TheFunded is filled with critical commentary by entrepreneurs about venture capitalists and cite real life examples that reinforce this stereotype.

However, now that I have sat on the venture capital side of the table for 4 years, I can also attest to the fact that entrepreneurs can be culpable of equally egregious behavior.

When I accept a meeting with an entrepreneur, I realize this is highly valuable time that he/she could be spending doing something else – meeting with a customer, another vc, employees, etc. Consequently, I try to ensure I am properly prepared to engage by doing some homework on the company, the team, and the market prior to the meeting so I can ask relevant questions. At a minimum, I try to find out about the background of the CEO and if I have any connections to him/her through my network.

On the other side, you would think that an entrepreneur who is looking to me and other members of my firm to invest millions of dollars into his/her company would also invest some time in advance to know who he/she is meeting with and learn about our backgrounds. However, I have discovered this is more the exception than the rule.

To give you a real example, last week one of my business partners and I had a phone conference with the CEO and the management team of a “cloud-computing” company looking for a Series A investment. It didn’t go well.

First, the CEO called in late and his team didn’t know where he was or why he was late – turned out he was talking to a customer (which is great) but he should have at least let his team know that he was tied up and why – we could have started later. No problem.

Second, based upon the content of his presentation it was fairly clear to me he  had not reviewed my nor my partner’s backgrounds prior to the meeting and he certainly didn’t bother to inquire about our backgrounds during the meeting. He proceeded to waste valuable presentation time explaining to us how cloud computing works, how Salesforce had pre-empted Siebel with cloud computing, and then schooled us on IBM’s go to market strategy for cloud computing.

Had he done some minimal investigating prior to our phone call, he would have known my and my partner’s backgrounds (me with Siebel and his with 30 years at IBM) and he could have tailored his presentation — and would have had far more time to dicuss his specfic business.

Yes, I could have cut him off early and explained our backgrounds but I felt it was better to let him just go through his canned pitch and see where it took us. Unfortunately, it only got worse (e.g. the financial slide showed profit would eventually exceed revenues). The CEO was looking for me to invest $5M into his company and he didn’t show up on time, know something about the people he was presenting to, nor check his slides to make sure they were accurate.

At the end of the call, I sent him an email  telling him I was passing but I included a write up on the issues I saw with respect to his business plan and some things he might want to consider to make his presentation better for the next firm he presented to – so far, no reply whatsoever.

If this were just an isolated incident, I would just write it off  and wouldn’t have  bothered blogging about it. However, this type of interaction has unfortunately been more often the rule than not.

I am far from perfect but I try to at least be prepared for my meetings, engaged during them and provide a cogent response afterward – even if I elect not to invest. I have had entrepreneurs disagree with my conclusions and get angry with me when I tell them why I have chosen not to invest, but I feel it is important I continue to provide this feedback out of respect for the time the entrepreneur spends with me – even at the expense of getting skewered on TheFunded.

If you are an entrepreneur and you want a venture firm to consider investing $M’s in to your company, I would propose that you treat your meetings as enterprise sales calls – where you are trying to sell a multi-million $$ deal. You should know in advance who you are meeting with, their backgrounds, and the firm’s background so you can ask questions that will help you determine if there is a fit between your company and the partners/firm (e.g. relevant investing/operating background).

Venture capitalists, too, need to get their act together. We need to pay attention and provide relevant and timely feedback – even if we aren’t going to invest in your deal.

In the end, we are all in this “game” together – venture capitalists and entrepreneurs. In this especially difficult economic climate, both venture capitalists and entrepreneurs need to step up their collective game – be prepared – or there won’t be a game for either of us to play.

I can certainly understand why this might be; most early stage entrepreneurs are subject matter experts in their domain and have a strong point of view with respect to what their application/product should do.  In addition, quantitative analysis can take time and money – something that is in short supply at an early stage startup.

That said, even the best product team can get it wrong — delivering a product that may not be exactly what the market wants, or is priced and/or positioned incorrectly. And, unlike larger software companies, a mistake in an early stage software company can be fatal – or at least cause the company to have to take in more capital and require more time to get into market.

So, I am surprised that more start up software companies (and big software companies, for that matter) don’t incorporate more quantative analysis to help them make critical product, market, features, pricing, and positioning decisions.

I took over the CRMOnDemand division in early 2004 after returning to the company after a 20 month hiatus. The CRMOnDemand division had been created by Tom Siebel to go after Salesforce.com and the SMB market – a market Siebel hadn’t really participated in until that point.

The CRMOnDemand division had two products to offer: UpShot’s “on demand” CRM products as well as our own internally-developed ”on demand” CRM products  (Note: Upshot was a SaaS-based CRM provider that Siebel acquired to gain access to its personnel who had demonstrated they knew how to compete against Salesforce in the “on demand” market).

Unfortunately, the CRMOnDemand division had been struggling since its initial launch 6 months prior to my return and had achieved very little traction with customers and Siebel’s own internal sales organization.

In my first weeks, I sat down with the product, marketing and sales organizations and listened to what the teams thought about UpShot v our internally-developed on demand product, key product features, market positioning, sales strategy, etc. As a result, it didn’t surprise me why we were getting our clock cleaned; we were competing against a strong competitor in its market of strength with a confusing 2-product, ”me, too” message and we were primarily using Siebel’s enterprise sales organization to go after small (SMB) accounts.

I decided to engage a small research firm (Incyte Group) to help us reach out to prospects and customers to better understand how they perceived our “on demand” products, pricing and messages.

From these surveys, we captured a significant amount of data that drove our conjoint analysis. We were able to identify many different issues that were not necessarily obvious going into the study. This data enabled us to quantitatively understand specifically what our engineers should be building, what our marketers should be saying and what our sales organization should be selling.

Consequently, the long and heated debates inside Siebel changed from subjective opinons regarding what should we build, how should we price it, how we should sell it, etc. to instead focusing on solving all the issues surfaced from the surveys. Engineering and Products were now working in alignment. Sales was confident we were building the right product and could sell with confidence. Marketing had a solid messaging platform to work from. And, I personally felt I had the data to show Siebel’s senior executive staff and the Board what we needed to do in order to win in the market.

The result: in 18 months, from relatively little revenues, we were able to grow the organization into an $80M annual bookings business.

While the study certainly wasn’t cheap (it took about 4 months and $100,000+ ), I think about how much it would have cost us had we not done it at all. And, today, with my own early stage start ups, I consider the risk associated with not doing conjoint analysis; how much time/capital will we spend if we get the product, market, pricing, go to market model wrong?

I recently read an interesting article on conjoint analysis by Brett Jarvis at Sawtooth Consulting. I think he makes a powerful case for why each of us involved in developing and/or investing in new product offerings – SaaS or otherwise – would be well served by using conjoint analysis to verify and/or refute our plans.

So, the next time you are faced with a critical product, pricing, messaging, go to market decision, rather than relying solely upon ”gut feel”,  I would suggest you initiate a little conjoint analysis. It doesn’t have to be perfect, take a long time, or a lot of money – and, there are a lot of small consulting firms that can help you do it. I think you will find it illuminating, clarifying, uniting and it might well be one of the single most important decisions you can make as a start up.

• The investing environment / opportunities to sustain the growth and competitive advantage of the American economy
• The exit environment
• The capital raising environment for VCs
• The positive and negative impacts of rules and regulations on the venture community and its portfolio companies

I have my own agenda and it centers around the topic of liquidity. 

In my opinion, the root cause of all issues that are curently having the greatest negative impact on the venture business – and our collective ability to raise funds so we can invest in your companies - is tied to liquidity. Every regulation that gets in the way of supporting liquidity ultimately affects the economy, Limited Partners, portfolio companies,  and the venture community in general.  

In my mind, there are three things the SEC could do to make an immediate impact upon liquidity for small, private companies:

SarBox. According to my own experience and industry experts, companies can expect to pay at least $2M/year just to service SarBox expenses. Meeting SarBox requirements eats up a good portion of earnings and therefore makes it impractical to even consider an IPO unless you are a much bigger company. Proposal: Relax the reporting requirements for companies generating less than $250M annual revenue. The market will build in a discount to the stock price to account for the additional market risk. This risk can be socialized in the Prospectus.  

R&D Tax Credits. Proposal: Enable small companies to carry forward all R&D expenses generated as a private company as a future tax credit thereby enabling small companies that IPO to generate strong earnings as a nascent public company so that their balance sheets can successfully compete against the incumbents for investor support.

Employee Stock Options. In this unstable economy, small companies are finding it more difficult to attract employees from large relatively stable companies. And, with all the stock option scandals that surfaced earlier in the decade, it’s dampened the enthusiasm for companies to broadly disseminate stock options as a mechanism to entice employees to join/stay with a small company. Proposal: Allow all vested stock options to be treated as a capital gain, irrespective of the exercise/holding period.

Those are a few of my ideas. But, I am quite confident you will have even better ones. Why don’t you comment with your ideas and I will see if I can compile them into some sort of categorized/logical order and get them in front of the Commissioner.

Looking forward to hearing your suggestions.

I remember the mid 80’s when Unix entered its hype phase. Traditional proprietary OS companies, seemingly overnight, developed competitive offerings for the Unix market. As a hardware vendor, if you didn’t have a Unix-based solution to offer – even if it was weak – you were toast. Similarly, today, if you’re a high tech vendor it is highly likely you have some sort of Cloud-based offering – even if you’re an incumbent and even if it’s weak.

It hit me last week at the Cloud Connect Conference in San Jose that Cloud Computing may have officially reached its hype phase.  What was my epiphany? When I received an invitation to form a group to discuss “Optical Character Reading In the Cloud”. Seriously? OCR in the Cloud?

I’m sure it was a legitimate invitation to a legitimate discussion but I just had to laugh. It reminded me when my kids were younger and they demanded my wife and me to add the words “in bed” at the end of reading our paper fortune inside our Chinese Fortune cookies. I’m sure it was amusing at first but after repeated readings, it grew a little tiring – at least for the grownups.

With every company adding the words “in the Cloud” to their every marketing pitch and product position it is beginning, for me at least, to feel the same as adding those words “in bed” at the end of those fortunes in the cookies; somewhat wearisome.

Cloud Computing is a great evolutionary business model and technology transformation. It provides an innovative way to deliver new solutions at a much reduced price for consumers/businesses. However, I hope the hype starts to get dialed back soon…just a little…in bed.

It rears its ugly head when a start up CEO comes into our office to take us through their business, introduces the management team and describes one of the executives as the “VP Sales & Marketing”.

At that point, I stop listening and start thinking about how I can end the meeting on a professional note. Like the mythical Unicorn, I don’t believe in the mythical VP Sales & Marketing. Actually, I am more likely to believe in Unicorns than a VP Sales & Marketing.

Why? Simple. Sales and Marketing are vastly different functions that require substantially different personalities, skills, and decades of experience to master. In my 30 years of operating experience, I have found very few people - I mean less than a handful – who are experts at both functions. And, for that rare individual, in my experience I do not believe it is possible to head up both functions simultaneously.

A CEO who doesn’t understand this basic fact, or doesn’t believe it, is not a CEO I want to invest in. Here is why.

Someone who is a head of Sales must have an in depth understanding of current key deals in the sales pipeline,  a deep sense of the probability of whether those deals will close, and what it will take for them to close. This is a 1:1, short-term focus game and success is predicated upon a career of working closely with buyers. In many cases, it also requires someone to travel and meet with prospects to gauge for themselves whether or not a deal is really a deal. It is the realm of oral communicators.

The head of Marketing, on the other hand, must develop and maintain an in depth understanding of the overall market and the company’s brand in that market. To do this, he/she must constantly work with industry analysts, the media, execute tradeshows, keynotes, and the web. Perhaps even more importantly, today’s head of Marketing must be an excellent demand creator (the “owner” of future revenue) through sales-ready leads.

Marketers must know how to generate those sale-ready leads for the lowest acquisition cost and ultimately nurture any sales-ready leads that fall out of the sales pipeline. This is a 1:many game and requires constant refinement through analyzing campaign, market and customer data. It requires continuous meetings with internal staff including the CEO, Product Marketing, Sales, etc. It is the realm of verbal/written communicators.

A CEO who has combined the Sales and Marketing functions, indirectly but undeniably, telegraphs me that he/she does not truly understand the diverse nature of these positions and the fact that it is impossible to execute both functions simultaneously with excellence. In most instances, I have found that the CEO who makes this serious mistake hasn’t worked with someone who is an excellent Marketer and therefore discounts the role it plays.

So, if you ever come and present to me and think you are going to show me a “real” VP Sales & Marketing,  don’t be surprised when I look at you as though you’re trying to convince me there are Unicorns and excuse myself early from the meeting.

At the time, many of the metrics that those who currently run or invest in SaaS businesses now take for granted were then relatively new concepts and not necessarily a part of a traditional software business  - Annual/Total Contract Value, Monthly Recurring Revenue, Cost of Customer Acquistion Ratio, LTV Customer, etc.

A few days into the job, I received my first set of waterfall charts and I remember poring over the numbers trying to cull out the critical information. The first numbers I noticed were “Bookings” and “Monthly/Annual Contract Value”. These were straightforward enough but the second number that popped out at me was “Churn Rate”. It didn’t take a rocket scientist to figure out that a large Churn Rate is an awfully large hole to plug in the bottom of this business model. Our Churn Rate at the time wasn’t outrageous but the trend was concerning.

As a result, I realized there were three critical areas to making this business model work:

1. Number and cost of prospects acquired
2. Velocity rate and conversion costs of turning prospects into customers
3. Churn Rate

I had a function in place responsible for the first (Head of Marketing) and the second (Head of Sales) but no one specific function in charge of number 3. In my experience, if there is a critical business function where there is no single individual/team who wakes up every morning concerned about achieving the objectives of that function, it is unlikely to get done — or at least not as well as it could be done.

As a result, I held a number of discussions with the sales, products, support and services organizations. We elected to create a function called “Customer Success”,  put in place a team and team lead responsible for achieving its objectives and had that lead report directly to me, as the GM of the division. This, I felt, would demonstrate to our employees and customers just how important this role was.

We determined the key metrics of success for this group would include:

• Onboarding rate
• Adoption rates
• Usage rates
• Renewal rates
• Customer satisfaction scores

The result of this decision took our then-current Churn Rate and lowered it by 2/3rds. And, it served as a direct conduit to our Products team in terms of prioritized feature sets for future releases.

Consequently, I have become a firm believer that a SaaS company that does not have a senior executive in charge of Customer Success is one that doesn’t understand its business model and not one I am likely to invest in.

Recently, I’ve had a few conversations with people regarding my version of the Customer Acquisition Cost (CAC) ratio. As a reminder, my version of the CAC ratio is: [($Total Sales + $Total Marketing)/$First Year Contract Value]. The objective is to make the CAC ratio less than 1 which implies a customer acquisition payback of a year or less. This is the ratio I recommend companies use to measure their sales/marketing effectiveness. I discussed this a year or so ago in this blog in a post titled “The Capital Needed to Create a SaaS Company”.

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Will Price when he was with Hummer Winblad and Phillipe Botteri at Bessemer Ventures suggest slightly different approaches and put the Sales and Marketing costs in the denominator with FCV on top of the equation. This makes sense if you’re looking at a company from an investor’s view but I come at things more from an operational perspective and developed my approach in 2004 when I was running Siebel’s CRMOnDemand division. I found that my approach allowed me to easily determine whether or not my Sales and Marketing teams were paying back our customer acquisition costs within 1 year and to track the trend. With the other mathematical approaches, in my opinion, it’s a little harder for the operational executive to determine what’s going on. All approaches are mathematically sound; it’s just a matter of preference.

One of the common issues I’ve been debating is why not use Total Contract Value v only First Year Contract Value so that Sales and Marketing get complete credit for multi-year deals.

Here is how I like to think about the issue.

With early stage companies that use a SaaS business model, companies should be primarily concerned with the preservation of cash not necessarily revenue.  The CAC ratio as I have proposed it focuses on actual Sales and Marketing expenses – which takes real cash – and the First Year Contract Value which represents actual first year cash inflows.

For early stage companies, I feel this is the most appropriate way to look at the CAC ratio because it measures ‘real’ cash inflows v ‘potential’ cash inflows. As the company matures and revenue becomes increasingly more important and cash less so you may want to adjust this ratio to give at least partial credit for multi-year deals.

I want to also comment a little further on the “$Total Marketing” in the CAC ratio. To really maximize effectiveness here, companies must hold the marketing function accountable for accurately creating and predicting future revenue for the company. Rather than just being responsible for managing corporate brand, marketing must be transformed and own the lead generation function and held accountable for accurately predicting out of period, future revenue.

Asking the sales organization to predict future revenue is like asking a sprinter to run a marathon. Sales is incented to predict and close in period revenue. They are terrible at predicting out of period revenue – just take a look at the garbage your CRM system contains in terms of future pipeline coverage. And, many companies make guidance statements based upon this highly subjective data – no wonder so many companies miss their forecasts.

As the former head of marketing for a multi-billion dollar software company, I am all too familiar with the pressure of delivering leads and generating statistically relevant data for Wall Street predictions. Consequently, I firmly believe the marketing function as we have known it must be transformed. Instead of just a brand organization, Marketing must become accountable for accurately predicting  Q+1…Q+N revenue by building a lead generation and lead nurturing function that monitors, tracks and predicts lead conversions and conversion rates.

That’s why I am a big believer and an investor in Marketo. They are building applications for Marketing and Sales that enable those groups to minimize CAC costs and accurately predict and maximize future revenue. And, whether you choose to use Marketo or another similar application, your company must transform its marketing function and hold it accountable for creating and accurately predicting future revenue: only then can you expect to truly minimize your CAC ratio. ]]> http://www.interwest.com/software-as-a-service/brand/minimizing-the-customer-acquistion-cost-cac-ratio/feed/ 3 http://www.interwest.com/software-as-a-service/on-demand/the-case-for-revenue-performance-management-in-the-front-office/ http://www.interwest.com/software-as-a-service/on-demand/the-case-for-revenue-performance-management-in-the-front-office/#comments Sun, 11 Oct 2009 18:49:54 +0000 Bruce Cleveland http://www.interwest.com/software-as-a-service/?p=313 In March of this year, I posted a blog titled “Process Work v. Knowledge Work – The Emergence of Performance Management“.

At the end of that blog post, I committed to commenting in much more detail on the topic of Performance Management and the role of predictive analytics in a future blog.

There are various labels applied to the current Performance Management market such as: Enterprise Performance Management [EPM], Corporate Performance Management [CPM] and Business Performance Management [BPM]. For clarity and simplicity sake, I am going to use the acronym “EPM” to represent the category going forward.

Two of the application leaders in the EPM market are Oracle and SAP and they define EPM accordingly:

Oracle. EPM applications are a “broad range of strategic and financial performance management processes …[sic] that drive profitable growth by delivering predictable results, improving transparency and compliance, and increasing business alignment.”

SAP. “Enterprise performance management starts with aligning operational plans, budgets, and resources to strategic objectives. It involves providing every information worker with contextual access to data they need to make faster, wiser decisions.

While the goal may be for EPM to involve “every information worker”, the reality is that EPM applications are primarily process-oriented and targeted to relatively small operations teams who are tasked with planning, modeling, budgeting and measuring the business. With few exceptions, EPM solutions are not designed for the Front Office LOB.

Directionally, though, applying Back Office-like performance management techniques to the Front Office to enable better business decisions by LOB is a tremendous opportunity. Using advanced mathematical modeling and statistical analysis with historical, current and forecast data rather than relying upon qualitative assessments just intuitively makes sense.

For example, here are some common business decisions that are typically made by individuals in the LOB using ‘best guess’ practices:

• Sales Rep – What is the price I should quote and negotiate that is most likely to be approved by the customer and simultaneously maximize revenue for my company and my commission check?
• Sales Manager – What forecast should I submit for my team based upon the current deals in the pipeline and the historical close rates of my sales reps?
• Marketing Manager – What is the best price I for my product line based upon the overall market forecast?
• Customer Support Representative - How long should I remain on the phone with this customer to address their concern?

To better address these business issues, a new class of realtime, analytical applications that use predictive analytics and statistical modeling techniques are beginning to appear in the Front Office.

These solutions use the data created through business and market transactions (e.g. SAP, Oracle) and enable the LOB organization to make much better business decisions that align with overall corporate objectives. To distinguish these revenue-oriented applications from their Back Office EPM brethren, I apply the label “Revenue Performance Management” or RPM.

Below are six primary areas of difference between EPM and RPM application requirements.

F&A/IT v. Line of Business

In the Back Office, F&A and IT own the resources and make the decisions that affect how the company manages and reports the business. Traditionally, these organizations have the people with the technical skills, domain expertise to use development tools to configure and customize and manage the systems and applications, and the budgets they need to run business systems such as: accounting, order management, payroll, tax, etc.

In the Front Office, Line of Business managers are in charge but in many cases neither they nor their organizations have access to capital budgets nor the technical personnel and/or expertise required to design, deliver and manage the applications they need to run their organizations. For example, Front Office groups such as Marketing, although potentially responsible for millions of $ in demand generation investment, have for years had to rely upon arcane tools such as email/spreadsheets to manage their function.

Cost Centers v. Revenue Centers

In the Back Office, the primary objective is cost containment. Every business process is analyzed to identify and remove overhead. Once an optimal method is determined by F&A/IT for a corporate business process (e.g. Create Purchase Order and Secure Approvals), an “internal policy” is generated and a corporate-wide mandate issued to drive compliance. Few, if any, are allowed to deviate from the policy.

In contrast, the Front Office is primarily focused on revenue generation. Since most companies can’t mandate revenue from their prospects/customers, they must incent the Front Office organization to identify and capture as much revenue as it possibly can. “Incentive Compensation” plans, bonuses, SPIFFs, etc. must be designed with the intent to find, secure, optimize and reward revenue production.

Static v. Dynamic

In the Back Office, every effort is made to stabilize business processes so that they don’t change and generate unnecessary overhead and errors. In the Front Office, change is the operative word. Customers change. Competitors change. Markets change. Territories change. The Front Office of a company must be able to quickly adapt and adjust to change. To address this side of the organization, applications must be easy to implement and manage and be extremely flexible. Relying upon an over tasked or in the case of small companies, a non-existent, IT organization is a non-starter.

As I stated in a previous post, I believe the primary reason Salesforce.com has become so successful is that it was the first company to recognize that with “internet-based computing”, the term used at the time, you could virtually eliminate IT. They pioneered the concept with SMBs and as their products have matured – enduring skeptics – they have gradually worked their way into the LOB organizations of large enterprises.

It is indisputable that Tom Siebel and Pat House, co-founders of Siebel Systems, identified and created what we now all know as the CRM market. However, Marc Benioff was shrewd enough to recognize that his delivery and business model was a better way to deliver CRM solutions to SMBs that have minimal IT support and LOBs inside larger companies who are tired of waiting on IT.

As described in Clayton Christensen’s book “The Innovator’s Dilemma”, Salesforce.com may not have created the CRM market but its disruptive innovation has exploited it.

Realtime v. Batch

The Business Intelligence market emerged out of the requirement for operational teams to be able to use transactional data to generate better business insight. Where online transactional processing (OLTP) was optimized to enable applications to quickly capture and view transactions, for reporting and analysis a different database structure/format was required. This led to the formation of online analytical processing (OLAP) and formed the basis of the Business Intelligence market.

The EPM market emerged in the Back Office out of OLTP/OLAP applications as companies realized they needed new applications that enable them to better plan, model and set budget targets for the business.

In a similar way, the RPM market is emerging in the Front Office. However, there is one very big difference between EPM and RPM.

With EPM, applications are designed more often around batched data.  While response time is important, if a report takes a while to run it may be inconvenient but it isn’t usually catastrophic to the business. Not so, with RPM applications. Here, the interactions can be in realtime and application performance is always critical. For example, if a customer asks a sales rep a question on the phone, the sales rep needs to be able to reply quickly. He can’t wait on the application .

Since the Front Office has few IT resources, RPM applications can’t rely upon IT to configure, manage and maintain them. They must be highly flexible, configurable; they must be SaaS-based. Consequently, the database and analytical architecture for RPM applications must be completely different than their EPM counterparts.

Voluntary v. Involuntary

If you perform a Back Office and/or operations function it is likely you must use an application to accomplish many, if not all, aspects of your job. For example; processing payroll, generating a purchase order, configuring an order, identifying a performance issue on a network, doing an audit, etc. These all require you to engage with an application to accomplish your task.

In the Front Office, other than a few applications (e.g. email), you may only interact occasionally with an application to accomplish your functional objectives. As a result, it is critical that Front Office applications are easy to interact with and generate easy to identify advantages to the individual using them. Otherwise, they won’t be used. RPM solutions, while needing to be quite sophisticated underneath, must have a very simple User Interface and must be able to be administered and managed by the Front Office organization on its own.

Subjective Data v. Objective Data

By far, here is what I believe is the biggest difference between the Back Office and the Front Office.

With relatively few exceptions, the Back Office is driven by objective data. A Purchase Order is either approved and signed or it isn’t. An entry into the General Ledger has either been made or it hasn’t. Revenue is either recognizable or it isn’t. And, these decisions can be made at a relatively slower rate than the Front Office.

In contrast, the Front Office is largely driven by subjective data and the decisions must be made much more rapidly to respond to immediate customer and/or market demands. What should the sales forecast be? How many widgets should I build? Are my sales territories optimized to maximize revenue? Am I spending too much/little money on support? Today, the answers to these questions are determined by largely by human judgment.

The CFO abhors “guesses” and wants to make decisions based purely upon facts. The CSO (Chief Sales Officer) lives in a world of ambiguity and must rely upon a series of educated guesses. If the CFO of a public company certifies the S-1 is correct and it isn’t, she might go to jail. If the head of Sales gets the forecast wrong, she might lose her job but isn’t likely to go to jail.

Therefore, the goal of RPM is to enable the Front Office to convert what has been primarily been subjective data into objective data so that the Back Office and the company overall can make better business decisions.

I have put my money where my mouth is with respect to Revenue Performance Management. I have made several investments to date in companies that have built realtime, analytically-based solutions targeted at the Front Office:

• Marketo (www.marketo.com)
• Cloud9Analytics (www.cloud9analytics.com)
• SignalDemand (www.signaldemand.com).

Each of these companies has designed and is currently delivering SaaS-based Revenue Performance Management solutions. Each is using analytics to help LOB organizations make better business decisions by converting what has been highly subjective data into objective data.

My underlying going-in thesis is that the world doesn’t necessarily need more transactional applications or business intelligence (reports/dashboards) for operational teams. Those markets are defined and owned by well-known incumbent brands.

The big market opportunity is in Revenue Performance Management; using applications that utilize data created by OLTP/OLAP that enable LOB organizations to make better decisions. By definition, these must be SaaS-based. Therefore, for the reasons I’ve discussed in previous blogs, it’s not going to be the incumbent brands that can capitalize upon this opportunity.

Only time will tell if I am right.

The HCIT market is very large and comprised of many large sub-markets. Overall, Piper Jaffray estimates the total HCIT market  to be $15.7B comprised of clinical and non-clinical HCIT systems and they break it into the following submarkets:

• Hospital IT
• Ambulatory IT
• Hospital Revenue Cycle Management
• Physician Revenue Cycle Management
• Connectivity/Interoperability
• EDI
• Payor IT
• Outsourced Services
• Drug Development

Within each one of these markets, there are literally dozens of private and public companies. Many of them have been around a long time.

There are many drivers behind the HCIT market but recently the key ones seem to be: shifting payment for procedure to payment based upon clinical outcome, multi-provider/payor access to patient data, and radical reduction of overall healthcare costs in all areas for all participants – patients, physicians, hospitals, insurance companies and government.

As I took a fresh look at the current major application software providers in each submarket, unsurprisingly I found that virtually all of them use a traditional enterprise software model. However, I can’t think of a industry better suited for the SaaS model than HCIT.

Hospitals – IT staff is under tremendous pressure to reduce costs while simultaneously improving service levels; using SaaS-based solutions the hospitals can substantially reduce their capital  and operational requirements. And, unlike corporate entities where competitive differentiation may lie in unique business processes and therefore require highly customized applications to support those processes, hospitals gain little by differentiating themselves this way. Instead, hospitals and all healthcare constituents benefit from economies of scale if the data and the processes are standardized. What about security? Yes, HIPAA/patient data is critical to secure but no more critical than financial data and SaaS has overcome this issue with flying colors in the traditional corporate world.

Physicians - Physicians don’t typically have IT staff and their concerns are far more about providing great patient care, not maintaining and operating patient management systems, EMRs, HIEs, etc. The SaaS model transfers the burden of managing and operating these systems (e.g. Patient Management, Lab, Prescriptions, Billing) onto the shoulders of the SaaS vendor thereby freeing the physician’s office to focus on patient care and outcomes.

Patients - Patients are becoming more and more interested in managing their own healthcare. High deductible plans, rising costs and looming tax legislation are forcing patients to better understand where and how they are investing their valuable health dollars. Having access to web-based applications that enable patients to consolidate and manage their interaction between insurance companies, physicians, hospitals and other healthcare providers will become increasingly more important. However, forcing a patient to interact with cumbersome master/detail list form-based applications is out of the question. By incorporating familiar UI (e.g. Facebook, Twitter, Blogger, etc.) into healthcare applications, users are far more likely to need little training and willing to use the applications thereby reducing support and operational expense for the providers. SaaS providers can easily provide role-based UI that shields the patient from the complexities of the application while providing other users (e.g. the physician’s office) with much more sophisticated UI for their needs.

Insurance Companies – Insurance companies also benefit from the SaaS model since it facilitates online connectivity and interaction between hospitals, providers and patients. Any time the process has to move from electronic to paper, which it does regularly now, there is operational overhead expense and the potential for error introduced into the process. If all participants are willing and able to participate electronically, costs and errors can be dramatically reduced.

While crowded, the HCIT market feels a lot like when we started Siebel Systems back in 1993. A lot of vendors – there were 300+ SFA vendors at the time. A very fragmented market – different companies solving different problems (e.g. SFA, Service, Support, Service, Marketing, etc.). No industry thought leader. Poorly-written applications without a comprehensive and extensible data model and application vision to address all functional business areas.

The Health 2.0 Conference reminded me of the SFA conferences held back in 1993 — lots of tiny booths staffed with people desperate to engage and sell their products. Keynotes and panels staffed with ‘experts’ who are well meaning and have domain expertise but without the experience and knowledge to create a multi-billion dollar industry, consolidate it and own it.

Based upon my recent observations, I think in spite of the hundreds of current HCIT companies there still exists an opportunity for an applications software company to emerge and own the HCIT market; one with a grand products vision yet with laser focus on solving a few key initial pain points using a SaaS-based model.

Since you need to be a member to read the full post, I have included the article in its entirety at the end of this blog post for your reading enjoyment.

I will wait for you while you read the article.

Welcome back.

Savinay makes several good points in his article. For example, I, too, believe that Cloud Computing will ultimately transform the way IT delivers computational and application services within the enterprise. And, one of the key drivers of this transformation – as with previous IT transformations  – is directly related to cost.

However, to make his point, he uses the analogy that Cloud Computing is similar to buying v. leasing a car and that this is a compelling reason for why IT will incorporate Cloud Computing into its operations. This is where he and I disagree.

Rather than buying/leasing a car, I believe that Cloud Computing is, instead, more analogous to hiring a taxi where the taxi driver/company is responsible for driving the car, managing the car as well as getting you from point A to point B. In exchange, you pay an agreed upon ‘rate’ for that service.

Whether you buy or lease a car, you (the customer) are still responsible for driving the car and managing the car (e.g. insurance, gas, mtce). However, when you hire a taxi you have transferred the burden of service delivery from your shoulders onto the shoulders of the taxi driver/company.

In fact, you will pay more (e.g. $ per mile) for the taxi service than if you drove yourself. However, by outsourcing the driving, you potentially derive multiple benefits: the driver may know a faster way to get to your destination, you don’t need to find parking, you don’t need to navigate traffic, and you are free to focus on getting other more valuable work accomplished during the amount of time you are in the taxi. And, it is a variable cost — you only pay for what you need.

Similarly, with Cloud Computing, you are transferring the burden of IT service delivery onto the shoulders of the Cloud Computing vendor such that the enterprise IT organization can focus on other more value-added issues. The Cloud Computing vendor is compelled to deliver a great product/application under an SLA with 4-5 9’s reliability, disaster recovery, 24/7/365 support. With IT departments shrinking daily, many are incapable of delivering comparable services at comparable (and variable) costs.

The fact that IT must increasingly do more with less resources and provide equal or better service at all layers – platform, infrastructure and application -  will ultimately be the driving force behind the Cloud Computing transformation. Yes, this normalizes out to ‘direct cost’ but the simple fact is that Cloud Computing vendors will live or die by their ability to deliver a compelling service that many enterprises have been simply ill-equipped to provide irrespective of the amount of $$ available in their budget.

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Cloud Computing – Hype or Reality?

Guest Column by Savinay Berry, VP, Granite Ventures – PrivateEquityCentral.net

September 8, 2009

Cloud computing is the new “Web 2.0” of today’s tech world. Any company that remotely provided services associated with enterprise software now has products which have a “cloud” moniker attached to them – a phenomena seen not too long ago with Web 2.0, when a whole generation of companies doing fairly traditional Web-content development started calling themselves Web 2.0 companies. Given that both of these terms represent a set of related concepts spreading across software and hardware, the terminology has helped to guide a conversation in the right direction. Beyond that, many wonder whether the cloud is yet another tech trend caught up in a whirlwind of investment and media hype, or is it a model with real opportunity for market growth and success? What does cloud really mean? What are the components? And finally, where are the opportunities to invest? In this article, I will attempt to address some of these questions from an investor’s viewpoint, rather than from a technologist or management perspective.

To Buy or to Lease Is Really the Question….

One analogy to describe cloud computing is buying versus leasing a car. The first option (buying) is similar to the traditional license-based model of buying software, requiring a large lump-sum payment up front to cover the cost of the purchase and then running it on hardware that you own. The second option (leasing) is similar to running software on-demand on leased hardware. While the end-result of using the car is the same, the means to acquiring it are different. Consequently, the workflow and processes associated with leasing a car are different from that of buying a car (mileage constraints, geo constraints, payments, etc.). This analogy can be extended to cloud computing as well, where the end result of running applications with defined SLAs is the same, but the means to get to the application are different. Hence the workflow needed to access the application in a cloud computing paradigm is different – leading to the potential opportunity for innovation and investment.

To further illustrate this point, consider TurboTax, the tax preparation software from Intuit. Traditionally, over the last few years, if you wanted to use TurboTax, you went to the store, bought the CD, installed it on your desktop or laptop’s hard drive and then prepared your taxes. Cloud computing enabled Intuit to develop TurboTax.com, where users could easily log-in to the site, enter their information and file their taxes – without having to purchase any CD/software. Let’s walk through the costs associated with both of these workflows.

In the first case, the company (Intuit) will incur the cost of making the CDs, packaging them and finally shipping them to retailers. The retailers will markup the costs to make their margins, and finally you – the end user – will buy the software package at the store. In the second case, the company will setup TurboTax.com, and enable enough servers on the back-end (possibly by leasing them) to support peak load given the seasonal demand for filing taxes and establish monitoring software to ensure that the site is up and running all the time. Given the current access costs for leasing servers ($0.08 – $0.15/hour) and the relatively low amount of data that needs to be accessed (there are no video or pictures in a tax filing), the company (Intuit) will incur much less costs-per-user to serve the customer. In turn, Intuit will pass this cost savings to the customer, which clearly shows in the pricing – a CD-boxed version of TurboTax costs anywhere from $49 and up, while the online version costs $35 and up. This savings for the end user creates an opportunity for companies to capitalize on specific aspects of cloud computing.  One caveat to this example is the potential growth in the internal cloud – which is a concentrated collection of servers either managed by a third party or operated as a separate business within a company. An internal cloud does not follow the lease model, since the hardware is owned by the enterprise, but it does follow the re-use tenets defined by the external cloud, which leads to similar or better efficiencies. Investors are paying attention to this sector for both internal and external clouds, as explicit consumer interest has a direct impact on driving new markets.

An Evolution in Computing: Lower Cost and Less Time Leads to Market Change

Before going further, it is helpful to review the evolution of enterprise infrastructure over the last several decades and how that innovation has helped both enterprises and consumers. The earliest implementation of computing was in a mainframe environment, which gave way to client-server. Client-server continues to be dominant today, but several evolutions on top of the client-server architecture created more efficiencies. For example, SOA and virtualization created opportunities to re-use both software and hardware resources more efficiently. Finally, the extension of the data center directly led into the cloud, which provides a way to utilize the best aspects of both virtualization and SOA, as well as take efficiency and reuse to the next level.

Within this entire evolution, two attributes were catalysts of change: cost and time to deployment. It turns out that these are the two most important tenets of IT managers as they grapple with the increasing number of choices for implementing enterprise infrastructure. Given the rise of cloud service providers like Amazon, Google and Rackspace, the IT departments within enterprises will be challenged to stay relevant and will try to turn themselves into service-delivery platforms, rather than pure cost centers purchasing hardware. Thus, from an enterprise’s perspective, the cloud is essentially providing an impetus for IT managers to re-evaluate their infrastructure and invest in proactive changes, which forms a credible opportunity for innovative startups in this space. To provide a perspective on the size of the market, in 2008, $870 million were spent on server management software alone, with the spend on this market expected to increase to $2.3 billion by 2013, according to the 2009 IDC report on cloud computing.

The Architecture and Opportunity behind the Cloud

Now that we have established the cloud computing impact from both a consumer and an enterprise standpoint, let’s go into more detail on the architecture of cloud computing and where some interesting opportunities for investing may lie. At the core, cloud computing can be divided into three layers: infrastructure-as-a-service, platform-as-a-service and software-as-a -service.

Infrastructure-as-a-service (e.g., hardware services like the ones from Amazon, Rackspace, GoGrid) will eventually get commoditized and platform-as-a-service is an area that will need the most work from established companies like Google, Microsoft and Amazon. However, the area of software-as-a-service will be ripe for innovation.

Specifically, as applications like Google documents, mobile apps, Salesforce.com, and others shift into the cloud, services driving these applications will be essential. Some examples of these services are databases, billing, analytics and security. Broader adoption of cloud computing within the production environments of companies like Pfizer and ING – where data security is critical – will not happen unless a robust end-to-end security solution exists in the market. Such opportunities will help to create a large and growing market for potential investments in the cloud computing sector.

Since I expect that the future IT environments will be a hybrid implementation of both internal data centers/cloud and external cloud, various tools will be required to ensure that applications, images and databases can be transferred from one resource to another without losing context, policies and security. The need for this “cloud brokerage” will create a category of companies for these management tools. Fundamentally, these tools will adapt existing functions in data centers, like resource planning, provisioning, applications management and transaction profiling, into services catering to the distributed and flexible nature of the cloud.

Finally, due to the potential commoditization of cloud infrastructure (e.g., Amazon Web Services, Google, Rackspace), companies may want to get the best pricing structure depending on time-of-day use, similar to the concept of energy usage on a time-of-day use in states like California. A third-party marketplace providing an arbitrage opportunity for enterprises to shift images from one cloud to another could be an interesting opportunity; however, this vision will not materialize until enterprise adoption of the cloud architecture reaches a critical mass.

By now you can probably establish that while the term “cloud” has a certain amount of hype associated with it, once you peel away the layers and dive in, opportunity is waiting.  The cloud represents investment opportunities and a potentially robust market positioned to change the way enterprises conduct business. The only question remaining is when this market will ripen, rather than if it will ever come to be.

Savinay Berry is a vice president at Granite Ventures (www.granitevc.com), an early-stage venture-capital firm that invests in innovative software, services and communications companies. He received his M.B.A. from the Kellogg School of Management and a Master’s in Engineering Management degree from the McCormick School of Engineering & Applied Sciences, Northwestern University. He holds a Master’s of Science degree in Electrical Engineering from Michigan State University and a B.S. degree from the University of Pune, India.