As the flaws in the ASP model were gradually being exposed, a second generation of vendors began to emerge. These vendors did not take traditional enterprise software and try to force it into a hosted world. Instead, they created new software platforms fundamentally designed for on-demand delivery that had the following characteristics:
· One, single version (with automated upgrades)
· A single, consolidated platform (the entire software stack)
· One target environment
· One deployment methodology
· Automated customer provisioning (new customers were simply turned on)
· Less configuration, more automation. Users were offered simpler versions of the applications that satisfied the 80/20 rule, but radically reduced the configuration burden.
By rationalizing the problem and providing a stack that automates the provisioning, maintenance, and normal plumbing that goes along with the implementation and maintenance of software, SaaS fundamentally changed the economics of software delivery. You may not be able to fully tweak every piece of the software, but people have discovered that most often, they don’t really need to. Instead of selling the kit to build the car, these companies sell the entire vehicle pre-assembled.
SaaS model aligns vendor and customer incentives
Moreover, since SaaS providers incur the cost of maintenance, operations and management, they are driven to reduce these costs. It has been said that only 20-30% of the total cost of a software platform is license cost – the remainder is the cost of implementing, managing, and operating the software (people, hardware and other resources). By focusing on this previously ignored part of the software value chain, SaaS providers can dramatically shift the value equation.
Operational SaaS is a success – but then there’s the BI problem. How do you analyze the resulting data?
As mentioned earlier, software companies that provide operational applications (e.g., CRM, ERP) embraced the SaaS model first. After a few years of growth and customer expansion, customers had accumulated a significant amount of business critical data in their operational solutions and naturally demanded analytical solutions for reporting. Since analyzing data directly against an operational database can be catastrophic, vendors began searching for analytics partners.
SaaS operational vendors try to partner with traditional analytics solutions – with unimpressive results
Although these operational companies were based on the SaaS model, many of the potential partner vendors that they evaluated were traditional, behind-the-firewall BI solutions that were already established in the analytics industry. Unfortunately, these traditional analytics vendors did not have true SaaS offerings, or were struggling to have their traditional model wedged into a SaaS-like delivery. As a result, the operational software SaaS players were partnered with sub-optimal solutions.
Most often, the analytics partners’ setup costs and deployment method limited the SaaS vendor to the custom, one-off software delivery business when it came to analytics; they lost the compelling economics of their mainline businesses. In a way, the analytics component ended up as a one-off consulting organization, an inefficient adjunct to the more scalable SaaS operational software model. The takeaway is clear: mixing software models doesn’t work. A SaaS vendor can’t redeem a traditional BI partner, and a traditional BI partner can’t add much value to a SaaS vendor.
Stay tuned for Part 3: Business Intelligence in a true SaaS model
