As manufacturers continue to push through the Coronavirus disease (COVID-19) pandemic and learn to refine their business operations, enterprises need to focus on building resilient, digital value chains in order to maintain operational efficiency. This resiliency is not only needed to handle challenges resulting from factors outside an enterprise’s control – such as a global pandemic – but also to address the challenge of concurrent events that have the potential to detrimentally impact operations. The movement from physical to “phygital” (physical and digital) customer engagements is one such shift. Manufacturing enterprises will need to invest heavily in strengthening ecosystem partnerships – for example, an R&D or product innovation ecosystem, a customer engagement ecosystem or a global distributed manufacturing ecosystem. By streamlining these ecosystem partnerships, all parties will be able to become more agile and resilient, at scale.
So how exactly can these manufacturers achieve these seemingly daunting strategic investments overnight? The answer lies in adopting a “neural” approach to their entire value chain. By building a digital infrastructure through cloud, artificial intelligence (AI), machine learning (ML) and other interactive customer engagement investments, manufacturers will be able to become fully realized neural manufacturing organizations.
Beyond bringing more agility and efficiency, a neural approach brings many advantages for manufacturers. In the short term, neural manufacturing enables resilient, machine first supply chains, which are imperative in an economy that remains uncertain and volatile. In turn, this allows organizations to be adaptable to any internal and external factors while working toward their shared end goals.
What exactly is neural manufacturing?
Neural manufacturing is a concept where digital technologies enable manufacturers and their ecosystem partners full data visibility at each value chain touchpoint – on the shop floor, warehouse inventory, logistics, customer engagement, aftermarket, etc. Think of the value chain as a neural network. Each touchpoint serves as a “node” that is constantly receiving, interpreting and sharing data with all other connected touchpoints in real time. More importantly, the ecosystem continuously learns and becomes cognitive.
If there’s a machine on the shop floor that is scheduled for routine maintenance, forecasting customer relationship management (CRM) will know immediately and take it into account for upcoming forecasts and demand planning. Logistics providers that manufacturers use will know if there will be delays as a result. Sales and service professionals will be able to notify existing and new customers of any delays, and the manufacturer would actually be able to negate any inefficiencies from the out-of-service machine by proactively planning for maintenance. On a deeper level, neural manufacturers must adopt a few key technologies. Process automation helps ensure that any mundane, manual tasks are mitigated so that employee time can be spent on more complex, cognitive tasks. Real-time asset monitoring and diagnostics help distributed workforce manage and maintain machinery and product on the shop floor and at the edge. Cloud-based collaboration helps ensure that distributed teams can share any information and increase productivity, from anywhere around the world. These are just a few of the key capabilities that help drive neural manufacturing resiliency.
Where to learn more
Investments in digital transformation not only make sense from an objective standpoint, but also have a clear ROI. Additionally, in a digitalized world, these investments highlight a crucial need for people. Technology is simply evolving traditional roles – augmenting people to learn more cognitive, complex skills that help provide end customers with innovative, quality experiences.
Manufacturers need to reimagine the ways in which they work both internally and externally in order to stay competitive in today’s market. Internally, digital technologies can help connect distributed workforces and streamline inefficiencies through AI and ML adoption. Externally, manufacturers need to build strong ecosystem partnerships, investing in ways to share and collaborate with partners digitally and in real-time. By establishing these real-time connections, a manufacturer can truly become the neural network it needs to be in order to scale alongside volatile shifts in demand – whether they are due to the pandemic, or any other inevitable market shift that we will face in the future. The confluence of multiple industry value chains through the neural enterprise operating model helps deliver frictionless experiences to the end customer for their integrated needs. This renewed focus on customer centricity creates new business model opportunities to drive exponential growth.