The Pain Point
WalkMe solves the problem that you only fully understand when you have spent thirty minutes on a website trying to extend your wireless contract or change your cable bill, only to give up in frustration and a phone call to an agent. With WalkMe, the software finds you, the user, while you are struggling on the website and provides a step-by-step guide, called a Walk-Thru, which moves with you through the website, guiding you on how to get the task done.
Many websites are not intuitive and, as much as every website would like to be Google, with a simple search bar and a single user experience, handling the banking or telecom needs of 50 million customers does not allow for the same simplicity. With many potential paths through a website, the designer has to optimize for the basic tasks, meaning that many other tasks, important to hundreds of thousands of customers, get lost in the third menu bar. The result is confusion, lost customers and expensive calls to a human operator.
The Way Things Should Be Done
When I first saw the Walk-Thru technology, I had the instant response that “yes this is the way things should be done.” I don’t want to over exaggerate or channel my inner Malcolm Gladwell Blink reflex, but I have learned that for technologies that want to straddle the business/consumer divide, the first reaction on seeing the technology should be a strong sense of relief and the thought that “finally someone has solved a problem that has been sucking energy out of my day.” I felt this when we saw Box eliminate the need to move files between home and work, and I felt it in spades when the Docusign app removed the need to ever print out a signature page again. While I may be colored by the miserable experience on the Comcast website (two domains for one transaction), I feel that WalkMe is a must have for complex transaction focused websites. Don’t tell me what to do via an FAQ, carry me over the line!
The product also works really well for corporate SaaS applications. Another personal example: At ScaleVP we have a heavily customized version of Salesforce that we use for all our deal tracking. Every time we add a field, we increase the likelihood that someone (usually a GP) fails to fill it out correctly. By adding a customized Walk-Thru that we built ourselves, we were able to guide the user to fill the data in correctly. We were even able to make sure that if key fields are not completed the record cannot be entered. This opens up the market for WalkMe to every customer of Salesforce, and any other widely deployed SaaS application that needs end-user guidance.
We are very impressed by the traction. In just six months of selling in the US, WalkMe has already landed such customers as Adobe, Amazon Web Services, Bank of Montreal, Cisco, Citrix and Kimberly-Clark. The founding team is strong technically and the core technology IP around element identification is well done. This is one of those classic technologies where it is really hard to make a tool that is easy to use but WalkMe has executed beautifully. I am delighted to be part of the WalkMe team and look forward to seeing them Scale.
During the last ten years, while venture capital was supposedly dying, the venture backed companies that went public or got acquired in that decade, achieved a combined valuation of $1.25 trillion as of Dec 31st 2013. Today, I wrote a column for Re/code explaining this. Check it out here. This companion post has the detail backup and an explanation of how the companies are categorized.
Here is the complete list
What the Categories Mean
We divided all Companies up into the three obvious sectors based on where venture capital dollars flow: Information Technology, Healthcare and Other. Within IT, we think about businesses in terms of who is the customer, broadly defined. We have observed over the years that while technologies change, customer categories are more persistent. The CFO who bought mainframe financial software thirty year ago, SAP software fifteen years ago and Workday today, is the same person with the same purchasing process, despite all the technical change to the product. The process is still sales call, product review, Proof of Concept, Considered Purchase etc.
IT Categories Based on who the Buyer Is
We see four buyers types within the overall IT industry: the Enterprise IT buyer, the Enterprise Line of Business buyer, Individual Consumers and the Components buyer. Enterprise IT and Enterprise Line of Business are fairly straightforward Categories. IT buys databases, routers and PCs and the Line of Business buyer buys applications. The total of these two buyers is the overall Enterprise Technology business. In one sense Consumer is a misleading title. Most companies in the consumer category generate revenue by selling advertising against free consumer eyeballs, and thus strictly speaking the consumer is not the customer, the ad buyer is. However, we believe the core competence in an internet consumer company is the acquisition of vast numbers of end users by offering a compelling consumer product. Once you have done that, the monetization is fairly straightforward. So, while the “buyer” is not an accurate description, practically speaking it conveys the idea that the value is created for the company by attracting and pleasing the consumer. Finally, Components companies typically sell to a deeply technical buyer, building an electronics product that will embed the component, with either no attribution or at best an “Intel Inside” moniker. Most of these are semiconductor companies.
Dividing IT up Further
Within some of these Buyer Categories we have done a further analysis. While at first it felt like overkill, we found that we wanted to know the answers to questions like, “are the big wins in Enterprise IT Hardware companies or software companies?”. Thus for Enterprise IT, we broke it out into software/services companies on the one hand and hardware products on the other, recognizing that the distinction is not hard and fast – because everyone wants to say they are a software company. The answer BTW is hardware and software exits above $1BN are about equal in quantity over the past ten years. For Line of Business, we wanted to know how dominant SaaS is ? We broke out the companies into SaaS vendors and the rest. All but 2 were SaaS. Within the Consumer market we broke the companies into Ad Supported Models, Marketplaces and a few other categories. Almost all the value has been in large ad supported consumer focused internet companies which took the number one, two, three and five slots across the entire venture industry for the past decade.
The consumer category and subcategories is where is where you see start to evidence of “disruption” of the non tech economy. Consumer internet ad supported companies are taking old media ad dollars, marketplaces are taking share away from old ways of purchasing rental houses. In the next decade here is where companies like AirBnB and Uber will show up. This is the “Digital Disrupts Analog Trend’. It shows up as companies, focused on either the Consumer or Line of Business, that are not selling technology but instead using technology to disrupt an existing business. Many consumer facing businesses have already been disrupted but B2B has not seen the same effect. It will be interesting to see if that changes.
Comments welcome, and in particular any missing names. We run this exercise internally and call it the GED, the Great Exit Database. Don’t want to miss anything.
Words You Don’t Hear in Venture; “Great it’s annual planning time!”
In the next two months, I will sit through seven annual planning board meetings. It’s a grind but an important one. Once a company has revenue, “making the numbers”—like it or not—becomes the shorthand by which management is judged. Scale is getting together with a number of our CFOs this week to talk about the best ways to make the annual planning process more effective. Going into that meeting, this is my list—written from a board member perspective—on what I would say to CFOs about how to get a board member to an informed “yes” to approve the annual plan.
Start with the Big Picture
Provide some context on what the company is trying to achieve in the next year. Spend time with the CEO on this. What—from a business perspective, not a purely financial perspective—is the company trying to achieve? The financial plan should map to these goals and should be judged in that context. Don’t assume your board grasps the big picture; spell it out.
If the CEO and CFO cannot provide two or three clearly articulated business goals for the next year, the planning process is doomed.
Show the Assumptions
Show the key assumptions that drive the plan. For example, in an enterprise software company, sales rep productivity is almost certainly a key metric. Show the average rep productivity metric for the past two years and spell out the improvement you are assuming in the FY14 plan. Do the same for all the key metrics. As a board member, the question in my mind is always this, “What do I have to believe will stay the same, or get better, to believe in this plan?” Your job is to make it easy for board members to answer this question.
Simplify the Assumptions
Keep the assumptions simple. A good plan will include lots of detail because teams need detail to get the plan right. However, to have a meaningful conversation with the board, reduce your plan to a small number of key drivers. Boards don’t like to see just the financial statements and a 10MB model. Instead, show them ten key assumptions for FY14 and, for context, provide the actual results alongside each assumption for FY12 and FY13.
Use the Company KPIs
The assumptions you lay out in the annual plan should be the same metrics that the operations/sales team uses to manage the business. That way, the team is fluent with the metrics and becomes progressively more comfortable as they use them throughout the year. If the finance team establishes KPIs but the rest of the team doesn’t use them, the budget becomes divorced from the reality of the business. The more you are aligned on metrics, the more you can push responsibility down in the organization.
You can predict costs with precision but revenue, not so much. Instead, you have to apply judgment to the revenue calculation. Board members find it helpful to understand the thought process that led to your revenue estimate. Suggestions include showing how to bridge revenue from last year to this year, doing multiple cross checks on the revenue build up, and providing some clarity around level of “slack” inserted. Every board member is trying to get a vision of how you will make your number. It’s your job to help them get there.
GAAP revenue is a trailing metric. Most companies will also use a forward-looking metric such as MRR (monthly recurring revenue), bookings, ACV (average contract value), or TCV (total contract value). Pick a single metric and work really hard to ensure that it is used consistently. Nothing is more frustrating than to have a metric in finance that the sales team simply ignores. Pick one and make it stick. If sales commissions are not based on it, it is not a real metric.
Mind the GAAP Gap
We prefer startups use metrics such as MRR or ACV because these measures take “unit of time” into account. Metrics like TCV can be distorted by multiyear bookings and you end up with a “GAAP gap”. This GAAP gap occurs when great bookings traction fails to materialize as GAAP revenue. After seeing this phenomenon many times, we’ve learned to monitor carefully how quickly a bookings metrics shows up as revenue. If bookings don’t lead to revenue, we know something is wrong with the model. Finance should always be checking for a GAAP gap.
Show a headcount chart across the key functional areas with the headcount adds by quarter. People are expensive. If revenue is not tracking, the least painful way to slow down the cash burn is to adjust the rate of new hires. It’s important to understand what the options are to manage headcount.
Show the expenses in the SEC/Accounting major categories: COGS, Sales and Marketing, R&D, G&A. It can also be helpful to see a simple list of the expenses classified by type: i.e. total salaries, total rent, marketing programs, etc but don’t provide these expense types without also showing them in the major accounting categories.
Marketing to Sales Sanity Check
You must have some simple math to explain how deals move from the top of the funnel all the way to closed deals. Don’t keep it a secret. And, make sure that marketing and sales agree on these assumptions and use them consistently. It is stunning how often I notice a disconnect between what marketing expects and what sales requires. As a high level sanity check, compare relative growth of marketing program dollars to the total volume of new sales required.
As a company matures, it can be helpful to think about the annual plan as a plan for several businesses under a larger umbrella. Some are in scaling mode, typically the core go-to-market business in North America, while others are new go-to-market initiatives, almost certainly consuming net cash. If your company is making an investment in international expansion or in a channel overlay strategy, call this out separately and explain how you will measure success.
Know Your Total Cash Needs
Any annual planning process will result in one of three outcomes on cash:
In all but the first scenario, you need as the CFO to have an answer to the following question, “How much does the company need to raise to reach cash flow breakeven?” It requires a multiyear plan. The plan will not be accurate but the alternative—no plan at all—is worse. When you end your presentation saying, “We exit this year with a $15MM burn and $5MM in the bank,” you leave the board hanging like a bad TV serial drama. State to the board exactly how much cash you need, in total.
Multi-Year Planning and Mid-Term Revisions
The big decision for most technology companies is how much to invest in sales and marketing. One reason for this challenge is that there is an inherent lag between when you invest in these functions and when the business starts generating revenue. We’ve seen a fairly consistent planning bias: companies show aggressive investment early on in the year and then taper off of investment to get to cash flow breakeven. The “cost” of under investment in sales and marketing—lower revenue growth—does not show up until the following year.
One way to highlight this issue is to do a multiyear projection as discussed above. Another way is to decide to have a mid-year check-in. If the company is tracking well, you can decide to green light more investment. If you are face challenges or if capital is scarce, you stick with the original plan.
Aim to be succinct. It should take you only 5 to 10 slides, max, to lay out the assumptions, do the revenue build up, and show the headcounts adds. After that point, you lose everyone’s attention. Once you’ve gone over these topics, show the basic financials by quarter for the planning period and perhaps a multi-year profit and loss statement covering both historical numbers and one to three years of projections. Everything else can go in the Appendix.
The list of items people could ask to see or might find useful is long. This is why some annual plan presentations take forever. Here is a partial list of information that gets requested:
I’m not saying that if you follow these steps, the annual plan review process will be painless. By taking this advice to heart, however, you will be more prepared for the questions you will receive and, likely, more confident in your delivery.
We are excited to announce our investment in Chef. The investment thesis is simple: every company in the world runs on software and—to survive—every company in the world has to run faster. This creates a massive need to speed up the process of developing and deploying code and, in turn, has led to the “DevOps” approach to developing applications. The idea behind DevOps is simple: if Development (the teams that write the code) can work more closely with Operations (the teams that run the resulting systems), they can deploy projects faster with fewer errors. This arrangement works; a DevOps-centered methodology is clearly the way of the future.
Chef Makes DevOps Possible
The Chef automation platform helps organizations switch to DevOps by enabling IT operations and developers to describe, model, and automate infrastructure as code. The Chef automation platform uses cookbooks (reusable code definitions that are written using the Ruby programming language). Each cookbook defines a scenario, such as everything needed to set up and configure a postgresql database together with all required components (templates, versions, metadata, etc.). There are over 1000 cookbooks, including those for databases, operating systems, applications, networking, and monitoring.
Armed with a cookbook, an IT management team can do everything from installing an operating system, to installing and configuring servers on instances, to configuring how the instances and software communicate with one another, simply and efficiently.
The following diagram illustrates how Chef works:
How Big is the IT Automation Opportunity?
The need to automate IT is not new. The IT systems management market has been around as long as the IT markets itself. In fact, every new IT architecture, from mainframes, to minis, to client server to web, has produced a crop of successful systems management companies. However few—or none—of them have been able to make the transition from an old architecture to a new architecture. They’ve either had to purchase to advance or have declined in relevance.
We believe that there is another architectural shift happening today in IT and so do the analysts per this Forrester Report. What’s changing now is not the underlying hardware, which has been commoditized servers for the last 10+ years, nor the interface to the end user, which will remain the browser. Instead, the shift is involves where hardware is deployed and how larger systems are put together.
Quantity has a quality all its own, (attrib. J. Stalin). The sheer quantity of servers under management, and the sprawl of those servers within the enterprise and on cloud deployments, makes the old way of running systems untenable. There are not enough sys admins alive to staff every IT company on a 100:1, servers to sys admin, ratio; existing datacenter solutions like HP-Opsware, or BMS-Bladelogic, to name two of the most successful products built in the early 2000s, just can’t handle this challenge. Throw in the need for faster change management and the problem becomes even more acute. The only solutions for this management problem are a DevOps approach and tools like Chef. Again see point #7 in the Forrester Report.
The IT Systems Management is a $9Bn/year market. We believe that a significant percentage of that market will move to a more robust—yet simpler—configuration and automation solution available from vendors like Chef. We are excited by this opportunity.
We like Chef’s team led by CEO Barry Crist and founder Adam Jacob. I will also stop to remember a core member of the Chef team, former CEO, Mitch Hill. Mitch passed away last week. I did not know Mitch—he was not CEO when we made the investment—but comments from his long time colleagues consistently describe him as a genuinely great person as well as a successful business leader. He and his family are in my thoughts as I write this. There is nothing that can be said that really ameliorates a loss like this. What we can do, however, is pay tribute and respect to the work he did to get Chef to the success and value it has today.
Scale is looking forward to working with Chef to build the systems management company of the cloud decade.
Today marks the announcement of our investment in Bill.com, a provider of integrated bill payment, invoicing and cash flow management solutions for small businesses. There are certain characteristics we look for in an investment and Bill.com proved to be a perfect fit for ScaleVP. Here is what gets me excited about this deal:
1) The need for the product
I was CEO of a start-up. The job I hated most was the job I had to do the most, especially when times were tough, juggling cash to stay alive. I would sit there at night, trying to figure out when cash would come in and what bills I could afford to pay. “If those guys pay me Friday, I can cover wages and three vendor invoices, if they push until Tuesday, I can only cover wages and one vendor. What should I do?” I would work with my CFO, write notes, make contingency plans, and then have it all upset when I had to pay an unexpected bill at the last minute.
Every startup CEO or CFO knows this dance and knows what a vital but broken process it is. Vital because while businesses are ultimately scored based on Profit and Loss, they survive every day based on Cash Flow. Broken because random spreadsheets plus sticky notes to the CFO are a band-aid, not a solution.
You might think that an accounting package or even a budgeting package solves this problem. If you have tried either solution, this is where you laugh derisively. Juggling near in cash falls squarely in the gap between accounting – which shows you what has happened, and budgeting, which shows you what should happen over the next year if everything goes according to plan. Neither product can help you figure out what bills are approved, whom to pay next week and what to do if the customer only pays half of what they promised.
2) The Bill.com solution
Bill.com solves this problem. The service allows a small business CEO, or finance team, to plan out when bills are paid, set up the approval process and then make payments as cash is received. For larger companies the service can set up internal approval mechanisms, so that individual managers, who would never get access to the accounting system, can approve vendor payments based on having verified the work done. Using the Internet, companies can collaborate with suppliers and customers to more quickly sort out queries on bills, with the result of getting paid quickly. Once a company tries the product, it will never go back to paper.
We love to invest in companies that simplify complex broken business processes. We especially love to solve problems that every business faces because that is how to build a big enterprise software company. Box made file sharing simple, Docusign eliminated the need to ever fax a signature again, and now we believe Bill.com will eliminate the need for CEO’s to stay up at night and write multiple “what if” plans to keep vendors from shutting them off.
3) The team
We like the team. CEO, Rene Lacerte, lives this stuff. A successful serial entrepreneur with a family background in the financial software business, he has lived the reality of the problem he is solving. When you talk to him about the product, it is not a theoretical discussion but a practical one about how to make the life of the CEO or CFO better. Around him he has assembled an experienced team of executives, some from his prior company Paycycle and some from other great SaaS companies like Salesforce.
4) The Timing
Now is the time for Bill.com. It is stunning that ten plus years after consumers got online banking and Fortune 1000 companies got multi-million dollar treasury management systems, most small businesses are still doing this by hand or by building a spreadsheet off the accounting system to track cash. The reason is part technology and part distribution. It is really expensive to reach small businesses at scale (pun in part intended) but we have been fortunate to have in our portfolio companies like Ring Central and Hubspot who have solved this and successfully reached thousands and thousands of SMB customers. We think we know how to make this happen and the timing for Bill.com feels right. Partnerships are key and the company is seeing strong interest from financial institutions (Bank of America, Fifth Third and American Express all invested in this round), software companies and accounting firms to distribute the product.
5) The Upside
Bill.com is really focused today on the small and medium sized customer but we would not be surprised to see them grow upmarket over time. We have seen over and over again that the “adoption cycle” for great SaaS products starts with small businesses using the product and enterprises sticking with prior solutions, but that over time, the elegance and simplicity of the new solutions results in adoption moving upmarket. In fact, we are seeing this so frequently, that is the theme of our next Scaling Dinner, taking place this week and featuring Lesley Young of Box and Zack Urlocker formerly of MySQL and Zendesk.
Salesforce has been the biggest beneficiary of this, and is now signing single deals in the multi millions. Many of our portfolio companies have seen the same upward tug and we would not be surprised if Bill.com was to see it too. The focus would probably be less on cash juggling and more on workflow and authorizations but the core engine is the same.
We are delighted to be investors in Bill.com and we look forward to a world where Bill.com ensures no CEO or CFO spends their evenings juggling cash projections on a sticky note or a jury-rigged spreadsheet, leaving more time for the important stuff…new products, new customers or even more time with the family.
If you’re involved in enterprise IT you’ve undoubtedly seen one of Gartner’s “Magic Quadrant” charts. They cover everything from security software, to business intelligence, to data center networking. In every Magic Quadrant, you find the most attractive companies—the visionaries and market disruptors—in the top right hand corner. Vendors refer to these charts to explain their market opportunity; prospective buyers use them to select vendors. Gartner does not decide the future of technology, but the firm certainly documents it. The significance of Gartner’s work is why the recent Gartner Magic Quadrant chart on Infrastructure as a Service (Iaas) market should terrify the shareholders of companies such as HP, IBM, and Microsoft:
I believe this chart is the most important chart in enterprise IT. It covers the new trend of IaaS, where instead of buying storage, operating systems, deployed applications, and other infrastructure, enterprises rent these products from vendors in a low risk pay-as-you-go system. It is a new way of doing enterprise computing.
There’s Only One Winner
Two things make this chart important. The first is the sheer size of the market. We are not talking about a specific vertical or a single technical use case. We’re talking about “where and how enterprise computing is done.” Computing infrastructure is the $150B a year “Big Kahuna”, where all the money changes hands, and where companies from Microsoft, to IBM to HP make all their profits.
What makes this chart scary is the second key takeaway: if IaaS becomes the dominant computing model, Amazon Web Services is the only possible winner. It cannot be emphasized enough how stark this chart is. As an IT investor, I have seen myriads of these charts over the past twenty years. The usual format is to show ten companies, give or take, tightly clustered in the upper right quadrant and across the other three quadrants, with highly nuanced relative positions. Since Microsoft dominated the operating systems market, I cannot recollect seeing such a stark and clear Magic Quadrant for a market already worth an estimated $4B and growing extremely rapidly.
Will IaaS happen for the enterprise?
What is still not clear is how much market share IaaS will take in the enterprise? Will it be 5%, 20% or even 80%? That is not yet clear and all caveats apply: infrastructure investments might not occur this way, enterprises may be slow to adopt IaaS, and the cloud could prove to have too many security issues. Even if IaaS does happen, established vendors already offer private cloud offerings and managed hosting products that replicate some of the IaaS advantages, but with a more controlled, enterprise friendly face. If all else fails, it’s possible that the cash-rich IBMs, Microsofts and SAPs will acquire companies and catch up to the market disruptors.
Even in light of these possibilities, it feels like we’re in the middle chapters of a classic Innovators Dilemma story. AWS is cheap, flexible and evolving fast, with no ties to an installed base. In every platform shift, there are valid reasons why the incumbents should survive but, over time, the power of cheap, the power of flexible, and the power of new, sucks up all the profit dollars. I don’t envy the incumbents here. My gut tells me we are looking at the NCR, Bull, and DEC of tomorrow— great companies living off a residual of the past that got left behind in a platform shift.
Scale Ventures Partners’ Role
As VCs, we are in the revolution financing business, so revolutions are good for business. Right now we are looking for more companies that are poised to take advantage of this shift and even help accelerate it. Recent investments like Boundary, and PubNub assume a cloud based infrastructure and are working to improve it. Companies like Datastax build big data clusters that implicitly assume hundreds of additional servers can be spun up in the public cloud if required. Investments we have pending and the deals that we are evaluating today are all about taking AWS and adding the services that will make it enterprise grade. As we build our team, we are looking to add people who understand where the world is going and how starts up will profit from this shift from on-premise resources—and major capital investments—to a more flexible, incremental investment model.
We are huge believers in the nail it before you scale it doctrine, expounded most cogently by Steve Blank. We also believe that once you nail it, you have to scale it and scale it quickly; that is where we come in. We like to invest in innovative technology companies, after product market fit has been established, a go-to-market channel has been solidified and early customers are happy. By that point, a company is ready to scale. On average our companies have grown revenues 92% in the year after our investment.
We have learned that there is no magic moment when the answer to “can you scale?” is obvious. Instead we have seen that, just as establishing product market fit is a process of discovery, so too is scaling. The scaling plan at $1M can be adding two telesales reps, at $10M adding field sales and at $100M, adding international and getting channel leverage. In every case what we are looking to understand is a roughly predictable relationship between adding sales and marketing expenses and seeing revenues grow– usually with some lag. As long as that relationship is understood, it pays to invest aggressively to build winners.
We have been fortunate to be involved with some great companies. We aim to provide a consistent perspective on growth that can help them scale but are more than mindful that the real work is being done by the teams making it happen every day.
Check out this Infographic to see if ScaleVP is the right investment partner for you.
“Why would anyone invest in a hits driven asset class that has yielded a negative IRR for the past ten years; where there are only a few good firms, and they are not taking new investors?“
That is what is weighing on the mind of many of the LPs we met in our recent fundraise. As yet, there are clearly LPs investing in venture, including newer managers like Scale Venture Partners. I would like to think our investment performance and our engaging smiles made the difference, but no institution would have invested in ScaleVP unless it first of all believed in the asset class and had answers to the questions above. What are they seeing that others are not?
Long term returns in venture are strongly positive
It is true that the pooled mean return for venture for the last ten years (2001 to 2011) is dismal at 3.3%, (and was -2.0% as of end 2010), but it is also true that thepooled venture return for the past twenty five years (1986 to 2011), even including the last ten bad years, is strongly positive at 18.6%. This mid to high teens return is the kind of outperformance relative to the Russell 2000 index, which has returned 8.7% over the same period, required to justify the extra risk and illiquidity of venture capital.
U.S. Venture Capital Returns
End-to-End Pooled Mean Return, Net to Limited Partners
|Cambridge Associates U.S. VC Index||13.18||3.27||18.61|
| The Cambridge Associates Venture Capital Index is an end-to-end calculation compiled from 1,347 U.S. venture capital funds formed between 1981 and 2011. It is a “dollar weighted” index that best represents the aggregate return of the entire venture industry.|
| The Russell 2000 Index measures the performance of the small-cap segment of the U.S. equity universe. It includes approximately 2000 of the smallest securities based on a combination of their market cap and current index membership|
| NVCA Benchmark report|
LPs we spoke to, who continue to invest in venture, implicitly believe that the next ten years will be more like the average of the last twenty five years than a repeat of the last ten. In short, they are betting on regression to the mean, which is almost always the likely bet in investing.
Narrative Matches the Math
A bet on regression to the mean also tracks a simple narrative of the past twenty years that we have blogged about before at ScaleVP. The terrible results of the last decade are not a mysterious affliction of unknown origin, but rather the result of the stunning results of the ten years prior. The story starts with sensible levels of overall venture investment in the early 1990’s (at approximately 0.1% of GDP), generating exceptional returns (the pooled IRR for 1995 was 88%), money rushing in (2000 fund raising grew tenfold to 1% of GDP), and returns inevitably plummeting. Capital then started to leave the industry but slowly. It has only been since 2008 that the capital raised by the venture industry has returned to that 0.1% of GDP level that was so profitable in the early and mid-1990’s. Specifically, in 2012, the industry raised $20.6 Bn which is .13% of US GDP for 2012, just as in 1995, the industry raised $9.4 Bn which represented .13% of the US GDP for 1995. As discussed above that was a successful year for venture! The graph below illustrates the trend, and the comment that “there is still too much money in venture” is now simply not correct relative to GDP. The industry took a far longer time to adjust than predicted, but with a decision cycle only once every four years, in retrospect that is not surprising. The strong performance of funds in the last few years is plausible, though still early evidence that the long-term dynamics of the business are improving.
Investing in a hits driven world
Even many of the LPs we spoke to who are not investing in venture would agree with the analysis above. What LPs really wrestle with in venture is how to build the right portfolio to get that venture return. Venture returns are concentrated (“a hits driven business”) and are persistent (“only a few good names”). The risk that an LP does not get access to the right names, and ends up missing the few great companies that make all the difference, is what turns many LPs off the asset class. “If I cannot get access to Sequoia, (or fill in your favorite name), then what is the point?”
However, LPs who have continued to invest in venture have a more nuanced perspective on concentration and persistence, and thus what portfolio strategy is viable. Take the extremes. If returns were 100% persistent and 100% concentrated only one firm would make all the money, all the time. The only sensible strategy would be to invest in that one firm, or not to invest at all. If returns were 100% concentrated but zero percent persistent, such that every year only one deal makes money and it is random by fund, then the best strategy is to invest in every venture fund, every year, to be certain to get the pooled return, or not to invest at all.
Exploring the extremes illustrates the point, but most investors agree that reality is where returns are both concentrated and persistent but neither metric is close to 100%. In that world, the rational portfolio strategy is to build a portfolio with significant access to known, persistent top performers, but with enough portfolio diversification in newer managers to ensure that the fund does not miss out, if the out-performers turn out to be the newer managers. A strategy of just investing in the “five top funds” runs the risk that, if concentration outweighs persistence, an LP is under-diversified and could miss some home run winners. A strategy of investing in fifty plus venture firms is over diversification, and will likely result in underperformance if exits are concentrated in a smaller number of firms.
How concentrated and how persistent?
At ScaleVP, we have made estimates of both return concentration and return persistence. Return concentration is relatively easy to estimate, and no surprise, returns follow a rough power law with a few huge wins and many base hits. There have been 779 venture exits valued at $100M or above, in the last decade, but the current market capitalization of the top two companies (Google and Facebook) at $290Bn, equals the sum of the value of the bottom 739 exits. Miss the top eighty-six exits, (valued at over $1Bn) and you have missed 71% of the total value created.
Firm persistence is harder to measure without individual fund level data, but it is clear that some firms manage to deliver great performance for years and even decades, but some old firms, like McArthur’s old soldiers, never die, they just fade away. Because an ability to fundraise based on prior performance is a lagging indicator, firms can still raise money even with an investment performance that does not compare to newer, more focused firms. In the face of this, LP outperformance has to come in part from pruning firms as they underperform, and increasing commitments to firms that are doing well. Change is slow in venture. It is a lot easier to maintain an existing winning firm than to build a new one, but change does happen and the successful LPs are ahead of that curve.
What it meant for our fundraise
The comments above sound theoretical, but they correspond with the reality we found on the road. Our typical LP has either maintained a long term commitment to venture over the past decade, or even more interestingly, has been contrarian and elected to increase its venture exposure in the past five years when others were exiting. Most have a portfolio with a critical mass of proven venture relationships (or access to same via a fund of funds investment). Even though it is harder as a newer fund to win support from an LP with a strong existing portfolio, these are also the LPs that have enough success to maintain investment committee support in difficult times. The reverse was also true. LPs who have had a negative overall experience with the asset class, were rarely interested in adding new names. It’s just like in real estate, where you don’t want to be the best house on a bad block; for a GP, you don’t want to be the best performing GP in a bad portfolio because your neighborhood may not survive.
Our typical LP is an activist about their portfolio. Despite having a base of good names, they are believers that smaller, newer funds can outperform and are willing to take the risk of trying newer names, and then doubling down on winning firms as they prove themselves.
Finally, our typical LP knows that investing in venture is not easy and does not expect it to be. The prize is an 18% pooled return over twenty five years versus a Dow return of 10% in the same period. Accessing that return requires effort, persistence and perhaps a little luck, but it is a level of equity outperformance that is simply not readily available anywhere in the investment universe.
It takes a passionate and driven individual to be an entrepreneur, but what happens after the company is launched? How does an entrepreneur go from an idea to building a long-term successful company? As part of our Scaling Q&A Series, we dive into growth strategies and successes from our rising stars.
Describe Axcient in one sentence?
JM: Axcient puts an end to down time and data loss by enabling businesses to store, protect and access all information and systems in the cloud.
What inspired you to start the company?
JM: I actually experienced data loss at my last company. It was very painful and I realized many businesses struggle with this problem. A company has two things: its people and its systems. If you take one of those away and you don’t have a company. I decided I wanted to start a company that solved the problem I experienced.
What is the biggest lesson you’ve learned through the process of starting a company?
JM: Always think bigger. Take Axcient for example, when we started we were thinking about helping companies that were 100 employees and 500 GB, now we are helping companies with thousands of employees and 50 TB of data.
You have to challenge yourself to always think bigger than your initial expectations – it will impact decisions you make regarding positioning, operations, product architecture, etc. My recommendation is to set your expectations and then scale it by 10X and apply it across all of your planning.
What advice would you give other entrepreneurs looking to start a company?
JM: Ask yourself why you want to start a company in the first place. I actually try to deter people from starting a company if they can’t truly answer that question. A lot of folks come out of business school and can be intrigued by the “glitz and glamour” of the valley. This mentality often causes first-time entrepreneurs to fail. Successful entrepreneurs are driven by a burning desire, obsession even, to solve a problem. If you don’t have that, don’t start a company. Building a company can be rewarding if you have that drive and obsession, but it isn’t glamorous and it is anything but easy.
Axcient has experienced a tremendous amount of growth? What’s your secret?
JM: Overall, it comes down to a lot of hard work, passion and focus, but three things do stand out. First, we have been diligent on hiring exceptional people and never compromising on talent. Second, we are very metrics driven. Whether it’s sales, operations or marketing, we make our decisions based on metrics. It forces us to be really ruthless with our priorities and keeps us on path to drive aggressively towards our goals, continuously monitoring as we go. Last, it has been the restraint to not chase every opportunity. We determine what we want to pursue and doggedly pursue it.
Who inspires you?
JM: I have always been a big fan of Richard Branson. I admire the culture he has built around him; one that is open, fair and fosters innovation. Too often, people associate the ability to build a large company with being a megalomaniac and I don’t think that is true. Branson is a good example of a true creative entrepreneur who has built innovative, market dominating companies while promoting a positive culture and a great place to work. I aspire to that with Axcient.
What was the best/most useful business book?
JM: Drive by Daniel Pink is a great book about understanding what motivates people. Understanding your employees and what motivates them makes you a better manager and better for your overall business.
What do you do for fun?
JM: I love to fly fish. You can be out for days and not catch anything, but it challenges me to enjoy the journey and learn from it.
Has it impacted how you run your company?
JM: Yes, I think the basic principles impact my approach to running a business. Fly-fishing is a test in patience, determination and focus. But more importantly, it gives me time to reflect. As I mentioned earlier, a committed entrepreneur is often obsessed with their company or project (and I am guilty) but it is just as important to step back once and awhile. We make critical business decisions every day and if you are too deep in the weeds all of the time it is hard to have the clarity and perspective to make the right decisions.
I have found it invaluable to have activities outside of work, where I don’t think about work and that separation gives me perspective.
Justin Moore is CEO and Founder of Axcient. Follow him at @justinrmoore
I wanted to describe our latest investment as an online multi-tenant complex query tool for filtering and analyzing large streams of real time semi structured data. Marketing stopped me. It turns out that DataSift, the investment we just announced today, is all about Big Data for Social.
I like both descriptions. The buzz word bingo of Big Data for Social is light on specifics, but it is accurate. DataSift is broadly in the trend of Big Data, and while Social Data is not the only data the Company analyses, it is by far and away the largest data set. However, it was in the specifics of the technology and the applications it enables, that we saw the compelling investment opportunity.
Big Data is a Big Tent. The phrase has at least three different meanings. It’s most precise meaning is the set of specific technologies around Mapr and Hadoop, publicized notably in the 2004 paper by Google, and brought to market by companies like Cloudera, Mapr and Hortonworks. This technology, which is broadly describable as the Hadoop stack, enables a non-real time (though that is changing) system for storing, counting and analyzing huge data sets. A second, more broad use of the term, has emerged to describe a whole range of newer technologies around NoSQL, HANA, and real time analytics, with the common thread being high volume data management technologies that move beyond the RDBMS paradigm of the last thirty years. These technologies can be either a substitute, or a compliment, to the core Hadoop stack.
Finally, the phrase “Big Data” now describes an entire movement in IT. The technology above made it easier than ever to handle enormous amounts of data, just as a range of industries, from genomics to the social web, started to generate enormous datasets. The combination has set off a mini gold rush as startups and large companies look to use data as a competitive weapon. Search for Big Data on the web and you get 2.3BN hits and the volume of searches is growing exponentially. In the startup world, we are seeing variants of the “Big Data for x industry” every day and this article by Geoffrey Moore gives a pretty good sense of how Big Data is spreading out.
Like any trend it can be overhyped, but the idea that more data and better analysis can lead to smarter predictions, is not a bad one. It received a stunning vindication last week, when Nate Silver predicted the 2012 election, simply by taking existing available information and analyzing it better than anyone else. Check out the hashtag #natesilver. Big Data is now mainstream, with Nate Silver being described as the Chuck Norris of Big Data!
DataSift fits in that second category of Big Data above. It is not building another Hadoop stack or even a Hadoop stack in the cloud. Instead the company has built a powerful platform and query engine that can sift through huge streams of real time data and find specific phrases, measure sentiment or find patterns. What is compelling about the technology is that it manages to be incredibly powerful, while at the same time, simple and accessible to use.
A user can go online, sign up, pay $100 dollars and using a visual interface, construct a sample query and run it against Twitter, blogs and every news source known to man. No complex analysis, no need to install software, and with the new user interface that was deployed last month, no need to learn the underlying language (although a more technical user can easily opt to look at the underlying Curated Stream Definition Language – CSDL – to write more complex queries). Finally, the platform allows users to query unstructured enterprise data as well as third party data.
Fires need fuel and Big Data engines need streams of Big Data. If you build an engine for querying large streams of real-time data, you pretty quickly want to point that engine at the mother lode of data streams, which is in social media and Twitter in particular. The Twitter stream is growing exponentially, and it has become the information pulse of the planet. Companies want to monitor that pulse for reasons that range from customer support to sentiment analysis, and news tracking, but how do you look at 500 MM unfiltered tweets a day?
You don’t. Through a partnership with Twitter, DataSift has full access to the Twitter firehouse. A customer can write a query, run it against the entire Twitter stream and set it up so that, on an ongoing basis, the results stream real time into a business application. The customer can filter by Klout score, geo location, gender, language, subject or any combination thereof. From 500 MM tweets the customer gets only the two, ten or one hundred tweets that matter to them.
Say you want to track every mention on Twitter relating to cars or any related term and you want to limit the search to males, within a certain age, based in or around Texas. The screenshots below showcase how easy it is to build the query.
1. Selecting Tweets by Geo
2. Selecting Tweets by Age
3. Final Query with Geo, Age and Subject Filter
The query can be set to run continuously against multiple feeds with the results pushed directly into an application which can provide user alerts, take action or simply follow what is going on. Maybe the purpose is as simple as just tracking consumer sentiment, or as narrowly commercial as finding auto enthusiasts in Texas that might be willing to test drive an electric car (maybe narrow the search to Austin).
DataSift works really well with software developers and application developers of all sorts. Part of how we discovered Datasift, was by seeing many of our software companies looking to partner with them to get access to the world of unstructured data DataSift handles the backend of managing the platform, integrating the data feeds and running the queries. The application company builds the application through which the results of the query are integrated into the enterprise workflow. Sample use cases include: customer support, lead generation, news tracking and financial trading. The company is also working with ERP vendors and relational BI tool vendors to enable easy integration of structured and unstructured data at the reporting tool level.
Just as Business Objects and Cognos were the query building tools of the relational database world, we believe that DataSift can be the query building tool for real-time streaming data. The way to make that happen will be to empower developers and end users to easily query all the data that is out there, and then let those developers find uses for that data, uses the Company has not even dreamed of.
We are excited to be working with @nik, @rmb and the team @DataSift.