The relationship between legacy and digital systems – and those who work with them – is often misunderstood. Businesses talk about phasing out and automating the former to free up budget and resources for the latter, with the assumption that they’ll need to tolerate some level of coexistence, at least for the foreseeable future.
Additionally, the legacy and digital teams often work very separately from each other, with different goals and strategies, rarely collaborating let alone communicating. Trust between these groups is low, with fully half of businesses recently studied citing legacy systems as the biggest hurdle to digital transformation. Meanwhile, the legacy team figures its dwindling budget and the savings being reaping through automation are being soaked up by digital initiatives. Not to mention, at the end of the digital transformation rainbow, they figure, they’ll be out of a job.
It doesn’t need to be this way – and it shouldn’t. Far from just keeping the lights on or being considered an unwelcome necessity, legacy IT teams can enrich and enable the work of digital teams. Indeed, the former can produce valuable byproducts that, when applied to digital work, can accelerate these initiatives and help produce meaningful outcomes. By establishing this “byproduct mindset,” organizations can enable a cycle of improvement between the two groups, where the product of the one enables the other.
Legacy, with an Eye on Digital
Enterprise automation is one area that can fuel a healthy legacy-digital cycle, particularly when it comes to quality assurance activities, infrastructure and traditional data services. Note that I say “enterprise,” not “legacy” automation – the automation strategy itself should be the driving force, not whether it’s being applied to legacy or digital systems. The work should be done with a focus on future solutions and reusability, not just the here-and-now. This includes the tools selected, the resources trained and deployed and the ROI measurement approach.
Other reusable byproducts include:
- Data management scripts: There are many similarities between legacy and digital data when it comes to preserving, preparing and producing both types of data, as well as administering it (although access and real-time analysis are bottlenecks for legacy data). Many database assets can be designed for use across digital and legacy environments.
- Configuration and release procedures: Regardless of legacy or digital, the string of corporate applications will follow standard procedures in order to be configured and released in production environments. Automation scripts can be heavily reused across the board if designed carefully.
- Quality assurance automation: A well-architected automation process can be reused in both in-stream and regression phases for both legacy and digital systems. Design and implementation can start in the digital systems and permeate to legacy in order to achieve standardization, centralization and optimization.
When these elements integrate well with the automation strategy of core digital initiatives, the business can optimize its modernization efforts from the get-go, leading to reduced costs and faster time to market for the resulting products and services. Businesses can also avoid the need for future product rationalization by ensuring that both teams select the same tools for their automation needs.
We worked with a financial services firm that essentially reinvented the wheel when it came to digital, rather than identifying and reusing the assets and talent resources that its legacy team had used for automation. By doing so, the business was missing the opportunity to accelerate its digital endeavors for the entire enterprise. Our approach of connecting the dots helped the company not only optimize efforts across the two groups but also accelerate digital at speed.
Capturing Knowledge for Future Generations
A second area that’s prime for legacy-digital collaboration is knowledge management and knowledge transfer. When legacy teams capture and document knowledge of legacy applications (such as business rules, process and data flows, code documentation, etc.) it can serve as a valuable byproduct for digital teams to:
- Reverse/forward engineer when digitizing these applications in the future.
- Better understand corporate applications to incrementally apply digital transformation logic.
By applying this knowledge, digital teams can build more intelligence into automated bots because the knowledge is continuous, from legacy to digital. This requires the teams to work with a holistic mindset and gain a sense of how their piece fits within the entire enterprise IT stream.
Byproducts can also flow in the opposite direction, from digital to legacy. A lot of the work we do in artificial intelligence (AI), machine learning and robotics involves using bots to capture information on how applications work, what they do, how they connect to other systems and what data they generate. The resulting knowledge of this “listening” process can be applied to both legacy and digital work, as the bot is often capturing knowledge from both types of systems.
Establishing a Collaborative Mindset
To better connect their legacy and digital teams, CIOs need to establish ongoing collaboration, work exchanges and resource rotation between the two sides. Otherwise, it isn’t easy for the legacy teams to stay motivated with existing work. And some team members may fear that they will lose their jobs once the digital initiatives are complete. The change in behavior that businesses need from their IT organizations must start from the top.
In the end, getting legacy and digital to play nicely together only makes good business sense. After all, today’s digital is tomorrow’s legacy – it’s a continuous cycle and a never-ending story. By finding a way to enable the work of each other, businesses will accelerate their digital initiatives for years to come.
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