With so many vendor-driven changes, it pays to assess the mission-critical nature of your systems – and what it costs to replace them – when you make your IT plans, argues Niel Nickolaisen, an advisor, author, and IT executive at Utah State University. In this article, he explains how to go about it.
No one knows better than a CIO the disruptive nature of the vendor and technology landscape.
New technologies are being developed all the time, causing current technologies to become obsolete and creating significant disruption for the organizations using them. The marketplace, too, is dynamic. The fortunes of technology providers rise and fall, acquisitions abound, and users are impacted. At the same time, vendors may warn that their support programs will end or change their licensing models.
I’ll share just three examples from the last couple of years:
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A global tech giant acquired the market-leading provider of virtualization technology, revising the product structure and licensing model. in most cases, the changes resulted in higher —in some cases, much higher — licensing costs.
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A leading provider of workflow automation and collaboration tools was likewise acquired with the new owner changing the licensing model resulting in subsequent — often significant — increases in costs.
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A phone systems vendor changed its licensing model from a perpetual model (the price paid for the system plus an annual support and maintenance contract) to a subscription model – even for those customers with an on-premises system.
Such changes add up to a lot of upheaval for technology leaders. There might not be much we can do to avoid these disruptions — they can be sudden and are always outside of our control. (The firm that acquired the virtualization technology certainly did not ask me for permission or even if I had any concerns) . But there are ways we can prepare for them and mitigate their impact on our organizations.
Two Dimensions of Vendor Assessment
Before we get into the preparations, let’s consider two dimensions that can help IT leaders assess the potential impact of a technology or provider disruption: mission-criticality and switching costs.
Mission-criticality measures how deeply entrenched a particular technology or provider are within our technology stack and business processes. Switching costs are the time, effort and money it would take to replace the technology or provider.
Walking through the three cases described above helps illustrate how this would work.
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The acquisition of the virtualization provider with changes in product structure and licensing model. For many organizations, virtualization is the operating model and about as mission critical as it gets. A large percentage — sometimes 100% — of workloads are virtualized. A change in virtualization technology is highly-disruptive. As for the switching cost to replace the incumbent virtualization technology, the acquired provider had more than 90% of the server virtualization market. When we combine the “de facto” standard status of the virtualization technology and the extent to which it is intertwined with other systems, changing to a different virtualization technology could have significant ripple effects. For our purposes, we will categorize the switching costs as “high".
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The acquisition of the workflow automation and collaboration tool with increased licensing costs. The mission-criticality here will vary by organization. Some made the technology its standard and have a large number of automations built into it that they would need to replace should they opt for a different solution. However, typically, the workflow automation and collaboration technology is somewhat “standalone” with limited dependencies on other technologies. This standalone nature tends to lower the switching costs, although they could be significant for an organization that has deployed the technology to support a large number of processes. There are alternatives to the workflow automation and collaboration tool that can largely replicate the functionality. For our purposes, we will describe that the switching costs as “medium”.
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The phone system provider’s change from perpetual license to subscription model. This is an interesting example. It is mission critical, but the switching costs have changed over the past few years. There are plenty of cloud alternatives to an on-premises phone system that can be deployed relatively quickly. One possible switching cost is the replacement of legacy phone system handsets, but the work-from-home trend that accompanied the COVID shutdowns increased the use of soft-phone functionality, thus reducing that switching cost. There are expenses involved in implementing a new phone system – such as integration with CRM applications – but the implementation of a new system is less work than it used to be. For our purposes, we will hypothesize that the switching costs are “medium”.
The Process of Preparing for Vendor Disruption
Going through this mission-criticality versus switching costs analysis is a critical step in the process of dealing with technology and provider disruption. And it pays to do much of this work ahead of time so that even though we may be caught by surprise, we’re not flatfooted in dealing with it.
Following are the actions IT leaders can take to plan for unexpected changes:
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Complete a system inventory. IT teams should be doing this anyway as they identify modernization and rationalization candidates, but the inventory becomes valuable during disruption scenarios as well.
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Complete a lightweight assessment of the mission-criticality and switching costs for all inventoried systems. This doesn’t have to be scientific, but rather provide enough information to be able to determine options and alternatives for each.
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Perform a disruption analysis. Using the assessment above, identify the systems for which a change — in technology, provider, licensing model, cost, obsolescence — would be highly-disruptive.
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Develop responses for possible disruptions. For the highly-disruptive changes, intentionally explore and test alternatives. This could include not only research but also testing for ease of implementation, ease of use, and compatibility with the rest of technology stack. Replacements could be so disruptive that absorbing the changes makes more sense. For the changes that create a medium-to-high disruption, perform a less intense exploration of alternatives and options that will identify options and help prepare for possible disruptions. For the changes that are not meaningfully disruptive, deal with them as they occur.
We can test out this process on our three examples:
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The virtualization technology is mission-critical and has high switching costs. There are alternate virtualization technologies including migrating workloads to the cloud and technologies from other providers (but they are not widely used). Should we decide, in our analysis, that a significant change in our existing virtualization technology would cause us to replace it, we would allocate time and energy to exploring and testing the options to determine how well the other virtualization technologies work with the rest of our technology stack, for example. This analysis might cause us to define the size of the change in virtualization technology and provider that would trigger a change. An assessment of the alternatives, and data about price increases, will guide our decision on switching vendors.
- We have assessed the switching costs of the workflow automation and collaboration tool as a “medium” for switching costs, but we need to consider how widely and deeply the technology is used in our organization. If its use is limited to a small number of users, departments, and workflows, the impact of the cost increases will also be limited. But if it is our organization’s standard, the impact of the cost increases could be significant. Based on this assessment, we determine that we will assess the alternative technologies to determine the costs and benefits of replacing the incumbent technology.
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The phone system is interesting to assess. Do we prefer cloud options over on-premises systems? Then perhaps we do not need to complete our mission-criticality/switching cost assessment. Since the provider of the current system has already changed to a subscription model, the financial analysis is straightforward. Our analysis would identify the alternative technologies and providers and get subscription costs, costs to implement, costs to use, cost to support, architectural fit, and costs to integrate data. Then we would be ready should a change in pricing model trigger a decision to look at alternatives.
How and When To Use This Process
IT teams do not need to go through this process for every system or application. The focus should be on those technologies that are somewhat to incredibly difficult to replace.
A good approach is to perform this analysis as part of IT’s regular planning and prioritization cycle, alongside modernization and rationalization plans or as IT leaders build their technology and service roadmaps. It’s not necessary to overinvest in this process, but being prepared for what might happen has clear benefits. All most IT leaders have to do is consider their past experiences with technology and provider disruptions.
It nearly impossible to know what technology and provider disruptions might happen or when. But with some lightweight analysis to segment systems based on mission-criticality and switching costs, technology leaders can focus their attention on preparing for those that will have the greatest impact.
Written by Niel Nickolaisen
Niel Nickolaisen is Director of Enterprise Integrations at Utah State University and is leading the implementation of the processes and systems to enable comprehensive constituent lifecycle management at the university. The co-author of The Agile Culture: Leading Through Trust and Ownership and Stand Back and Deliver, he is as an advisor to several technology start-ups and sits on the board of a start-up accelerator. Previously, Niel held several technology and operational executive positions. Nickolaisen has an MBA from Utah State University, an M.S. in engineering from MIT, and B.S. in physics from Utah State University.