Enterprise resource planning (ERP) brought a solid – sometimes rigid – structure to corporate information systems in the 1990s. The resource planning part of ERP was typically modelled on a ‘push’ and non-optimised approach to organise the creation of goods or services.
The result was a reliance on overcapacity investments to cope with peaks in demand, and reliance on push marketing to shift surplus goods whenever production exceeded demand.
This backward approach, of planning to cope with bad planning, has become inappropriate in the current dynamic, customised, and rapidly changing industrial market. It is widely understood that suppliers need to be in tune with real market requirements. The demand is now driving the market, not the supplier, and push marketing is becoming less and less the answer. On top of that, the current economic climate is imposing cost reductions and investment restrictions, making resource optimisation imperative.
A complementary alternative to ERP is advanced planning and scheduling (APS), which when properly implemented, can help organisations rapidly and efficiently respond to market conditions and changes.
Given the focus on customisation and responsiveness, a good APS system is not necessarily an off the shelf system and the approach is very different from a traditional ERP approach. An organisation must check that any proposed APS model matches its own business model, bottlenecks and planning processes – at both a strategic and a tactical level. There are no compromises in APS: if the package or bespoke system is based on the wrong business model, an organisation will never get the return on investment expected. Therefore, an APS proof of concept exercise is often the key way to safe delivery.
APS systems can optimise a small but vital process, such as paintshop scheduling in a car factory, or a macro process, such as the whole supply chain sequence in a car factory. The one constant is that an APS system requires high quality operational data. It is unlikely that a good APS system can be built using only the data provided by existing information from ERP systems, and it is equally unlikely that APS data sources will be identical to ERP data sources.
At the core of the APS application is a mathematical process, designed to optimise production given the specific business constraints of an organisation. Optimisation should not require a supercomputer. With the right software, coupled with clearly defined parameters, a business can expect to solve 95% of scheduling problems on a standard laptop.
For most businesses, an APS proof of concept exercise can be completed in less than two months. A nine-month project is typical for full roll-out, while return on investment can often be reached within a year. Rapid results are possible because APS systems target what has not been targeted by the ERP era – maximising a company’s most valuable asset, its ability to supply an ever-changing demand.