The recession has impacted us all in varying ways, both personally and professionally. On the business front, most companies have had to come to terms with cutbacks in budgets and spending. They’ve been very diligent about trimming expenses and, in particular, reducing capital expenditures. As we prepare for the imminent economic recovery (we can only hope), it is a good time to take stock of what behavioral changes might continue longer term.
After the painful reductions in staff and capital expenditures, many companies will be reluctant to grow these areas even when the recovery is in full swing. It seems there is a very real movement towards “pay for use” rather than “purchase and deploy in-house.” We’ve already seen multiple waves where this has happened in the past and it seems a natural progression. For example, the movement from in-house power plants to utility services, from in-house payroll to external payroll services, from in-house manufacturing to external contract manufacturing, from in-house call centers to outsourced call centers. It really comes down to capital conservation, organizational core competencies, and economies of scale where service delivery and infrastructure costs can be amortized across multiple companies.
If we look specifically at software, the Software as a Service (SaaS) and cloud computing models support the concepts of paying for use, conserving capital, focusing on organizational core competency, optimizing staffing levels, and providing a common service to multiple companies. As a result, these models deliver better returns on the investment in the underlying infrastructure and more cost-effective solutions for all companies served. We are already seeing the effects of this with the growth rates being reported by SaaS companies, while on-premise software license revenues are stagnant or declining.
The SaaS “pay for use” model continues to gain traction due to the benefits it offers companies, including:
- There are no upfront capital expenditures for software and hardware;
- Multi-tenant architecture means infrastructure supports many customers and costs are amortized accordingly;
- IT staff is tasked with minimal requirements for deploying and maintaining the solution;
- Internal staff can focus on the company’s core competences;
- The use of Web 2.0 technologies in most SaaS applications improves accessibility and ease-of-use, leading to wider adoption and usage;
- Subscription pricing scales linearly with use and is an operating expense rather than capital expenditure;
- The solution is low risk since the subscription can be cancelled or simply not renewed if there is insufficient value received.
What might not be so obvious is the extra capabilities that can be achieved with a SaaS solution that would be difficult or very costly to achieve with an on-premise solution. One analogy would be the fundamental shift that occurred in the corporate aviation world with the introduction of NetJets. Prior to NetJets, companies had to have their own private aircraft or perhaps arrange a partial ownership of a specific plane. When NetJets arrived on the scene, many of the same advantages I outlined for SaaS applied:
- Costs could be shared across multiple companies;
- Companies benefited from reduced capital expenditures (although these weren’t entirely eliminated until the Marquis Jetcard offering arrived);
- Companies didn’t have to have pilots and crew on staff, etc.
But NetJets also brought something that was very expensive to do internally: guaranteed aircraft availability at a large number of airports within a four-hour window.
This idea of additional value can also be delivered with the SaaS model – accessibility from anywhere with an internet connection, ease of use to ensure widespread adoption, and a cost-effective model that means it is viable to provide the solution capabilities to a much larger audience.
This is particularly relevant for providing operational intelligence (OI) solutions that help companies optimize operational performance. Compared to traditional business intelligence (BI), which has typically been used by business analysts to provide information to senior management for strategy and planning, OI has created new requirements:
- The number of people who make daily operational decisions is much greater than those making strategic business decisions, hence accessibility and cost-effectiveness is very important.
- The timeliness of decisions is critical to success, meaning that OI has to operate in “right-time” – that is, with time granularity that supports operational decision making.
- Analytics that help identify the root cause of performance issues, characterize those issues and determine the most effective corrective actions must be easy enough to use and understand for everyone. It’s no longer acceptable for these analytics to be suitable only for analysts and statisticians.
- By leveraging investments in existing systems – including BI implementations – operational intelligence is a great example of SaaS-based solutions that are delivering incremental value over on-premise solutions.
The time is right for companies to make a permanent move to “pay for use” rather than purchase software so they can reap the rewards of reduced cost, reduced staffing requirements and reduced capital, while also benefiting from additional capabilities not previously available. This could be the inflection point for SaaS, and in the future, on-premise software may be as unusual as in-house power generation.
About the Author
Wayne Morris - President, CEO
Wayne Morris has more than 25 years of experience in executive management, strategy, marketing, sales and technical roles in software, services and hardware companies. Most recently Wayne was Senior Vice President of Worldwide Marketing for McDATA and previously, he was the CEO and Managing Director of Citect Corporation, an industrial automation software company listed on the Australian Stock Exchange. As part of his commitment to technology and business, Wayne has spoken at many industry conferences and is co-author of "Foundations of Service Level Management" published by SAMS in 2000.