Reps qualified the opportunities registered by the channel partners and visited those prospective customers with the highest potential. Reps also collaborated with the channel partners to host various marketing events in order to generate leads. Reflected Evans:
During this period the OptiGen sales reps were two times more effective than the VARs at closing a deal. When customers had objections or competitive positions, our people would usually have to drive the deal to close from that point on. Only a few of the national VARs could close like that.
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The drawback to the field sales was cost: the fully loaded cost of a sales rep was $250,000; that of a SE was $200,000. During the first few years selling product, the percentage of revenues that came from direct sales topped 40 percent. Sales reps were being proactive about registering their own deals, but were less eager to get out in front of the VARs in their territory to help prospect for customers that they would not get full credit for. In the first two quarters of selling product, OptiGen saw early penetration in a few vertical markets, including small financials (regional banks and credit unions), hospitals, and government offices. The average transaction size was $40,000. Klein hired another two field reps, bringing the total to four, and expanded his geographical focus to include New York, Boston and San Francisco.
MOMENTUM BUILDS
By the time that OptiGen raised its third round of venture funding in the fall of 2004, it had 250 customers under its belt and claimed 10 percent of the WAN optimization market. Predicting profitability in the coming year, the start-up generated plenty of attention. Although the goal for the round was set at $18 million, it became oversubscribed within only two weeks and closed at $24 million.
Key Decisions
By this time OptiGen boasted 55 resellers, however, the relationships with VARs were spotty. Thayer recalls: “In the first couple of years the VARs weren’t making a lot of sales. Yes, we were selling through them but our sales team was doing most of the work. They were the fulfillment engine and that was it.” Sales reps felt that VARs were getting a lot of credit (not to mention discounts) for tagging along while they made the sales. At a board meeting following the Series C, management debated whether they should transition to a 100 percent direct strategy. There was also a discussion around who should be OptiGen’s target customer. Some board members suggested developing a lower-priced product and acquiring OEM relationships to go down market; others thought the company should tack on features and look up-market. The high-end market was attractive, given the large average deal size (larger companies tended to have multiple, dispersed locations and were willing to pay a premium for optimized WANs). Thayer and his team pushed back, citing the demanding product and support requirements of large enterprises. Thayer recalls: “The board kept pushing us to go up market and we kept resisting, saying, ‘Our product and support capability isn’t ready. Give the VARs in the mid- market some time.’” The board relented on both issues for the time being. In the meantime, CEO Mark Kingston―who was more sympathetic to the direct sales and up-market approach suggested by the board than to the ideas of the rest of the management team―resigned, and the search began for OptiGen’s third chief executive. Management interviewed Robert Campos for the CEO role shortly thereafter. Campos had most recently served as CEO of Tripod.com, a website hosting platform. While lacking domain expertise, Campos had experience developing channels from past roles at Lotus. Prior to meeting with management, he conducted his own due diligence on the industry, meeting with IT executives and interviewing VARs, customers, and industry
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analysts. During his interviews, he heard the board’s concern about whether OptiGen’s current sales model could scale. Their uncertainty about the future was palpable. Campos, himself, felt differently: “I was confident that OptiGen would be able to scale the business with its current channel model, based on the success it already had as a small vendor with some pretty reputable VARs.”
“Sales by the Seat of his Pants”
Campos was hired and took over the CEO role in November 2004. He reflected on the state of the company upon his arrival:
OptiGen was being managed opportunistically. If a big sales opportunity presented itself, the motto was: “let’s see if this sticks.” There was no discussion around whether the customer was an appropriate candidate given OptiGen’s product selection and available resources. Todd was incredibly hard-charging— he chased everything and was always trying to determine how we might generate more traction as a company. He was clearly skeptical of the VARS; he insisted on a high level of interaction to make sure they wouldn’t screw things up. By the time I joined the company it was still 40 percent-plus direct sales. Optigen clearly hadn’t yet committed to a core VAR sales model.
Campos recognized that Klein was running sales in an intuitive rather than strategic manner. So did Thayer: “Todd was not a strategic planner by any means. He was more instinctive than cerebral. When he saw trends, he jumped on them.” Although data were collected around repeat business on a gross level, there was no granularity to the data—for example, there was no information tracked about customers’ characteristics that would help with future sales. The strength of a VAR partner was assessed by verbal feedback from the field rep rather than through analytics. Lastly, there was no tracking of vertical market adoption, even with hundreds of customers. Klein’s style was successful in delivering strong, early company revenue growth, but it came with breakage. According to Campos, “He terrorized the marketing and support executives.” Rather than collaborate with his colleagues on the issues of which segments to target and the tools needed in order to support the sales team in doing so, Klein acted autonomously and made disruptive requests. He made promises to customers around custom support models, as well as requested special products from the engineering team. He also barraged the marketing team for endless types of collateral to sell to a wide range of industries. It was too much given the constraints of each team. Campos recalled, “He expected people to turn on a dime to respond to every potential idea he had, even though within weeks he would have moved onto the next big thing. That said, he was very good at experimenting with different segments, price points, and applications.” The new CEO was not the only person who noticed Klein’s disruptive behavior. Recalled Thayer:
Todd was impossible to collaborate with. He’d be making up new stuff while the rest of us would just be catching up. We never knew what he would do next, but to be fair, he didn’t know either. It made him look like the innovator, but it was incredibly hard on the rest of us.
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Failure to Forecast
When Campos joined OptiGen, he inherited an operating plan agreed upon by management and the board. He was disturbed to find a large deviation between the operating plan and Klein’s sales forecast. He would soon learn that the two were constructed independently and thus, had little relation to one another. He met with Klein right away to understand how he thought about developing his forecasts. Campos recalled, “He refused to commit to the company operating plan and to be accountable to a forward-looking forecast.” Klein would instead provide a lower set of numbers based on what he knew was coming through the pipeline that quarter. As the quarter progressed, he would bump up his “forecast” so that it eventually converged with the plan. The result was useless figures consistently below both the operating plan and actual results (see Exhibit 1). While Klein did not seem bothered by the deviation between prediction and reality, it wreaked havoc on the rest of the company. For example, manufacturing required a 16-week lead time for some of the costliest product components. When Campos asked Klein to give a sense of future sales beyond the current quarter, he received fuzzy numbers and a long list of excuses. The average sales cycle was a relatively short 45 days, meaning that OptiGen reps had only partial visibility into their pipelines. A common refrain from Klein was, “How am I supposed to predict accurate quarterly sales when my reps won’t even meet half of their customers until six weeks into the quarter?” After several frustrating meetings, Campos stopped trying to incorporate Klein:
I ended up taking him out of the room when we were building the operating plan. I had no choice but to make predictions based on collaboration with manufacturing and historical order patterns. We couldn’t afford for the sales team to lose orders due to a backlog situation, which would have happened if we used Todd’s numbers.
Hard to Argue with Success Internally, sales continued its haphazard progress through 2005. OptiGen’s average deal size was increasing, reaching $60,000 by the end of the year. As in previous quarters, Klein continued to sandbag. Since he was no longer involved with the process of building the operating plan, the rest of the management team had only minimal visibility into the numbers during the quarter. Thayer recalls: “It was always a slam at quarter’s end. You would have no idea how the quarter was going to close until the last two weeks.” (See Exhibit 2). OptiGen closed 2005 with nearly $60 million in bookings and 900 customers. Even though Campos knew that Klein was not adhering to the model, he found it difficult forcing a change in behavior:
I was uncomfortable with how Todd operated but it was hard to challenge a sales executive who is achieving these great results. He wouldn’t give clear commitments to the plan and it was painful to get him to participate in the annual planning process. But he was growing the team and growing the base of business. It was tough to argue with success.
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Thayer agreed that Klein was doing his job but also had concerns about his long-term role at the company: “As a leader of a small team, he was able to manage the chaos. But we would never have been able to scale his approach.”
THE FIRST BLIP
Sales appeared to be slipping when the board met during the second half of March 2006. OptiGen had never missed its plan and this was especially bad timing for it to happen for the first time. Given a prospective IPO at the end of the year, it would not look good if sales went off track. When pressed, Klein replied: “We’re slower than usual but the pipeline is strong. Don’t worry, we’ll make the plan.” Ultimately, the quarter closed $3 million below the $19 million set by management. Campos was livid:
I asked Todd what happened and he told me it was because of a product delay from the previous quarter. However, we had warned the field sales team about the delay that December, so this could not have been the reason. Then he continued, saying: “The VARs are awful and the competitors have figured us out. Cisco and Juniper have a playbook on us and they’re coming after us.” It was evident from all the excuses that Todd didn’t understand the root of the problem.
THE IPO MARKET
Technology IPOs had been few and far between during the prior two years. Industry and competitive dynamics played a large role in determining when companies went public. This had always been a goal for OptiGen, though discussions grew more serious in early 2006 when Riverbed Technology, a peer network acceleration company with similar growth dynamics to OptiGen, filed its S1. Like OptiGen, it was not yet profitable. When Riverbed debuted on Wall Street ―the first network and storage infrastructure company to do so in more than two years―it opened far above its anticipated offer range. The window for OptiGen had opened; yet everyone knew it would not remain that way forever. Campos began to prepare his team for meetings with investment bankers. Although the press was applauding the company for its impressive year- over-year growth, things looked far less rosy on the inside.
Marching Toward IPO
Despite a rough start to the year, the second quarter of 2006 closed with a bang (see Exhibit 3). Industry analysts called OptiGen a rising star in the WAN optimization market, which was predicted to hit $1 billion by 2008. At a company-wide meeting in June of 2006, Campos boldly announced that OptiGen would go public that year. He recalled, “To go public we had to have confidence in the scalability of our model. We also had to be hitting our plan. We believed we could get there.” The company began the process of meeting with investment banks.
Lesson Learned In the meanwhile, the IPO market remained highly active. Isilon Systems, a network attached storage company, had made a big splash going public in March of 2006.3 On its first day of trading, its shares soared from a $13 offering price to more than $23. With a smaller revenue 3 IPO timing altered for case purposes.
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base and lower gross margins than OptiGen, its successful debut boosted OptiGen’s confidence. Both investors and employees were buoyed by Isilon’s success; the mentality became, ‘If they can do it, we can too.’ However, to everyone’s surprise, Isilon missed its first quarter after the IPO. Its value on the street took a hit, but it was essentially forgiven based on the promise of quarters to come. Unfortunately, it missed its second quarter as well. This time, Isilon was hammered. The company lost 36 percent of its value for not being able to execute on its sales commitment. The value of the stock depended on growth, so top line results mattered most. OptiGen was in the midst of interviewing with investment banks when Isilon tanked. Recalls Campos, “When the bankers saw our miss in Q1 they ripped us a new one. They needed confidence that we were going to be able to continue to grow at a rate that justified an IPO premium. They wanted to be able to model us.” At this point, it was not obvious that OptiGen could even model itself. It was one thing to make estimates of the upcoming quarter, but when the bankers asked for management’s expectations for multiple quarters post-IPO, the team started to panic. The stakes had gone up.
THE SECOND BLIP
Unfortunately, OptiGen’s third quarter also came in under plan. Although the miss was not as big a surprise as in the first quarter, it presented a huge set-back. The company now had a saw- tooth track record, another indicator that the sales model was haphazard and unpredictable (see Exhibit 3). Campos began to seriously question whether Klein was the right person to head OptiGen sales. Klein’s unwillingness to plan had become increasingly disruptive as the company grew and the two quarterly misses had caught everyone off guard. As Thayer recalled, “When we were small, it was okay because we all caught up. But once we got big, we needed rigor. Todd caused chaos throughout the company.” That said, firing the head of sales was sure to cause its own ripples throughout the company. Some sales reps would undoubtedly leave with Klein, and others would lose focus without a clear leader. With a gaping hole in the management team, who would be responsible for hitting the aggressive sales targets in the new year? As Campos weighed his options, Thayer admitted, “It would have been gusty to remove Todd. It’s not that we were failing; we just weren’t reaching our full potential.” Perhaps most importantly, a spotty forecasting record would not pass muster on Wall Street. One board member gave Campos a sobering assessment: “You have ruined the company; we’ll never be able to go public now. We have no choice but to sell.” It was hardly encouraging. Campos knew that if OptiGen wanted a shot at going public, it would need more rigorous planning. Campos needed to come up with a plan for building a scalable organization that could deliver consistent and predictable growth. He also had to fix the forecasting system. The bottoms-up forecasts that Klein had presented failed to account for prospects outside the pipeline, and thus, typically fell below actual results. Campos reflected:
At this point we had basically given up trying to forecast. We were reactive: we added heads based on lagging not leading indicators, and we were forced to fire up the supply chain at the last minute to meet surprises in demand. This was okay for a small private company but wouldn’t fly for a public one.
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A New Model
OptiGen had matured to the point at which it needed a predictable sales model to support its growth. Given its short sales cycle, the company needed a more forward-looking approach. Hoping to engineer a model that would pass muster for the bankers, Campos began brainstorming a list of leading indicators that he thought might help predict future sales. Beyond partners (Exhibit 4), he added data around customers (Exhibit 5), deal registrations, sales FTEs, and the sales pipeline (Exhibit 6). This was a different approach to sales than Klein had employed bringing a new product to market. The bottoms-up forecasts that Klein had presented only accounted for deals that would close imminently and ignored prospects outside the pipeline and thus, typically fell below actual results. Campos knew he would need to provide realistic forecasts, as the operating plan (which would soon be all over Wall Street) now depended upon it. He recalled a warning from one of the analysts:
If you come in and give me a low-ball forecast and then kick butt on your earnings every quarter, I am going to know that you are sandbagging me. I want you to know that if that happens, I will penalize you for the next six quarters.
For the exclusive use of F. Eldemir, 2018.
This document is authorized for use only by Fahrettin Eldemir in 2018.
OptiGen E-359
p. 13
Exhibit 1 OptiGen Quarterly Financials, Q3’04-Q3’06
(in Thousands of $)
Qtr. Day 1 Operating Plan Day 1
Forecast Final
Bookings
Q3’04 $4,000 $3,500 $5,030 Q4’04 $6,400 $3,500 $6,643 Q1’05 $8,800 $7,230 $9,981 Q2’05 $10,800 $8,521 $14,002 Q3’05 $13,200 $10,066 $15,450 Q4’05 $15,400 $13,127 $17,950 Q1’06 $19,000 $15,033 $16,300 Q2’06 $23,500 $18,640 $24,250 Q3’06 $25,000 $20,100 $23,500
Note: Data has been altered for the purposes of confidentiality.
Exhibit 2
Note: Data has been altered for the purposes of confidentiality.
27.7%
37.1%
27.4%
13.9%
25.9%
33.5%
43.4%
33.9% 34.0% 34.6%
47.5% 48.3%
42.9% 43.7% 45.3%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
05Q3 05Q4 06Q1 06Q2 06Q3
End of Quarter Business
Final Week Last 2 Weeks Last 3 Weeks
For the exclusive use of F. Eldemir, 2018.
This document is authorized for use only by Fahrettin Eldemir in 2018.
OptiGen E-359
p. 14
Exhibit 3 Quarterly Bookings History, Q3’05-Q3’06
(in Millions of $)
Note: Data has been altered for the purposes of confidentiality.
Exhibit 4 OptiGen Historical Data, Q3’04-Q1’06
Quarter Pre-existing VARs New
VARs
Total Partners Signed*
Total VARs with sales in
current periodActive* Inactive Q3’04 35 5 15 55 49 Q4’04 49 7 18 74 65 Q1’05 65 12 34 111 98 Q2’05 98 28 37 163 111 Q3’05 111 51 57 219 129 Q4’05 129 78 69 276 123 Q1’06 123 133 72 328 165 Q2’06 165 150 88 403 178
* Partners signed references the total number of resellers that had signed contracts with OptiGen, whereas active partners represents those partners that had booked sales in the previous quarter. Note: Data has been altered for the purposes of confidentiality.
$0 $5 $10 $15 $20 $25 $30
Q305 Q405 Q106 Q206 Q306
For the exclusive use of F. Eldemir, 2018.
This document is authorized for use only by Fahrettin Eldemir in 2018.
OptiGen E-359
p. 15
Exhibit 5 OptiGen Customers, Q3’04-Q1’06
Quarter Pre-existing Customers* New
Customers Total
Customers Q3’04 185 60 245 Q4’04 249 141 390 Q1’05 283 138 421 Q2’05 327 244 571 Q3’05 330 252 582 Q4’05 442 440 882 Q1’06 463 480 943 Q2’06 502 520 1022
* Pre-existing customers are those customers who have purchased product in previous quarters. Figure is calculated at the end of the previous quarter (or beginning of current quarter). Note: Data has been altered for the purposes of confidentiality.
Exhibit 6 OptiGen Historical Data, Q3’04-Q1’06
QTR Deal Registrations Sales FTE* Funnel (Pipeline)**
Q3’04 70 6.00 $28,327
Q4’04 190 7.25 $37,444
Q1’05 602 9.75 $48,973
Q2’05 898 12.50 $66,564
Q3’05 1,299 14.25 $79,342
Q4’05 1,643 15.75 $91,523
Q1’06 1,532 18.00 $113,199
Q2’06 2,492 19.25 $145,662 * Net sales FTEs are calculated with the assumption that reps reach 50 percent productivity in their first quarter, 75% in their second and 100% in their third. Figures are cumulative and represent the total at the start of the given quarter. ** In thousands of $. Note: Deal registrations represent the total number of deals entered into the OptiGen deal registration system in each quarter. Funnel (or pipeline) represents the value of every deal that the sale organization captured in the CRM system as future potential business in each quarter. Like Sales FTEs, funnel is calculated at the start of the quarter. Note: Data has been altered for the purposes of confidentiality.
For the exclusive use of F. Eldemir, 2018.
This document is authorized for use only by Fahrettin Eldemir in 2018.
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De gemaakte PDF-documenten kunnen worden geopend met Acrobat en Adobe Reader 5.0 en hoger.) /NOR <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> /PTB <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> /SUO <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> /SVE <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> /ENU () >> >> setdistillerparams << /HWResolution [600 600] /PageSize [612.000 792.000] >> setpagedevice