Trident Capital Blog

Panel Discussion at the AlwaysOn OnDemand Conference

Yesterday I participated in a panel discussion on how the startup model has changed in the era of open source, Amazon’s cloud infrastructure and SaaS.  The panel was part of the AlwaysOn OnDemand conference.  Three of Trident's SaaS portfolio companies made it to the AlwaysOn OnDemand 100, the list of the top 100 SaaS companies: Host Analytics, Pivotlink, and Tricipher.  Other panelists included Gordon Ritter of Emergence Capital, Ravi Mohan of Shasta Ventures, Mark Gorenberg of Hummer Winblad and Sanjiv Parikh a venture advisor.  Because of the participants the discussion delved primarily on the strengths and staying power of the SaaS model, the characteristics investors are looking for in SaaS companies, and areas of new investment opportunity.  Below are some of the discussion’s highlights:

• In its purest form, cloud computing represents a fundamental platform shift in that allows everything to be offered over the internet as a service, elastically/dynamically, and paid ratably.  Many companies (mostly large vendors of on-premise software solutions), are either trying to marginalize this shift by calling it a fad, e.g., Oracle, or are trying to leverage the recent hype around cloud computing to position their products as cloud-based because they feel that in this way they will remain relevant.  At Trident we have a well-defined set of criteria that allow us to determine whether a company has a true SaaS product and the associated business model and practices.  The other investors participating in the discussion have similar criteria

• The panelists agreed that corporations are adopting SaaS applications because they provide a) their employees with universal access to the solution (anytime, anywhere), b) quicker time to value, c) reduced Total Cost of Ownership (TCO), compared to equivalent on-premise applications, and d) unique and needed functionality that is enabled only by the cloud, most importantly collaboration.  These adoption factors were most recently also validated through a survey conducted by InformationWeek.  To continue providing superior TCO, SaaS companies must continue to rapidly evolve their products, business models and distribution models.  Customers must feel that they are getting something of value immediately (even if they are just testing the free version of a SaaS product) thus creating the right conditions for future upselling opportunities.  Cloud-based infrastructures enable the rapid iteration through product offerings and models.

• Strong teams with knowledge of the SaaS the model is a top characteristic of the SaaS companies seeking investment.  Technological and business model innovation is another top characteristic.  What type of technological and business model innovation does the cloud enable, other than a delivery mechanism, that will cause a customer or a partner adopt a SaaS solution? By understanding the target customer’s pain-points investors are also trying to determine whether a SaaS company is trying to automate an important business process that can be uniquely automated through a cloud-based solution or whether the SaaS solution will just replace an existing on-premise solution by introducing additional efficiency.  Understanding of the target market (as investors we don’t want to hear that a SaaS company is targeting the generic SMB market; instead we expect a more sophisticated segmentation of a company’s target market since the purchasing and adoption criteria of a mid-size enterprise are completely different than those of a small company).  Finally, there was a brief discussion regarding the metrics a company must have achieved to be considered an ideal candidate investment, such as MRR, LTV, and CAC.

• Regarding new areas of investment interest we mentioned vertical SaaS applications particularly in industries such as health care and pharma even though security and compliance of data were identified as potential impediments to broad and quick adoption of such solutions.  I mentioned that my personal investment interests are around SaaS applications that automate Internet process in the areas of online advertising and e-commerce as well as in analytic applications and cloud-based infrastructure that address big data problems.  Identifying applications that utilize the data captured by SaaS applications was mentioned as another promising investment opportunity.  The panel touched upon the investment opportunity for a new generation of SaaS applications and cloud-based infrastructure created by smart phones and the new generation of tablets.

Real-Time Analytics

Last Friday I attended SDForum’s The Analytics Revolution Conference.  The presenters were startup public and private company executives and investors.  The presentations were mostly around real-time analytics.  For the past few years Gartner analysts have been writing and talking about the Real Time Enterprise.  Gartner sees the analysis of the data that is generated by various enterprise applications such as an ERP and residing behind the corporate firewall and an important ingredient to achieving the Real Time Enterprise.  However, Friday’s presentations brought to focus that the impetus for real-time analytics is not the faster analysis of enterprise data, but of the Big Data captured on the Web (structured and unstructured social data, activity logs, data coming from mobile applications, geolocation data, data mashups, the interactions during the lifecycle of the captured data, etc).  This data is orders of magnitude larger and more complex than the data currently stored in the enterprise data warehouses.  I had written that Internet SaaS applications will drive the SaaS innovation agenda.  Friday’s presentations provided more examples and additional justification for this conviction.

Companies like Facebook, eBay, LinkedIn and Zynga that presented at the conference are interested in making analytics-driven decisions in Internet speed and cheaper than it is currently possible with the existing data warehousing and analytics technologies. They want to use their data to continuously optimize their businesses, simulate the effect of decisions on business processes, and forecast the impact of actions.  Making decisions based on reports that summarize and find trends in data that is a week or a month old simply won’t do.

To take advantage of emerging opportunity of real-time analytics of big data, we are considering investments in the following three areas:

1. Infrastructures of next-generation data management systems, including open source systems like Hadoop and derivatives, and systems for creating OLAP cubes in real time.
2. Horizontal and vertical analytic applications, examples of which are listed here.  Additionally, these applications will need to find a way to monetize on the data they capture, not only on the data they process.  See, for example, how internet data exchanges like BlueKai are able to monetize the cookie data they capture.
3. Analytic services offered around the captured big data, e.g., the services offered around big mobile data by companies like Ground Truth, and Flurry.

My underlying hypothesis (driving one of my investment theses, and shared by several of the investors present at the conference) is that cloud computing will make big data analysis faster and cheaper.

I am convinced that over the next few years, investments in each of these three areas will result in several strong exits.  I don’t believe that the established on-premise data warehousing, BI and analytics vendors will be able to create adequate technological and business model innovations around real-time analytics.  The results of a survey conducted by InformationWeek and published on March 27, 2010 make it clear that more enterprises are looking to cloud computing to address the perceived shortcomings of on-premise applications, with SaaS BI being one of the top areas of interest.  Finally, as stated here, incumbent on-premise software vendors will continue to face the innovator’s dilemma that won’t allow them to move fast to offer the novel solutions for real-time analytics that the market needs and is starting to demand. 

SaaS Multi-tenancy Economics

In response to my post on the criteria of determining a company’s SaaSyness I received several messages asking for further elaboration on why I consider multi-tenancy to be such an important criterion.  I want to provide an investor’s view on the importance of multi-tenancy.

First a little background so that we can all be on the same page.  After a spirited discussion in the LinkedIn SaaS group Alok Misra wrote an article on multi-tenancy explaining why it matters to SaaS applications, and Nati Shalom followed with a great post explaining the technical aspects and challenges of multi-tenant architectures.  In an earlier post Mike Krigsman touched upon how multi-tenancy impacts the business model of a SaaS vendor.

There are two ways to achieve multi-tenancy: 1) build on top of a PaaS that offers it, e.g., Force.com, or 2) implement it yourself (as most SaaS vendors).  As Nati states, broadly there are two approaches to multi-tenancy: 1) the fine-grained approach exemplified by Salesforce.com, and 2) the coarse-grained approach exemplified by vendors offering a hosted application service.

From a user’s perspective multi-tenancy doesn’t mean much as an architectural construct unless it impacts:

1. The SaaS application’s total cost of ownership (TCO),
2. Data security, and
3. The ability to customize the application.

By far the biggest impact of multi-tenant architectures, and the reason I use multi-tenancy as one of the decision criteria prior to investing in SaaS companies, is on the vendor’s business model.  Before embarking on the implementation of a SaaS application under a particular multi-tenant architecture, the vendor must understand the impact of the architectural choice on product development, product maintenance, customer onboarding, and customer lifecycle management.  Understanding the architecture’s impact along these dimensions will also help the vendor understand the application’s TCO and whether the company’s business model will be winning scalable or whether it will need to be revised.  For this reason during the due diligence process I try to answer the following questions along each of these dimensions:

• Product development.  Are there any regulatory or legal reasons that will inhibit the adoption of a particular type of multi-tenant architecture?  For vendors converting an existing on-premise application to its on-demand equivalent I want to find out whether the original application imposes restrictions to the type of multi-tenant architecture that can be used.  How much will it cost and how long will it take to implement the selected architecture?  For example, the economic benefits to the vendor resulting from the use of a fine-grained multi-tenant architecture may be negligible compared to the cost of implementing such architecture.
• Product maintenance.  What does it cost to maintain a product implemented under a particular multi-tenant architecture?  Does the product’s maintenance require senior (and thus more expensive) engineers and database administrators? How long does it take and what is involved to apply software patches and data model changes?  For example, does the entire application need to be brought down in order to apply a patch that may impact only a single customer?  Are there penalties associated with application uptime?  In other words, does the vendor need to pay a penalty to the customer if the application does not achieve a particular uptime Service Level Agreement (SLA)?
• Customer onboarding.  What type of database administrators (senior, junior) does the vendor need to employ for customer onboarding and what is the ratio of administrators to customers?  For example, if the multi-tenant architecture requires complex modifications to the application’s database then the vendor will most likely need to use senior database administrators for customer onboarding?  Will junior services personnel be able to configure the application to the customer’s needs or will more senior personnel be needed?  The seniority of the required personnel of course impacts the cost of the onboard process.
• Customer lifecycle management.  How easy will it be for the application to meet a customer’s growing usage (number of transactions processed by the application per unit time, size of the data, diversity of usage and number of organizations from the same company using the application)?  Will the vendor need to make changes to the database or to other components of the application as the usage increases?  How expensive are the optimizations the vendor needs to perform in order to keep the application running properly and how frequently do they need to be performed?  How expensive is each such potential change?  What will it cost to the vendor each time a customer leaves the service (in addition to the lost recurring revenue)?

I’m certain that there are several other questions related to multi-tenant architectures whose answers impact the economics of running a SaaS business.  However, I hope I have been able to provide you with a glimpse on how we as investors look at multi-tenancy and its impact on a SaaS company’s business model.