Although digital transformation and digital optimization sound similar, they serve different purposes for companies.
Digital transformation fundamentally changes the way a company works and delivers value to customers, employees and other stakeholders. Digital optimization focuses on refining and improving specific IT processes and systems to increase efficiency and effectiveness.
Learn more about digital transformation vs. digital optimization.
Digital transformation enables companies to leverage technology to improve and adapt to changing business and market needs. In other words, digital transformation can be transformative. However, it also carries significant costs and risks, including the growing problem of transformation fatigue.
Today, companies are under increased pressure to do more with less, which could make digital optimization a better approach.
What is digital optimization?
While digital transformation seeks a new sweet spot between IT and business, digital optimization realigns IT to best align with current practices. Digital optimization generally does not disrupt business.
This method is also less likely to cause fatigue because it minimally impacts departments that rely on digital processes. However, the short-term benefits are likely to be small or too small.
What you should pay attention to when digitally optimizing
The first question to ask when considering a digital optimization plan is whether the benefits are too small to justify the costs and effort. CFOs expect projects to deliver an ROI equal to or greater than their internal rate of return (IRR).
CIOs and IT leaders should consider assessing whether ROI meets the IRR target before pursuing digital optimization. If not, a major redesign may be required or planners may need to ask a different question.
The question is whether allocating part of the budget to an orderly IT infrastructure modernization will meet most, if not all, of the company’s digital optimization needs. However, it is rare that the cost of a transformation project is limited enough to fit into modernization plans.
Since optimization typically requires less investment, a large portion of the project could fit into a modernization plan. If the optimization project can cover some of the costs within a modernization budget, it can increase the project ROI enough to make optimization a viable choice. If the optimization meets all ROI requirements, the question arises whether the transformation is still better in terms of achieving more per unit of investment.
If optimization cannot meet the project’s ROI requirements, transformation may be the only option.
What you should pay attention to during a digital transformation
If you have undertaken a digital transformation project less than two years ago, it is rarely easy to find support for another project. The average financial amortization of technology investments is three to five years.
Another transformation project will likely require a write-off of some of the residual value of the equipment, making it harder for the CFO to justify a brand new project.
On top of that, leading another transformation project so quickly can lead to transformation fatigue. Unless there has been a major external driver since the last project, such as: If something has developed, such as new competition or new regulations, you should only consider a new project if the company can derive extraordinary benefits from it.
There is also the possibility that the organization is currently completing a project. If the company still has a transformation project to complete, the rule of thumb is to choose the option with the highest ROI.
Companies also say that if a transformation project has not been completed in the last five or more years, the combination of organizational updates, market changes and technical upgrades since the last project will most likely result in the current relationship between IT and operations becoming stale.
For example, optimizing might leave too many unrealized benefits. In addition, technical debt accumulates during the process, putting stability, security and operations at risk. In this case, take a close look at transformation vs. optimization.
Assuming that the ROI of transformation is higher than that of optimization and that the last transformation occurred approximately two to five years ago, questions still remain.
For example, CIOs and IT leaders should consider the impact of the transformation on operations. The difference between digital transformation and digital optimization is that transformation not only realigns IT, but also operations and practices across the entire organization.
This almost always impacts productivity as workers adjust to a new way of doing their work. However, if this change occurs at a time of great opportunity, competition, or both, it could result in lost sales.
What to expect if a project fails?
CIOs and IT leaders should consider how much risk digital transformation entails compared to optimization, the more conservative alternative. The larger the project, the greater the scope of potential problems and the more things that can go wrong.
Failure of a transformation project will likely result in significant cost overruns, impact corporate departments more than expected, and increase digital transformation fatigue and technical debt.
If the ROI of transformation is low compared to optimization, risk could tip the balance in favor of optimization.
This benefit is intended to demonstrate that the difference between digital transformation and digital optimization is often subtle.
The challenges of moving from optimization to transformation
Once a project is underway, new situations often arise that were not considered before approval.
For example, employees may need help with abstract visualization of application changes and identifying problems and opportunities as the project progresses.
The difference between digital transformation and digital optimization is that transformation not only realigns IT, but also operations and practices across the entire organization.
There should be a mechanism to address these concerns, including defining a point at which optimization must become transformation and how to prevent that transition if it poses a threat.
Changes proposed later in a project’s schedule are more likely to impact the project’s success. If changes in one area impact other areas, project managers can either pause the project for review and consider moving to digital transformation, or hold off on the changes until the project is complete and then conduct a separate phase to implement the changes to be carried out.
Proposed changes resulting from project activity are likely to continue. Effectively managing these changes becomes more complex as their frequency increases.
Companies should not commit any Optimization project change that changes dependencies between project tasks without thorough review. Any proposed change that requires an actual operational change should be considered a shift to a transformation model.
A pattern of minor changes proposed throughout a project could be an indicator that the initial project evaluation missed too many critical issues to be trustworthy.
Once a project is at the point of integration testing and requires direct employee involvement in evaluating input and output changes, postpone any changes that could impact the integration until a thorough review of the entire project design is completed.
The decision to move from optimization to transformation should always be made clearly, starting with the creation and approval of a digital transformation plan. However, expect change to increase the risk of transformation fatigue and take leadership actions to mitigate this risk.
What is the best approach to compare digital transformation and digital optimization? Imagine starting with a calculation of ROI for each activity and then considering the risks of each project.
Remember that transformation is a long-term strategy. Do not undertake a project if business or technological changes could render the transformed approach obsolete without achieving the expected benefits.
Tom Nolle is founder and principal analyst at Andover Intel, a consulting and analytics firm that first looks at evolving technologies and applications from the perspective of the buyer and the buyer’s needs. By nature, Nolle is a programmer, software architect and manager of software and network products. He has been providing consulting services and technology analysis for decades.
