If you think technological terms like artificial intelligence (AI) and big data are not impacting your supply chain and logistics, think again. When these and other advanced technologies converge, they help create a digitized supply chain that is more efficient, customer-centric, and cost-effective than its predecessors. Digitization also poses new challenges for organizations, which have suddenly been forced to adapt to a changing global trading environment and changing customer expectations. "Moreover, with growth being the CEO's top priority, leading chief supply chain officers (CSCOs) are under pressure to leverage digital technologies," according to Gartner Rob van der Meulen in A 5-Step Innovation Process for Supply Chain. To start turning the company’s goals into real value that helps optimize your company's supply chain and better serve your customers, consider these steps in the right direction: Leave No Stones Unturned When it Comes to Digitization Operating an end-to-end digital supply chain remains rare in many sectors. It requires a multi-pronged approach that starts with robust data, is driven by strong governance, and includes traceability and data control so that companies can trace the lineage of data and understand where it came from. These insights enable companies to not only reduce costs, identify risks, but also have a positive impact on their highest priority: their customers. A data-driven digital supply chain also lays the foundation for advanced analytics, withstanding the ripple effects of changes in any link (upstream or downstream) and then adapting to avoid a severe shock when disaster strikes. The demand for this type of digital transformation is becoming increasingly evident in the wake of the Covid-19 pandemic. While many aspects of the supply chain are digitized, final decisions are often made by a team member working with spreadsheets. Eliminating this manual process is the final step in the digitization of the supply chain; arguably one of the most difficult things to do and, unfortunately, many companies have not yet been able to achieve it. Use AI and AA in Supply Chains AI can provide extremely valuable insight, identify anomalies, provide better forecasting, clarify patterns and improve performance. AI can be used to increase data quality and business outcomes, whether you are looking at planning and delivery, procurement, manufacturing, or warehouse management. AI models predict the estimated time of arrival of shipments. Order date and probability detectors forecast the statistical probability that a deal will be effective, along with an estimate of the week in which an event might occur. This intelligence can help forecast supply and demand If the idea of robots circulating around your warehouse, working side-by-side with humans, still sounds like the product of a good science fiction novel, it's time to put some of these autonomous bots to work in your supply chain. The good news is that these automated solutions are now available with lower capital investment and can be scaled up as needed, which reduces the initial investment and improves overall RO (rollover). Embrace the Concept of Industry 4.0 Industry 4.0 refers to the inclusion of technology in the physical processes of a company. For example, this includes the use of big data to predict workloads and thus improve worker productivity. By adopting a more strategic approach, your company will be enabled to leverage digital technologies to improve its competitiveness through the Industrial Internet of Things (IoT). According to PwC, today's supply chain consists of a series of largely discrete steps, marketing, product development, manufacturing, and distribution, and ultimately in the hands of the customer. Digitalization breaks down those walls and the chain becomes a fully integrated ecosystem that is completely transparent to all the players involved, from the suppliers of raw materials, components, and parts, to the transporters of those supplies and finished products, and finally to the customers who demand satisfaction How to Implement These Initiatives In addition, the approach to these digital transformation projects has also evolved. Many processes that were carried out at an early stage had a huge financial cost and a high risk of failure, and this has changed. The cost of technology has come down considerably and it also now allows focus on specific aspects, offering the possibility of achieving faster results and minimizing the risk of failure. When faced with a digital transformation project, the first necessary step is to define a target model. A highly recommended way to do this is by applying a methodology based on "design thinking", which emphasizes a series of concepts to avoid failure:
Explicitly articulate the problem to be solved. Generate a deep knowledge of the problem to be solved. Hold workshops to develop the solution. Work with prototypes. Create a first minimal version for rapid testing and subsequent improvement.
Today's consumers are increasingly skeptical about distribution channels, do not recognize the difference between them, and expect an optimal shopping experience in each and every one. In reality, for the consumer, it is a single channel that combines both physical shops and online shopping portals, going to one or the other according to their convenience at the time of purchase. Consumers also demand to know where the product they have bought online is at any given moment, to receive it quickly and conveniently, and to be able to return it easily and without having to pay for it. It is not only the consumer who is indifferent to the channel but also the boundaries are blurring for manufacturers, who are now connecting directly with shoppers rather than using their traditional retail channels.