Is it possible to have too much of a good thing? Aesop and Shakespeare would say yes—and your company’s tech leaders may think so, too.
The saying is applicable to the inefficient organizational use of technology stacks, or a set of software systems used to get work done. When taken in pieces, each tool may be beneficial. In combination, however, they may be getting in each other’s way, leading to inefficiencies and wasted expenditures.
A good tech stack should be user-friendly, resilient, efficient, and secure. When building it, chief technology and/or information officers (CTOs/CIOs) must take into account reputational, financial, regulatory, and legal risks. They must also work within a budget, which means preparation is key.
A vision is a good start, but with today’s ever-changing technology landscape—especially in light of the generative artificial intelligence boom we’re experiencing—foundational knowledge is just as important.
A 7-Step Approach to Building a Resilient Stack
KMPG outlines an approach to building a tech stack that can stand up to even the toughest of challenges:
- Identify the services and systems critical to the business and its customers, and the people, locations, and vendors that support them.
- Identify and assess for risk all data elements required to keep the organization’s critical business operations running. Data, and the assets that handle them like applications and infrastructure, must be carefully managed to an acceptable level of risk by committing necessary resources to sustain recovery point and time objectives.
- Plan for complex and sophisticated cyberattacks. This could include, for example, a ransomware attack in which data security is threatened and large-scale recovery and restoration efforts may be needed. Or consider planning for geopolitical developments that could prevent the ability of a vendor to deliver on its agreements.
- In developing the IT operating model, ensure that resilience is at the foundation. The model should bring diverse parts of the enterprise together with well-defined roles and responsibilities.
- Digitize and automate resilience processes through up-to-date, market-leading platforms to improve recovery consistency and efficiency. For example, the IT department may want to standardize recovery plan documentation and store it in a location or system accessible during an outage. Automate recovery testing, infrastructure, and application recovery using scripting and tools. Use AI for anomaly monitoring and detection.
- Routinely test resilience and recovery systems and processes to ensure they can be relied upon. Training exercises should be frequent, robust, and unannounced at times, escalating in complexity as the organization matures. These efforts should always include an inspection of lessons learned that develop into action plans.
- Include resilience requirements in the company’s vendor management program and hold critical vendors, including cloud service providers, to a high standard of availability and recovery.
A Holistic Approach to Stacking
About 45% of CIOs are beginning to work with their C-suite colleagues (CxOs) to bring IT and business area staff together to co-lead digital delivery on an enterprisewide scale, according to Gartner’s annual global survey of CIO and tech executives. The 2024 Gartner CIO Agenda gathered data from 2,457 CIO respondents in 84 countries and all major industries. The survey uncovered three distinct CIO profiles that encompass how CIOs accelerate and scale digital delivery:
- 55% of CIOs embraced an operator mindset, where the CIO retains digital delivery responsibility and partners with CxOs as sponsors of business area digital initiatives.
- 33% are explorers who have begun to involve CxOs and business area staff in digital delivery activities.
- The remaining are franchisers who co-lead, co-deliver, and co-govern digital initiatives with their peers.
“CIOs face a paradigm shift, sharing leadership responsibilities with CxOs to deliver digital success, while also contending with budgetary pressures and transformative technologies,” said Mandi Bishop, distinguished vice president and analyst at Gartner. “To successfully lead digital transformation initiatives, CIOs must co-own efforts with business leaders to place the design, delivery, and management of digital capabilities with teams closest to the point where value is created.”
Don’t Overdo It
A global survey by Dynatrace of 1,300 CIOs and tech leaders at large organizations found that organizations are struggling to manage the vast data they create. About 88% of organizations surveyed say the complexity of their technology stack has increased in the past year, and 51% say it will continue to increase. The average multicloud environment spans 12 different platforms and services, and 87% of technology leaders say this complexity makes it more difficult to deliver outstanding customer experiences; and 84% say it makes applications more difficult to protect.
Some 86% of technology leaders say cloud-native technology stacks produce an explosion of data that is beyond a person’s ability to manage. About 81% of technology leaders say manual approaches to log management and analytics cannot keep up with the rate of change in their technology stack and the volumes of data it produces. The same percentage say that the time their teams spend maintaining monitoring tools and preparing data for analysis takes away time from innovation.
AI to the Rescue?
The Dynatrace survey also found that 72% of organizations are using AI for IT operations (AIOps) to reduce the complexity of managing their multicloud environment. Yet nearly all tech leaders (97%) say probabilistic machine learning approaches have limited the value AIOps delivers due to the manual effort needed to gain reliable insights.
“Without the ability to transform the high volumes of diverse data from cloud-native architectures into real-time, contextually relevant insights, IT, development, security, and business teams struggle to understand what is happening in their environment and lack the answers needed to solve issues quickly and decisively,” said Bernd Greifeneder, CTO at Dynatrace. “While many organizations turn to AIOps, they often encounter limited value due to reliance on probabilistic methods, which can be imprecise and time-consuming to implement. To overcome the complexity of modern technology stacks, organizations require advanced AI, analytics, and automation capabilities. By unifying diverse data, retaining its context, and powering analytics and automation with a hypermodal AI that combines multiple techniques, including causal, predictive, and generative AI, teams can unlock a wealth of insights from their data to drive smarter decision-making, intelligent automation, and more efficient ways of working.”
How Talent Mobility Pros Think About Tech Stacking
While embracing new technology can be exciting for mobility professionals, it’s important “to pause, reflect, and fully understand their potential impact on a company’s mobility programs before adopting more and integrating them,” said Rob Giese and Trent Krause of Graebel. They offer this advice to help talent mobility professionals decide whether new tools are worth the investment:
- Assess your need and how well the tech will assimilate into your organization, leveraging key stakeholders for input and seeking leadership perspective.
- Understand the end user needs.
- Will they use it or is there too much complexity to be useful? Ensure you understand the related process and data quality. Rarely does a new tool solve problems without first addressing workflows and data.
- Is the tech representative of a solution that user focus groups have identified as a need?
- Is the technology regionally focused, or can it be used globally? Consider browser limitations, language, licensing requirements, and government restrictions.
- Define:
- How will it add value?
- Will it save time? If so, how?
- Will it reduce costs?
- Can it improve communications and timeliness of distribution?
- What options are available today? Are similar tools part of a package that the company already owns?
- Understand the resources (time, people, money) required to implement and maintain the technology.
- Is it scalable to flex with your program and are there costs for future enhancements/changes? Utilize your IT team to ensure the new solution is scalable, supportable, and secure.
- Consider piloting the tech to prove its value before fully investing and deploying it as a standard tool. A proof of concept approach is not always needed, but it’s a powerful way to better understand the overall business case, unforeseen challenges ahead, and roles and skills needed, while engaging other stakeholders for support and understanding.
Don’t Count Your Chickens Before They Stack
It’s a Lego City dreamland for tech professionals out there—to the casual eye, at least. So much hardware and software to choose from, to stack on one another. There’s always something coming down the line to make things better, smarter, more efficient, friendlier, and, yes, cooler.
AI is all the rage today, but will it be tomorrow? Will quantum computing make AI anachronistic? Or some yet unheard of technology?
“AI is here to stay,” said Krause. “But it’s not a project or technology implementation—it’s more of a means to an end, and not the end in itself. An effective AI strategy is not just about the technology, but also about how it aligns with our business goals, increases value, and how to best manage associated risks.”
For talent mobility professionals, Krause advises a judicious approach to generative AI-based tools and process adoption. “Seek to gain a thorough understanding and how it can be applied in various business processes,” he said. “Quantum computing will only make AI more powerful, smarter, and faster. The combination of quantum with AI is expected to be mind boggling.”
For now, the best an organization can do is determine what objectives are most important for it, and how to achieve those objectives within budget, while making things as efficient, user-friendly, and secure as possible for employees and clients alike. When a new addition is being considered, it must fit with legacy systems and be capable of growing as an organization and its needs grow. Remember, all that glitters is not gold!