Post-implementation monitoring for a successful market go-live

The digital transformation of core banking processes is a monumental undertaking but, in the current market, it is no longer an option, it is a necessity. Organisation that embrace this shift to state-of-the-art digital systems unlock a future of enhanced customer experience and innovation, streamlined operations and improved agility (see Part 1 of this blog series[1]). Transformation journeys do not end, however, with the development of a new system (see Part 2[2]) or change management initiatives (see Part 3[3]), but rather with a successful roll-out and adoption. This is where the post-implementation monitoring steps in, playing a vital, yet often underestimated, role in solidifying and capitalising the benefits of the transformation to ensure long-term success. This last blog in the series explores Phase 6: Post-implementation monitoring and commercialisation (in dark blue in Figure 1) with a focus on lending process transformation as an example.

Figure 1: Overview of E2E tech-enabled transformation approach

The post-implementation monitoring consists of an initial hypercare period, followed by a period focusing on reflecting on the release and looking forward (leading to additional initiatives). No matter how meticulous the readiness planning, development or testing, unforeseen challenges can arise, and early identification and resolution prevents a snowballing effect. This is the reason for the hypercare period, an intensive phase that immediately follows the go-live. This short-term period, which usually lasts 4-6 weeks, ensures the system is stable and reliable before transitioning to business-as-usual (BAU). It is characterised by increased surveillance and proactive engagement to ensure rapid mitigation of associated risks, to facilitate adoption (both internally and externally) through a prompt response to concerns and any technical glitches. This additional attention allows for enhancements to system functionality, reinforcing confidence in the system overall. This phase typically involves continuous monitoring, frequent updates, and adjustments based on real-time feedback. The goal is to minimise operational disruptions, thereby preventing minor problems from escalating into major disruptions. Beyond the technical support, the hypercare period serves as a bridge to full operational handover, as well as planning for the decommissioning of previous systems. Recent research suggests that 90% of respondents encountered a negative effect from the lack of post-implementation monitoring[4]. The post-implementation phase then further focuses on quantifying the impact of the release, applying iterative improvements and identifying additional initiatives. To enable these outcomes, this blog dives into establishing three key success factors:

Effective feedback loop	Insightful KPI monitoring	Capitalised data analytics

A robust reporting framework is crucial to unlock these success factors. Reporting is often overlooked in the early stages of a tech-enabled transformation, but it should be considered a key requirement during the design phase. Tailored insights from specific data points are essential. Therefore, reporting should be tested and functional before the post-implementation monitoring period and further consolidated with the shift to BAU support. While there are a variety of design principles to consider in a target reporting framework (see Figure 2), internal post-implementation reporting is driven by three key characteristics: standardised reporting formats for simplified trend analysis and anomaly identification, regular reporting schedules in the first weeks following go-live; and consistent data across all sources and journeys to avoid discrepancies, with a strong focus on robust data governance.

Figure 2: Overarching maturity levels for reporting frameworks

Post-implementation monitoring: Top 3 success factors

Success factor 1: Issue management through an effective feedback loop
The current digital age fosters the wide spread of information, substantially increasing exposure to immediate feedback (e.g., through blogs, social media, or expert opinions). While this external loop provides valuable insights, it can pose a reputational risk, especially during a tech-enabled go-live. To mitigate this risk, organisations can include external voices (e.g., customers, online experts) in pre-release testing and actively prompt post-release external feedback in a controlled way. For example, by integrating feedback loops directly in the tech-enabled process (e.g., in-journey screens and structured call-backs), organisations can enable a continuous flow of user information to avoid being blindsided. Feedback collection focuses on all customers who have started the journey, regardless of the outcome. Understanding why some customers abandon the journey allows for further targeted improvements. By analysing all sources of feedback, key issues can be identified, and continuous improvements prioritised, especially in the hypercare period.

Integrated external feedback enables prompt identification of issues but, a subsequent prompt resolution requires seamless internal collaboration. Establishing a specific taskforce, comprising of all affected front-to-back units (from relationship managers to operations), and an internal feedback loop through daily alignment calls, enhances transparency and ensures the stability of the new system. Progressively, as confidence increases, dedicated hypercare efforts will decrease, before shifting to BAU support. Ensuring clear allocation of responsibilities, timelines, and next steps is key for the success of the post-implementation monitoring period. Additionally, ensuring people with the appropriate expertise (e.g., IT representatives) and/or decision-making power are involved allows for prompt mitigation and resolution of issues. Integrating these standards avoids the pitfall which 80% of respondents encountered of undefined escalation paths[4]. By creating an open culture of communication and shared ownership, an internal feedback loop becomes a powerful enabler for continuous improvement with insights stemming from external feedback and reporting (see Figure 3).

Figure 3: Feedback loop towards an enhanced journey

Success factor 2: Actionable insights through KPIs
Without clear visibility on the journey, it becomes impossible to identify areas in need of immediate attention or to monitor success against targets. A comprehensive reporting framework, along with defined key performance indicators (KPIs), act as a real-time diagnostic tool, allowing for quick identification and therefore minimisation of potential disruptions that detract from the user experience or system efficiency. Even though KPIs act as an integral component of the post-implementation monitoring period, only 13% of respondents indicated that they use well-defined targets and KPIs[4]. During the design phase it is essential to define a list of data points which are required for the target KPIs. Across selected success dimensions, KPIs should also be specifically defined and tracked ahead of the roll-out to allow for comparison and ensure a full picture view[5].

As confidence increases and monitoring shifts from hypercare to BAU, the scope of KPIs also shifts. Initially, they should focus on digital adoption, the overarching application funnel and customer profile. At this stage, clear transparency on how many customers start the journey, but also where in the journey they stop provides insights into potential pain-points. Clearly visualising the funnel (see Figure 4) provides information on, for example, customer cancellation, system rejections and the approval rate, allowing the organisation to quantify the success of the system, as well as identify issues. In the first two weeks of a recent lending transformation that we supported we identified through analysis of the funnel and tailored customer call backs that no application was being finalised because there were problems with the digital signature. Progressively KPI monitoring will shift from journey-specific to strategic, focusing on system efficiency and effectiveness. Examples of critical KPIs are the Net Promoter Score (NPS) for customer satisfaction, processing times for system efficiency, and the first time right (FTR) rate for system effectiveness. Transformations are often significant investments; selected KPIs, such as return on investment (ROI) or cost reductions can help measure the transformation success, fuelling interest in future digital initiatives.

Figure 4: Illustrative application funnel across the E2E journey

Success factor 3: Competitive advantages through analytics
Data is the foundation of modern banking. Digital journeys offer a wealth of data points to be transformed into actionable insights. During the post-implementation monitoring period, data analytics becomes key, beyond monitoring, to unlocking informed decision making. Understanding how receptive various customer segments (e.g., existing customers vs. new customers) are to the new transformation allows for opportunities to be tailored. Additionally, in best practices, commercialisation efforts are accompanied by marketing campaigns a few weeks after go-live to increase reach. In a recent study 80% of respondents reported that their commercialisation was negatively impacted by improper marketing budget allocations[4]. The post-implementation monitoring period also helps determine the timing of marketing campaigns. In modern banking, marketing efforts are data-driven, allowing for targeted campaigns capitalising on specific customer needs and behaviours. Marketing segmentation based on, for example, online behaviour, demographics, or purchase history enables organisations to tailor campaign messaging and focus. Integrating predictive analytics provides an opportunity to anticipate customer needs and tailor initiatives. Furthermore, data empowers campaigns success monitoring, with measures like click-rate, conversion rate or engagement levels. Organisations can optimise their campaign results through data-driven adjustments.

Analysis of user behaviour patterns in the release also allows organisations to uncover opportunities for future growth, whether on a product or offering level. A dedicated team comprised of marketing, product and data experts can delve deeper into the data and identify potential opportunities for cross-selling and other initiatives. By analysing user feedback alongside system usage data, the dedicated team can pinpoint unmet or partially met customer needs and translate them into concrete product offerings. For example, in a previous lending transformation we supported, it was observed that 1st time mortgage clients still insisted on face-to-face branch meetings despite the new tech-enabled journey. Therefore omni-channel capabilities were prioritised. Internally, analytics can help the organisation in identifying staff adoption through process mining (e.g., to identify areas where the employees do not yet leverage the full capabilities of the new journey). A data-driven approach fosters continuous innovation, ensuring organisations remain at the forefront of a rapidly evolving financial landscape. Organisations are increasingly exploring generative AI to spot data abnormalities or trends and to provide teams with insights faster than manual analyses would[6].

Conclusion
The few weeks following a tech-enabled transformation release are critical to safeguard its success and reinforce a positive first impression in the market, both internally and externally. While monitoring and problem solving are key in this period, careful study of the situation and adjustment of the releases and initiatives to follow is also a priority. Analytics can provide insights with which to prioritise upcoming features based on market appetite, customer preferences and internal adoption, ultimately enabling the value chain and its KPI. Additionally, taking the time to reflect on the transformation and identify potential lessons learned and opportunities for improvement will foster success in further initiatives in the long-term.

At Deloitte we have experience in supporting Financial Service Institutions as they seek to maximise the impact of and insights from the post-implementation monitoring period through a set of enablers and accelerators (e.g., lessons learned, daily reporting template, tactical and strategic KPIs for core value chains).

Reach out to us if you want to participate in the Deloitte Banking Digital Transformation survey (2024 edition) and gain deeper insights into your bank’s positioning relative to industry peers, or if you want to discuss how we can help support your preparations for your next process transformation initiative.

References

[1] Navigating tech-enabled transformation of core banking processes | Part 1: Business execution readiness as a foundation for success - Banking blog (deloitte.ch)
[2] Navigating tech-enabled transformation of core banking processes | Part 2: IT development and testing - Banking blog (deloitte.ch)
[3] Navigating tech-enabled transformation of core banking processes| Part 3: The importance of non-IT change management - Banking blog (deloitte.ch)
[4] Deloitte. (2023, September). Deloitte Banking Digital Transformation Survey.
[5] Deloitte. (2023, February). Measuring value from digital transformation. Retrieved from https://www.deloitte.com/global/en/issues/digital/maximizing-value-using-digital-transformation-kpis.html
[6] Deloitte. (2024, January). Bridging measurement divides in AI, cloud and cyber. Retrieved from https://www2.deloitte.com/us/en/insights/industry/technology/measuring-cyber-ai-and-cloud-kpis.html?id=us:2em:3na:4diGLOB176936:5awa:6di:MMDDYY:author&pkid=1012003

Key contact

Eric Gutzwiller - Director, Financial Services Transformation

Eric is a Director in the Financial Services Transformation team of Deloitte's practice in Zurich. He focuses on leading process optimization and digitalization as well as TOM design projects. He brings over 11 years of strategy consulting experience in financial services for both leading global institutions and emerging players, as well as central banks and regulators in several established markets (Switzerland, UK, US, HK, Singapore, Germany, Canada) and emerging ones (CEE, Middle East).

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Nadia Moutiq - Manager, Financial Services Transformation

Nadia is a Manager in the Financial Services Transformation team of Deloitte's practice in Zurich. She brings more than 6 years of experience at several financial services providers in Switzerland, Europe and the Middle East in medium to large, complex and tech-enabled front-to-bank core banking process transformation programs covering topics from change management, smart PMO, process optimization and re-engineering to testing capabilities, risks, controls and reporting frameworks.

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Matilde Pearce - Assistant Manager, Financial Services Transformation

Matilde is an Assistant Manager in the Financial Services Transformation team of Deloitte’s practice in Zurich. She focuses on transformations, from digitalization to risk frameworks with experience at several financial service providers in Switzerland and internationally. She focuses primarily on lending process optimization and digitalization with specific expertise on change management, smart PMO, regulatory compliance, reporting frameworks (incl. KPI) and monitoring

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