In today’s ever-evolving business environment, organisations frequently find themselves needing to implement new ERP systems in certain areas of their operations while maintaining older systems in others. This scenario becomes particularly complex during mergers and acquisitions, resulting in a tangled IT landscape. Unfortunately, such changes often breed confusion and discord between business and IT departments, diverting attention away from shared objectives and towards disputes over misunderstandings.
Fortunately, managing even the most intricate IT landscapes is possible. One effective strategy for reducing complexity involves gaining a comprehensive understanding of current processes and user behaviors, pinpointing areas of inefficiency, and streamlining operations through process mining. By delving into the existing workflows and habits of users, organisations can identify bottlenecks and inefficiencies, paving the way for targeted optimisation efforts. Through process mining, businesses can align their IT systems more closely with their operational needs, fostering greater harmony and efficiency across the organisation.
Are you wondering about:
- Ensuring a smooth and risk-free ERP migration?
- Meeting business needs with available resources and aligning teams?
- Completing complex ERP projects with timely end-to-end testing?
These are common concerns during ERP system development. In this blog post, I’ll show you how process mining can address these challenges from an IT and ERP development perspective.
IT & ERP development challenges
In large organisations, having too many systems in use poses a significant challenge in IT and ERP development, according to Gartner. Drawing from our experience of completing over 400 process mining projects worldwide, we’ve identified several reasons contributing to this issue.
The evolving business landscape often necessitates deploying new ERP or workflow systems in some areas while retaining old ones in others, particularly evident in merger and acquisition scenarios, which inevitably lead to a complex IT environment.
Moreover, even within a single system, diverse usage patterns pose challenges. For instance, in processes like purchase-to-pay or order-to-cash, companies may have standardised blueprints, but variations arise due to different regions, vendors, end customers, and products. These variations increase support demands on IT.
Digital transformation trends further compound the burden on IT and ERP systems as businesses rush to adopt new technology to enhance customer experiences, adding complexity to development projects.
Initiating IT or ERP deployment often involves grappling with understanding business requirements, which can be time-consuming. Traditional methods like dialogues with employees only offer a partial view, as each individual explains their process variations, issues, and best practices.
Unfortunately, it’s not uncommon for IT and ERP development teams to encounter challenges such as high maintenance costs, chaotic migrations, and dissatisfied users, leading to decreased productivity on the business side.
Today, I’ll explore IT and ERP development from the ERP life cycle perspective, highlighting challenges across the Design, Implementation, Deployment, and Maintenance phases. At each stage, I’ll demonstrate how Process Mining can effectively address these challenges.
1. Design
Designing an IT and ERP system that effectively aligns with business needs while managing resource constraints poses a significant challenge. However, process mining offers a valuable solution by providing insights into the current utilization of IT and ERP solutions. It offers both a holistic overview of processes and detailed analyses of top variations and bottlenecks.
The diverse usage patterns within IT and ERP systems often lead to ongoing challenges. Process mining addresses this complexity by showcasing all process variants and highlighting the most common ones, facilitating a thorough analysis of current workflows.
Through this analysis, organisations can identify best practice variants and construct process models to guide their operations effectively. Utilising data from existing systems, tools like QPR ProcessAnalyzer offer fact-based insights crucial for making informed decisions, whether for optimising current ERP systems or planning migrations from old to new ones.
This functionality proves particularly useful during efforts to enhance existing ERP systems or when undertaking migrations, providing essential insights for driving improvements and ensuring smooth transitions. Additionally, leveraging process mining can streamline decision-making processes, enabling organisations to justify and enact significant changes required for well-functioning systems.
2. Implementation
When embarking on an IT and ERP development project, ensuring timely completion with sufficient end-to-end testing is a critical concern. However, determining if the project is heading in the right direction during the implementation stage can be challenging.
Traditionally, end-to-end testing consumes significant time in development projects. Process mining offers a solution to this issue by providing insights from development data, enabling quick assessment of testing progress, time spent on different steps, and identification of problems encountered in testing environments.
A prime example of this is showcased in the success story of L&T, a major electric services company in Finland, where QPR ProcessAnalyzer facilitated a successful and risk-free ERP migration by analysing data from the early stages of the project.
Furthermore, process mining allows for the creation of best practice examples for intended use cases. This functionality proves invaluable when communicating with stakeholders and colleagues from different parts of the organisation, as it provides clear instructions on how to utilise the system effectively. Additionally, it enables comparison between testing environments and alternative workflows.
During the implementation phase, process mining supports continuous monitoring of user adoption and benefits derived from the system, ensuring its successful integration into daily operations.
It’s worth noting that tools like QPR ProcessAnalyzer can also prove beneficial for projects involving Robotic Process Automation (RPA) and Intelligent Automation (IA), extending their utility beyond ERP development.
3. Deployment
During the deployment stage of an IT and ERP development project, process mining plays a crucial role in ensuring that system users quickly adapt to new processes, while also providing an opportunity to address any unforeseen issues promptly.
Based on numerous process mining projects with our customers, it’s been observed that ERP deployments can be expedited by up to 50% with process mining, as it enables real-time tracking of user utilisation of the new system.
Following the system’s launch, users gradually acclimate to the new functionalities, sometimes resorting to manual workarounds. This could stem from unawareness of intended workflows, skepticism about benefits, or simply a desire to stick to familiar practices. Addressing these behaviors and expediting this adjustment phase is essential.
Process mining aids in detecting users’ old habits and manual workarounds, facilitating immediate assistance in transitioning to the new system. Additionally, the software easily identifies the root causes behind these workarounds, enabling organisations to either educate users on preferred practices or rectify complexities within the system hindering adherence to intended workflows.
In essence, process mining provides a means to effectively identify and understand deployment stage problems and their underlying causes, empowering organisations to swiftly address issues using tools like QPR ProcessAnalyzer.
4. Maintenance
Maintaining a newly developed system involves understanding its performance, addressing potential issues, and continuously monitoring and improving it. This includes actions such as identifying and rectifying problems, streamlining processes, and optimising resource allocation.
A key metric for evaluating the effectiveness of an ERP system is the number of manual processing steps required to complete an end-to-end process. This statistic provides insight into how well the ERP system aligns with business needs. By analysing data and conducting root cause analysis using tools like QPR ProcessAnalyzer, organisations can continuously identify and address errors, manual workarounds, deviations, and unnecessary rework.
Process mining offers a holistic view of the ERP system, enabling the detection of functionalities that are no longer in use. This insight serves as the basis for deciding to drop support for unused modules, thereby reducing ERP maintenance costs and streamlining system operations. By leveraging process mining insights, organisations can effectively optimise their ERP systems, ensuring they remain aligned with evolving business requirements.