The demands of the modern supply chain are massive in the digital age and only with projections of a steady increase. With product development being more accessible with shorter lifecycles, geographical flexibility and faster delivery are the base requirements for any successful supply chain. The disruption of online retail and the data insights gained made the digitization of supply chains the next logical step. In fact, reports (McKinsey, 2017) show that companies can potentially improve annual growth with supply chain digitization by as much as 3.2%.
However, most companies either do not attempt or have not sufficiently optimized their supply chain networks. While some reasons could be the complexity of the network, legacy methods, or a lack of a comprehensive view of the entire chain, a recurring issue is the inability to process data insights and apply them for maximum effect. For companies that are more informed about technological leverage, there is usually a case of losing momentum after an attempt to optimize begins. The gap is due to no changes made at an operational level that would allow them to make full use of the effects of their digital solution.
At its foundation, an optimized network is in service to the business objectives. The research phase involves narrowing down target areas and markets, the growth areas desired, and the ideal parameters of efficiency. This may relate to broad transport logistics, market competition or even customer service. The model starts to be defined by the knowledge gained, and one can make the appropriate changes to the supply chain. More importantly, building a model based on data avoids any subjectivity and bias.
Signs that you may require to undergo the exercise of network optimization can be affected income margins, mergers, acquisitions, high inventory costs or a change in your listed products. One should also factor in the time taken to build an accurate model of the supply chain. While the time and effort investment may determine the frequency of the check, ideally, one should optimize as often as possible.
If you are still trying methods of manual record (via spreadsheets, for example), data recording becomes a tedious process that may contain a high error rate and a significant sink in resources. Software solutions allow the user to repeat and refine any simulations easily as the model does not have to be reconstructed several times over. Additionally, prescriptive analytics easily factor in the intricate dependencies and leverage available in the supply chain network.
We recommend that you consider a comprehensive software solution versus an “add-on” to your MRP/ERP software suite. Add-ons only provide a basic solution without considering ground-level data, usually due to a lack of advanced modelling capabilities.
Axidio provides advisory services to help customers optimize their existing networks to gain the most out of their investment in eCommerce platforms, especially within the constraints forced onto the market by the global pandemic. We specialize in supply chain network modelling, robotic process automation, data strategy, and digital transformation. Whether your business needs to become more efficient, agile, innovative, or customer-centric, we provide solutions to enable sustainable change.