Why the Traditional Approach to Buying Supply Chain Planning Systems is Flawed
Most supply chain organizations recognize that their ERP solution does not deliver the functionality that they need to effectively model and plan their supply chain. So selecting a good planning software solution is critical and can drive significant value to the business.
Since there are many options and approaches, the decision making process can be very challenging. Stories abound of poor selections. Lora Cecere, founder of Supply Chain Insights, noted in a recent webinar that a common outcome of these failed implementations is that supply chain organizations end up in “Excel ghettos where lots of people are touching data but not improving it.”
The old way of buying supply chain planning (SCP) solutions was similar to purchasing an ERP solution – long lists of requirements and long vendor responses, followed by feature/function demos. But what may have worked for ERP and other transactional systems, didn’t work very well for SCP. The problem was that the parts didn’t necessarily add up to the whole. Evaluators spent weeks comparing spreadsheets of the vendor response and looking at screenshot demos, but often didn’t end up with an understanding of how the functionality would improve their business. What this approach did not do is validate the ability of the vendor’s solution to model the buyer’s supply chain and deliver value.
This traditional RFP-driven approach to selecting supply chain planning systems was deeply flawed. Since the key with SCP is to model the supply chain accurately, if you didn’t do that right you didn’t get good results, no matter how many features and functions you checked off. So buyers got burned.
Supply chain planning software selection demands a data-driven approach. It is not a transaction system. It is essentially a “predictive analytics” process; that depends on the quality of the model in order to correctly predict service level.
Since the key is to model accurately demand and inventory, the evaluation should focus heavily on the heart of the issue – the quality and precision of the model. Testing the model in a conference room pilot, a “proof of concept”, or even a full-on pilot installation reduces the risk of serious under performance. Buyers can trust the system and have a reasonable degree of certainty that it will actually improve their supply chain and business performance.
So organizations are now building model validation into their evaluation process. A Proof-of-Concept (POC) involves providing actual supply chain data to the vendor and asking them to validate the ability to build a working model of their supply chain solution. Depending on the scope of your supply chain, the data selected could be for a geography, a product line or some representative portion of your business.
Dan Gilmore of Supply Chain Digest cited a recent example of a Proof-of-Concept that “gave everyone confidence in the proposed system before signing on the dotted line. That investment also largely paid itself back in terms of a faster and less expensive full deployment – which was achieved in just 6 months or so.” He concludes that incorporating a POC approach “should be used in almost every area of supply chain adoption.”
A Proof of Concept has a much richer set of outputs than the traditional RFP evaluation process that includes:
- Proven Supply Chain Model – Working model of your supply chain that allows analysis of business scenarios
- Articulated Business Case – With a model that represents your supply chain you can understand the potential performance improvements in terms of reducing inventory and increasing service levels
- Increased User Buy-in – Because your users are looking at their data and able to validate their business scenarios, there is a much higher degree of user buy-in than is achieved from looking at vendor-driven demos
- Evaluation of Data Readiness– Building a working model allows you to understand data readiness, gaps if any, and begin the preparation for implementation
- Validated Deployment Approach – The learnings from the proof of concept allow you to be much more confident about your ability to implement, and provide higher certainty of the expected results
- Tested Sustainability – Good POCs test the sustainability of the model and its ability to automatically and continuously adjust a variety of conditions and changes without constant manual intervention
Consultants can be helpful with this process, but be careful, they don’t necessarily reflect this way of thinking. They may be stuck in what they were familiar with in past big transaction systems.
Lora Cecere says, “I encourage people to do pilots to test the effectiveness of current advanced planning systems for the tail – To be able to look at safety stocks, to be able to look at demand sensing and forecasting, be able to look at how to design that and compare it to current systems.”
Click below for a Nucleus Research report on the seven steps a supply chain executive should take in selecting an inventory optimization tool: