Implementing an ERP project: the keys to success
The problems encountered when implementing ERP projects and data repositories vary from company to company. As a result, there is no simplified guide to ensure your project’s success. But ERP projects and data repositories are strategic and necessary to companies’ data-driven evolution.
Fortunately, your ERP and data repository projects can be successful, and we are going to present the various elements you should consider before getting started. And if your project is already underway and encountering difficulties, all is not lost, but the following practices should be implemented as soon as possible.
Data scoping: a fundamental element that is all too often overlooked
Although data is now at the heart of many conversations, it is all too often overlooked when scoping major transformation programs.
Understanding the data asset management steps that need to be taken before embarking on an ERP transformation is a key factor in the success of such a project.
The aim of data scoping is to provide a comprehensive overview of your operating mode, including roles, processes, systems, and data processing rules, in both automatic and manual mode. The aim is to provide a complete and up-to-date picture of the functioning of the targeted reference data scope (product, suppliers, prices, etc.) that is as realistic and factual as possible.
Our scoping methods use the principle of Data Process Management to explain and define existing business processes from a data perspective.
Our scoping methodology will help you to:
- understand the processes that will be involved in and affected by the project
- consider the data used in these processes
- cross-reference these elements with the company’s data maturity to identify the organization’s problems.
By providing an exhaustive vision of current operations, from the creation of a product or service to its delivery to the consumer, data scoping will help to better define the areas of improvement to be covered in the targeted operations. Once these elements have been identified, it will be easier to identify the sticking points that lead to scheduling, quality, and functionality problems.
This data scoping also aims to define and describe the data practices to be implemented:
- mode of governance of data domains within the company (federated, centralized, etc.),
- organization of the DATA team,
- data migration and quality factories, etc.
The data scoping team: a cross-functional team that must remain available throughout the whole project
However, once the initial elements have been identified, this data scoping unit should not be disbanded. The project, with its slippages and changes in functional scope, will require new cross-functional analyses and continuous improvements to the program roadmap.
The program therefore needs to maintain a scoping capacity to avoid any deadlock and to be able to validate changes of direction by taking all data aspects into account.
Do not just focus on the target: secure every stage of the ERP project
Because of their complexity and length, ERP/repository programs are generally broken down into several stages or milestones, encompassing the various components of the project. Security involves ensuring the nominal operation of the company at each stage of the program and must be based on updating the functional and data mappings.
This mapping is an indispensable solution for organizing the actions of each team and for providing a precise vision of the functioning of intermediate milestones and of the gaps/inconsistencies that need to be resolved in each process.
Linking up the various teams through data also brings greater cohesion and better communication on functional coverage and shortcomings, which creates transparency and user buy-in.
This practice makes it possible to specify the data roles & responsibilities at each stage, and to define the actions required to maintain consistency, which are indispensable at intermediate milestones.
In addition to this organizational coherence, data mapping can help to define the means of controlling data between each stage. In intermediate versions, data discrepancies between two systems are quite frequent, as not all the necessary flows and processes have been established. It is a “degraded” mode, but it can, nonetheless be of use to the company. It is essential to identify any data discrepancies that may have been created and that need to be corrected before switching to the target version, to ensure that no data is lost. This can be extremely annoying for users who must change systems but are unable to retrieve the most recent data.
Successfully achieving this last point requires the support of data analysis teams.
Set up a project analysis and reporting unit
Some ERP and data repository programs may appear to be navigating blindly due to a lack of reliable indicators. The implementation of KPIs is too often relegated to the end of the to-do-list, making it difficult to analyze problems and define areas for improvement.
This type of program must therefore be equipped with a data analysis unit capable of dealing with various issues:
- Quality audit
- Validation of functional rules via a data audit
- Checking consistency between systems during changeover plans
An important task for this data analysis unit is to ensure data consistency between the different systems, by checking that records (customer, item, etc.) exist between systems, but also by verifying the consistency of critical attributes, to ensure that the new system remains the sole source of truth for the company’s data.
This unit will then be able to provide all the analytical elements needed to answer questions and provide factual information to the various business line managers, giving them a reliable overview of the data so that they no longer need to work or interact based solely on their perceptions of the data.
In these few lines, we have drawn on our experience to highlight some essential practices that you can implement on your projects. ERP/repository projects will always be complex, due to their cross-functional nature, but their success rate will improve if you follow this advice.