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Management discipline: Software procurement

How companies select SaaS solutions, implement them effectively, and measure their benefits

Article

  • Executive Summary

    Over the past three decades, enterprise software has evolved from a few central systems to highly complex tool landscapes. Today, organizations work with a multitude of specialized applications, but there is a lack of transparency regarding actual usage, costs, and ultimate value contribution. The success of new software depends on consistent alignment with business objectives, integration into the working reality of employees, and embedding in governance and compliance structures.

  • From core systems to the digital work environment

    In the 1990s, a small number of systems formed the stable basis for financial processes, human resources management, and production planning. Introducing new software was a lengthy and investment-intensive process, with responsibility lying almost entirely with the IT department. With the functional specialization of the new millennium came new tools for individual areas of the company. For the first time, specialist departments became active decision-makers, while integration and data consistency gained in importance. With the breakthrough of cloud and SaaS, software transformed from an internal management system to the central working interface of entire organizations. Applications could be procured without large initial investments, departments built their own tool landscapes, and digital processes often emerged in parallel. Today, large companies use several hundred applications. At the same time, a significant portion of expensive licenses remain unused and data is often stored in separate systems. Investments are increasing, but controllability is decreasing. However, the cause of this is not the technology itself, but the lack of connection between software use and measurable impact.

  • The selection of tools: A business management issue

    Many companies select software purely on the basis of selected functions. In a fragmented system landscape, this approach inevitably leads to redundancies and, accordingly, to acceptance problems among employees. Successful organizations therefore do not start by looking for a tool, but by formulating a goal for improving results. Only when it is clear which KPI is to be influenced and which process is to be improved can it be assessed whether the introduction of a new tool makes strategic sense. This also changes the way economic efficiency is viewed: in addition to license costs, more attention is paid to onboarding costs, the general need for organizational change, integration capability, and long-term scalability, which has a direct impact on effectiveness. Software is no longer evaluated as an isolated investment, but as part of a value creation system.

  • Acceptance of software in everyday working life

    But even if software is carefully selected at the management level, its success is determined by its daily use. For employees, every new system means a change in their usual way of working. They have to enter information in a new form, switch between applications, or adapt their processes. If this does not result in a noticeable improvement in their work, parallel shadow solutions may emerge—regardless of how powerful and versatile the introduced tool actually is. Acceptance arises when software reduces complexity, provides orientation, and, in some cases, makes the user's own contribution to the overall result visible. Users consistently use systems when they recognize that their inputs improve decisions, simplify coordination, or clarify priorities. If this connection is missing, data entry is perceived as an additional administrative burden. This makes the user's perspective a central part of the selection process. Solutions that are tested in real-world work scenarios and can be seamlessly integrated into existing processes achieve significantly higher usage rates than systems that have been evaluated exclusively at the management level. Understanding plays a particularly crucial role when it comes to AI-supported functions. Results must remain comprehensible in order to be accepted in everyday operations. Another important aspect is well-designed interfaces and processes that enable largely intuitive use.

  • Governance, compliance, and AI are changing decision-making logic

    With the shift of data to the cloud and the integration of generative LLMs and AI, software is becoming an integral part of a company's regulatory architecture. Questions about data locations, access rights, audit-proof documentation, and the traceability of algorithmic decisions are now key selection criteria. The EU AI Act reinforces this development, as companies will in future have to demonstrate how AI is used, who is responsible, and how human control continues to be ensured. A lack of governance is the most common cause of uncontrolled tool landscapes. It not only leads to unnecessary cost increases, but also to legal risks and even the loss of data sovereignty. Software selection thus also becomes a decision about controllability and regulatory sustainability.

  • Value contribution through organizational anchoring

    There are several development steps between acquiring a license and achieving a business impact. Many companies initially only record whether a system is in place. More progressive organizations measure usage. However, real control only comes into play when the impact on throughput times, decision quality, cost structures, or performance indicators becomes visible. Only this connection allows for a reliable assessment of the return on investment (ROI). Technical implementation is only one part of the introduction process. Systems only become effective when they are linked to goals or OKRs, reporting structures, and decision-making processes. Usage does not arise solely through training, but through concrete use cases in a real work context.

  • Software as an actively managed portfolio

    Leading companies no longer treat their applications as a historically grown collection of tools, but as an investment portfolio. Transparency across all systems, regular evaluation of their value contribution, clear procurement guidelines, and consolidated data models replace isolated decisions in a fragmented environment. The goal is not to reduce software, but to maximize its impact while controlling costs and risks.

  • Conclusion

    With SaaS, AI, and LLMs, software has fundamentally changed its role. It no longer merely supports existing processes, but has become a central component of corporate management. Its success depends on how consistently it is aligned with performance targets, integrated into the working reality of employees, measured in terms of its benefits, and secured by regulatory measures. Software selection thus becomes a management discipline. It combines efficiency, value contribution, acceptance, and compliance, and thus plays a key role in a company's future viability.

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