That said, terms do go out of use, sometimes even when they still accurately describe an existing technology. For instance, every person I work with has a “personal digital assistant” – but no one uses that term.

Is it ‘Software as a Service’, ‘SaaS’, or ‘Cloud Computing’?

Recently, I’ve seen some a few posts declaring Software-as-a-Service and SaaS to be outdated terms. At the same time, the replacement and all encompassing term that seems to be the trend — Cloud Computing– is being contested. Is it a superset of SaaS (or DaaS, IaaS and PaaS for that matter)? Is it something different altogether as Joel York discusses in a recent blog titled “Hey SaaS Experts — What’s Your Cloud Computing IQ?” or Ray Wang in his post titled “Understanding The Many Flavors of Cloud Computing and SaaS“.

So I decided to look for some data to see what popular terms people are using to gain a sense of the trends. In an era when selecting the right SEO keywords can be critical to getting visibility, this isn’t just an exercise it is being au courant.

What the Numbers Say — ‘Cloud Computing’ in the Lead

Here are a few statistics, based on frequency of use over the last month:

Media (Google News)

• 2,164 – SaaS*
• 2,163 – “Software as a Service”
• 4,974 – “Cloud Computing”

Blogs (Google Blog Search)

• 18,752 – SaaS*
• 7,617 – “Software as a Service”
• 70,000 – “Cloud Computing”

Twitter (Topsy)

• 12,531 – SaaS**
• 2,632 – “Software as a Service”
• 23,612 – “Cloud Computing”

Searches (Google – monthly searches based on average of past 12 months)

• 550,000 – SaaS
• 246,000 – Software as a Service
• 550,000 – Cloud Computing

Keyword Cost Per Click (Google Adwords estimate)

• $2.36 – SaaS
• $7.26 – Software as a Service
• $0.05 – Cloud Computing

(That last CPC figure for Cloud Computing looks suspiciously low to me.)

Conclusion

While it looks like the industry is coalescing around Cloud Computing as an umbrella term – even though there is ambiguity about its specific meaning -  other terms are still in regular use, especially SaaS, which leaves people 136 characters for tweeting!

For now, I plan to use Cloud Computing as the umbrella term to include all of the following: SaaS, DaaS, IaaS and PaaS. As the industry settles on specific nomenclature, I’ll adapt. That said, whether you call it “Cloud Computing” or I call it SaaS, it all represents disruptive innovation.

Which terms are you using?

*Since this term has alternate uses, I excluded articles that didn’t also include “software” somewhere in the copy.

**See note above. There may be some “noise” in this number, since I couldn’t sensibly exclude “software” in a 140 character tweet.

I believe there is tremendous opportunity in delivering Back Office-like performance management techniques to the Front office to enable better business decisions by the lines of business, so I reached out to SignalDemand, one of the companies I mentioned in my last post, to test whether the framework I had developed has mapped to their experience on the ground.  I also wanted to verify what type of business results companies were seeing when they deployed advanced mathematical modeling and statistical analysis to predict the future, and make rigorous decisions based on those predictions…versus the traditional approaches of analyzing history, or worse, relying only on qualitative assessments.

SignalDemand in turn shared one of their case studies from Cargill Meat Solutions, a leading processor and distributor or fresh and prepared beef, pork and turkey with more than $15B in revenue and over 35,000 employees.

In my previous post, I noted six primary areas of difference between Enterprise Performance Management and Revenue Performance Management.  These differences both define the significance of the opportunity in the Front Office as well as why this large market opportunity is going to be driven by SaaS-based solutions that provide real-time answers, targeted to the needs of the line of business.

Why SaaS?  It’s Not Just a Deployment Approach

In the Front Office, Line of Business managers are in charge but in many cases they lack access to the technical personnel and expertise required to design, deliver and manage the applications they need to run their organizations.  Instead, you have the teams that control the top-line of the business using arcane tools such as spreadsheets and email to manage complex processes that lead to critical business decisions required to run their organizations.

Nowhere is this pain felt more acutely then around the problem of ‘price’.  According to SignalDemand, this was the situation Cargill Meat Solutions (CMS) found themselves in, recognizing that their traditional means of pricing – a complex process that involves pricing experts working with internally developed tools – while serving them well in past, would not keep them competitive in the future.  CMS recognized the value that could be achieved by applying predictive analytics and optimization to price back in 1999, but quickly realized that without the capability to translate price changes into their resulting revenue and supply implications, the usefulness of the technology was limited.

It wasn’t until SignalDemand brought the right mathematical modeling expertise, along with a SaaS based solution that CMS was able to get the business answers they needed.  In addition to requiring targeted answers to business problems, CMS needed them to be delivered without a protracted IT project, the kind of solution that only SaaS based applications can provide.

The Dynamic Nature of the Front Office

In the Back Office, every effort is made to stabilize business processes, but in the Front Office, change is the norm.  The Front Office of a company must be able to quickly adapt and adjust to change.  CMS faced a situation where more than 150,000 pricing decisions were being made each week – this in an environment where they were surrounded on both the buy- and sell-side with changing market conditions.  And the impact of price in this environment wasn’t isolated to sales.

There was the reality that a single production input (an animal carcass) can yield thousands different products (cuts of beef), and every carcass harvested has the same parts…so you had better use price to make sure you’re selling the various parts at the same rate, or you could end up with a lot of inventory sitting around for one part of the animal while you’re going gangbusters in another (the adage in the industry is “sell it or smell it”). In this type of environment – with significant volatility and complexity – an environment extremely common in commodity based value chains, it is nearly impossible for human intuition and spreadsheets to truly optimize an organization’s business results.

Real-Time Answers Critical to Front-Office Success

The Enterprise Performance Management tools provided by application leaders are often designed around the batch processing of data, where response time is important, but if a report takes a while to run the impact is an inconvenience rather than catastrophic to the business.  Not so with Revenue Performance Management and the needs of the Front-Office.

CMS needs to be able to price-product in real-time as highlighted by Mark Hoekstra, Pricing Manager, Cargill Pork Retail, “SignalDemand has helped us to speed up our pricing process, allowing us to respond to our customers’ requests more quickly and ultimately to win more business.”  The Front Office needs solutions like those delivered to Cargill which support decisions at the speed of business, with capabilities such as rapid scenario analysis, enabling a sales rep to understand the immediate price and margin impact of changes in input costs or sold position.

Revenue Centers – More Difficult, BUT More Opportunity

The reality is that it is far easier to analyze back office processes and to ensure that all costs are contained.  The Front Office is more difficult because of the dynamic nature of their decisions and processes, which calls for real-time information – I’ll discuss this in more detail later.  Better support for the Front Office however can have a much larger impact on a company’s bottom line as evidenced by the often quoted McKinsey study which showed that a one percent improvement in price increases operating profit by eleven percent, whereas decreasing COGS by the same one percent results in only a seven percent impact on operating profit.  While the privately held company would not share financial results, they “clearly were substantial” as quoted from an AMR case study prepared on the SignalDemand deployment at Cargill. Below is a graph of information they did share with AMR, showing two measures of CMS price volatility, both before and after implementing SignalDemand.

The Executive Champion: A Critical Role in Front Office Success

In the Back Office, it is likely you must use an application to accomplish many, if not all, aspects of your job while in the Front Office; just the opposite is true – other than a few applications (e.g. email), you may only interact occasionally with an application to accomplish your objectives.   When asked how they managed the “change management” elements of the project, project sponsor, Herb Meischen, noted that it was the president of Cargill Meat Solutions who sponsored the project and that this senior sponsorship helped facilitate the product’s rapid adoption.  User adoption can be a challenge when organizations are accustomed to using “gut feel” and intuition rather than mathematical models.  Meishen points to the fact that Cargill initially ran the technology in parallel with what was then a spreadsheet-based method to determine price.  From AMR’s case study on Cargill, “Each day, the SignalDemand technology calculated pricing options and the best mix, while the team used existing processes to calculate pricing options manually. When team members found out the technology could more accurately price a complex scenario in minutes versus the manual process of hours or days, they quickly adopted the tool.”

Applying Predictive Analytics to the Front Office: Turning Subjective Data into Objective Data

By far the largest difference between the Back Office and Front Office is that with relatively few exceptions, the Back Office is driven by objective data and decisions can be made at a relatively slower rate.  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.  So what if there were technologies available that enabled the Front Office to convert what has been primarily subjective data into objective data?  What if the Front Office was able to apply the same rigor to its available data, but in real-time so they could make business decisions?

Cargill Meat Solutions implemented SignalDemand’s solutions (which use historical pricing, USDA market activity, sold positions, inventory and supply constraints) and developed detailed pricing and demand elasticity models for each of the time-horizons in which Cargill Meat Solutions sells its products: spot, mid-, and long-term.  Whereas historically this information was scattered through a series of applications and spreadsheets which would need to be manually reviewed, SignalDemand pulls this complex data set together, running it through their models, translating complexity into simple answers – what is the right price, for this product, in this time frame, for this customer? As stated by Bill Chandler, Beef Pricing Manager, Cargill Beef, “It’s given us an unbiased tool as we operate in a very emotional environment to be able to make a good decision.”

The Inexorable Transformation of the Front Offce

With SignalDemand and Cargill Meat Solutions as a prima facie example we now have empirical evidence that demonstrates Revenue Performance Management solutions are beginning to enter the Front Office and make a significant positive financial impact.

While still early, I believe that the compelling economics of  RPM solutions such as SignalDemand, Marketo, Cloud9 Analytics, and others will dramatically change the way in which companies manage their Front Office.

Not surprisingly, he said SaaS and cloud-based companies are struggling with the liability issues associated with customers’ number one concern – security.  Customers want vendors to assume unlimited liability for security breaches; vendors want to restrict and cap their liability. Negotiated subscription agreements often end up somewhere in the middle.  So, how can a vendor give its customers a high level of liability protection and still sleep at night?

Based upon my conversation with Cary, the answer may lie in a good cyber liability insurance policy.

Q. So, Cary, what exactly is “cyber liability insurance”?

A. Cyber liability insurance is insurance that allows a vendor to outsource the risks that remain after it has implemented direct, technical computer security measures and attempted to limit its contractual liability to customers.  Since typical commercial general liability (CGL) and errors and omissions (E&O) policies rarely cover “intangible” losses related to loss of data, privacy breaches, and the like, cyber liability insurance policies are intended to fill that hole to address the particular needs of a company doing business in the cloud.

Q. Why should SaaS/cloud providers strongly consider cyber liability insurance?

A. Unlike traditional enterprise software vendors who ship software to their customers to run locally, SaaS and cloud-based service providers receive and maintain business and personal data on behalf of their customers.  The value of this data to the customer often exceeds the cost of the service.  So, customers are not shy in asking for security and confidentiality liability that far exceeds the profit the provider can expect.

Providers rely on a myriad of employees and third party vendors (cloud platform providers, collocation facilities, system integrators, solutions providers, etc.).  However, these folks cannot or will not provide adequate liability coverage for the security breaches they may allow.  After security policies and procedures have been put in place and agreed to, cyber liability insurance increases the providers’ ability to offer liability levels that go beyond the value of the contract.

Q. There is a lot of media hype around security issues but just how big is the risk of a real data breach?

A. Data breaches can come from any number of causes: unauthorized access to online systems, denial-of-service attacks, and introduction of viruses and malicious code, any of which may result in loss, dissemination or destruction of electronic data, business interruptions, privacy law violations, disclosure of non-public personal and or confidential information, and, potentially cause financial harm to the persons whose data is released, as well as the provider.

Fixes can be expensive: detection, escalation, notification and response along with legal, investigative and administrative expenses, customer defections, opportunity loss, reputation management, and costs associated with customer support such as information hotlines and credit monitoring subscriptions.

Recent studies provide varying results regarding the cost of data breaches, but they are always expensive:

• A recent survey by the Computer Security Institute found that the average company financial losses due to security incidents exceed $230,000.  The Ponemon Institute puts the average total per-incident cost even higher at $6.75 million, with an average cost per compromised record of over $200.
• In the CSI survey, wireless related exploits were the most expensive, averaging $770,000 in losses per incident, followed by theft of personally identifiable information or personal health information through all causes other than mobile device theft ($710,000), and financial fraud ($450,000).

Rogue employees are part of the problem, resulting in data security issues 43% of the time.  But accidents can happen too:  25% percent of survey respondents felt that over 60% of their financial losses were due to non-malicious accidents by insiders.

Q. If I’m a cloud provider, can’t I just pass some of the liability on to my vendors?

A. You could pass some of the liability for your vendors back to them, if they were willing to accept it.  Problem is, they are not.  I have negotiated enough contracts with cloud platform providers, collocation facilities, telecommunication providers, solution providers and others to know that they will simply not take on the liability for damage to your business or your customers’ businesses resulting from their data security breaches.  (I’ve actually heard counsel for a colo extol the virtues of its security procedures, only to assert that it should have zero liability for data breaches because placing a box in the facility does not constitute disclosure of the data. At least they offered to cover the cost of the lost hardware if one of their employees walked off with it.)

Inevitably, you will be stuck in the middle between your customers and the third party vendors you use to provision your service at a reasonable cost.  Remember that agreements with vendors should require that they carry a cyber/privacy liability policy that names you as a third party beneficiary.

Q. How do I decide what cyber liability insurance I need?

A. To decide what kind of cyber liability insurance you need, first evaluate your existing policies, and ask yourself the following questions:  Am I covered for loss of electronic data?  Is electronic data stored on media covered?  Are first party claims covered (damage to your company’s electronic data or equipment)?  Are third party claims related to electronic data loss covered (in other words, customers who claim you damaged or lost their electronic data, or personal information)?  Newer commercial general liability (“CGL”) policies typically exclude electronic data loss from coverage as electronic data is excluded from the definition of covered tangible personal property.

You should also consider whether any of the following types of damages and claims are covered or expressly excluded from your policies: DNS and other types of hacker attacks (causing downtime, and potential exposure to your customers); transmission of malicious code; data released by rogue employees or by employees making innocent mistakes; security breaches; business interruptions; privacy violations, including disclosure of personal information or customer personal information, and incidents related to unauthorized access to company online systems; unauthorized access to credit card information; notification and other expenses incurred in remedying a privacy breach; expenses related to customers’ claims; costs to investigate and restore data.  In reviewing these scenarios in your existing policies, examine how and whether intentional acts are excluded from coverage; and whether fines, penalties and related settlement costs are covered in any policy.

Also consider whether your current policies cover liability assumed under contract.  A CGL policy may not cover liability assumed under contract; they primarily cover tort liability.  It is good practice to consider obtaining coverage that expressly covers contractual undertakings, for example, indemnity for privacy breach, as this will give you some flexibility in the types of promises you can safely make to customers.  In addition, look at whether your policies cover acts of subcontractors (such as data that is lost/damaged by your collocation provider facility or by your consultants).

Finally, think about the kind of data you are storing online and where is it being stored.  Does it contain any personally identifiable information (“PII”)?  If yes, then at minimum, you’ll need privacy liability coverage.  Is the data encrypted?  What techniques are you using to protect unencrypted data?   This is quite important since some insurers may include policy exclusions for unencrypted data.  Are you transmitting, or do you plan to transmit any PII from Europe to the US?  If so, are you US–EU Safe Harbor certified?  Do you have good procedures in place for a data breach event? Do you have a disaster recovery and business continuity plan in place?  These things matter in terms of whether you can get a policy, and how much it will cost.

You might consider “cyber extortion” coverage if you are concerned about the risk of having to pay a ransom amount demanded by a hacker threatening to shut down your company’s network/services or steal private information.  These policies often include forensic or investigative costs to help determine the validity of the hacker threat, and there is usually no deductible because the carrier views this as a proactive measure that could prevent larger damage and loss.

This isn’t an exhaustive list – consider other loss scenarios not mentioned here to determine with your broker what other risks should be covered.  For instance, Mike Gilmore of Crump Insurance Services, Inc. in San Francisco highlights that intellectual property infringement and personal injury claims arising our of technology products, services and website activity are often covered with a cyber liability policy.  Software copyright infringement claims are fairly common for software code.  And he’s seeing more and more personal injury claims arising from company websites that contain blogs where individuals can post comments, pictures, and otherwise, that can be defamatory, slanderous, and damaging to reputation.

Another good source of information is the IRMI.com website which includes some ideas to consider in evaluating various loss scenarios.

Q. What other steps can I take to limit my liability with cyber liability insurance?

A. Many carriers are offering proactive services in addition to the risk transfer in the cyber liability policy, including forensic experts and consultants who can help mitigate a security/privacy breach, legal experts to advise on requirements per state, public relations support, and even 24-hour IT support for guidance if a company thinks it may have a privacy breach situation or hacker threat.

One interesting area of coverage to discuss with your broker is regulatory defense and indemnity coverage to cover fines and penalties where insurable by law, for example the costs associated with a settlement with the FTC in the event you violate your own privacy policy.  Think about your posted Privacy Policy, and whether your internal procedures comply with your public promises.  If not, and your system is hacked, you may have exposure to FTC action, potentially leading to costly fines, penalties, and remedial actions.

Using its authority under Section 5 of the FTC Act, which prohibits unfair and deceptive practices, the FTC has brought a number of cases to enforce privacy policies, including promises about the security of consumers’ personal information.

A good recent example of this was the settlement by Twitter with the FTC for Twitter’s lax security practices. The case involve two hacking incidents in 2009, one in which a number of high profile accounts were compromised, and another in which a hacker gained access to a Twitter employee email account containing the employee’s administrative password.  Under the terms of the settlement, Twitter was barred for 20 years from misleading consumers about the extent to which it maintains and protects the security, privacy, and confidentiality of nonpublic consumer information. The settlement also required Twitter to establish and maintain a comprehensive information security program, which will be assessed by a third party every other year for 10 years.  Similar settlements between the FTC and various technology companies over security breaches can be found on the FTC website.

First be sure there is a broad definition of “Claim” so coverage applies to demands, investigations, requests, complaints, and civil, criminal, and administrative and regulatory proceedings.   In terms of FTC and other government agency activity in the privacy arena, this is becoming increasingly important.

Evaluate the definition of “Loss” to ensure coverage encompasses a wide scope of relief, including statutory, and regulatory fines and penalties, defense, investigative and settlement costs.  Clarify that disruption, corruption, deletion, theft, or copying of data, software, or programs whether stored electronically or on good old fashioned paper is deemed to be “physical loss or damage” to potentially avoid coverage issues for loss or damage of electronic data.  Seek to add a provision covering the cost of making a determination that reconstruction of data is impossible.  Look for coverage for unauthorized use by authorized users.  Check for coverage for loss of use by a third party.

Examine the “Exclusions” to coverage to ensure they are narrow and contain “exceptions” where coverage will be provided.  If possible determine if exclusions for bad conduct by officers, directors or company employees will be triggered only by a final adjudication of the excluded conduct.  Defense costs should be covered, and the exclusions should be severable, so that one rogue employee does not disrupt coverage for all.  Make sure the cost to replace or restore electronic data is not excluded.  And review the “insured versus insured” exclusion to ensure you have coverage for your own employees as long as you are buying the coverage.

Finally examine the duty to mitigate damages carefully.  “Covered damages” definitions often exclude the cost of repair if you did not take prompt, reasonable measures to address a security breach.   In part this why you should take a pre-coverage security assessment, continually improve security procedures, and conduct internal training on them.

Q. OK, I’m convinced!  But how do I sell this internally?

A. Ted Doolittle of Risk Placement Services tells me tech providers often think they are immune to the risks identified here.  From a tech perspective, they’ll say they don’t have exposure because their systems are airtight, or that they don’t have time for the steps involved in obtaining insurance, such as third party security audits, lengthy applications, etc.  From a finance perspective, they’ll simply say that cyber liability insurance is not in the budget.  Hopefully, the information in this article will give you some ideas about how to discuss the issues and justify the purchase.  Given the risk of litigation associated with dealing with personally identifiable information (PII), he recommends that tech providers get at least a policy to cover the defense costs associated with a claim.  The process for obtaining coverage, he says, is much more streamlined that it was even 1 or 2 years ago.

Q. If people want to contact you directly to discuss this issue in more detail, what’s the best way?

A. Just have them email me directly at cary@platkinlaw.com

The general premise of the article is that SaaS point solutions or “best of breed” are going to eventually be replaced by suites – just as what happened with traditional enterprise software applications.

In the interview, Sino makes 5 significant points as they considered SaaS-based ERP solutions:

1. “The major problem with a best-of-breed ERP solution is integration.”
2. “If I’ve got three different best-of-breed applications supporting the process, how can I be sure the integrity of the data remains intact across all of them?”
3. “In essence, best-of-breed products would create a new set of integration challenges…”
4. “Support was another key consideration.. “
5. “Throughout the purchase process, cost was an overriding concern.”

Sounds pretty familiar doesn’t it? The issues that Sina outlines are identical to the issues that drove consolidation of traditional enterprise application point solutions.

His conclusion: “The overarching need for a business “truth” pushed us to a single suite solution that was capable of tying all master business data and processes together.”

Saugatuck Technology, a research firm, has also been predicting the arrival of SaaS suites sooner v later for some time. They predict that full SaaS suites become widespread toward the end of “SaaS Wave III” (2012-2013) and the beginning SaaS Wave IV (2013- ).

We’ve seen how this play turns out in the traditional software sector which is why it is fairly obvious why the market values SaaS companies CRM and SFSF at an 8X EV/Rev multiple.

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.