The advent of the latest recession and slow recovery has led many companies to realize the benefits, nay, the necessity, of integrating demand and supply planning across the enterprise. The benefits of increased response to demand fluctuations, reduced inventory without adverse effects on service levels, and the resulting increased profit margins, are too good to pass up. This has driven the growth in ERP and other planning systems in the last decade, with the goal of a fully integrated system from top to bottom, allowing maximum responsiveness with minimum slack.
Many companies have come to realize, however, that most enterprise systems are either not actually integrated, have weak links, or lack some required functionality. This has led to numerous systems being implemented across the enterprise, with varying levels of integration between each one, ranging from none to very tight integration. The implementation of these various systems has been driven by the needs of the various business units, which often have very different requirements and priorities. This in turn has led to a disconnect in common data terminology and usage across the enterprise, as each area of the business focuses on the data required to meet their immediate needs in their own terms.
When the time comes that an enterprise solution is to be implemented across several different business units or functional areas, it is then discovered that the definition of the same piece of data differs from unit to unit or area to area. This leads to the necessity of building exception handling rules and look-up tables in order have the data flow through the enterprise with consistent meaning. This can greatly add to the project’s cost and time to implement, and is usually an unexpected complication of the project. It also significantly increases the amount of effort required to support the solution. The question becomes, what is the best way to deal with this situation in order to reduce cost and timeline impacts? Following are some suggestions that might help mitigate these issues:
- Perform an audit as part of the preliminary planning phase. While this will not do much to fix existing data issues, it will highlight gaps in the ‘data chain’ across the enterprise that will need to be bridged. Key data fields should be identified and their exact meaning to each functional group in the organization should be spelled out. This will quickly identify areas where cross reference tables or extra business logic is required.
- Centralize the administration of business rules and data schema, especially as they apply to enterprise-wide initiatives. While ERP systems generally ‘hang together’ because of their module interdependence, the business apps that reside above this transactional layer tend to be more isolated. When an enterprise-wide application is implemented to replace and integrate these business functions, the gaps become readily apparent. The most successful method I have seen used is to drive all data definitions from the transactional ERP layer, or the layer where the best cross functional integration occurs, and build a common base on top of this.
- Plan and implement every business process as an enterprise-wide initiative. This will ensure that data and business rules are defined at the enterprise level, not at individual, possibly differing functional units. However, in order to do this, it is much easier if you are using a tool that supports enterprise level business processes. This includes the ability to tie disparate data sources together, large multi-user scalability, and is flexible enough to be configured to meet the varying requirements of all the functional units involved.
While I have not covered all the different techniques that can be applied to help mitigate this very prevalent issue, I hope I have given people an idea of where to start in tackling this significant implementation problem. If anyone has other ideas or techniques they have seen or used, I am sure everyone in the community would be very interested in hearing them.