Supply chain technology is seeing seismic shifts and changing rapidly as new, innovative solution providers leave traditional legacy players behind.
Tremors. Seismic shifts. In supply chain management technology there is a fault line separating new, innovative technology providers and traditional supply chain software providers, and the gap between them is growing.
In fact, the market for supply chain management technology is dramatically changing. On one side, I am seeing market consolidation among traditional application providers, which does not bode well for innovation (a topic I discuss later in this article). On the other, I am seeing startups explore how innovations such as artificial intelligence and blockchain can be applied to the supply chain.
Where are the most important seismic shifts and changes happening?
Here are five fundamental shifts in supply chain technology that companies need to be aware of:
Redefinition of decision-support software
Decision support includes all forms of planning: demand, supply, revenue, manufacturing, and transportation. There is currently a lot of noise in this market.
In the past few months, I have spoken to several emerging cognitive computing companies that are attempting to redefine decision-support technologies. Cognitive computing involves using self-learning systems to mine data, recognize patterns, and process language in order to mimic the way the human brain works. The inclusion of cognitive computing in decision support will make the traditional applications in the advanced planning solution markets obsolete.
Disintermediation of business process outsourcing (BPO)
In the past, companies have focused on labor outsourcing and third-party solutions to reduce headcount. The result? While they have shifted costs down the value chain, they have also lost control of process integrity.
To regain control, companies should eliminate BPO providers through the use of machine learning and automation. In addition, blockchain and cryptocurrencies can and should disintermediate business process outsourcing.
Emergence of digital manufacturing technologies
Technologies such as robotics, wearables, the Internet of Things, and additive (3-D) manufacturing are redefining manufacturing. These new technologies will change how manufacturers define spare-parts requirements, schedule maintenance, and conduct production planning.
They have the possibility to become even more revolutionary when combined with other new technologies such as cognitive computing, blockchain, and analytics.
Adoption of autonomous vehicle technologies
Logistics is already being transformed by autonomous vehicle technology. For example, some companies are exploring how drones using machine learning can perform real-time inventory counts in warehouses, and others are considering how self-driving vehicles can be used for deliveries.
Redesign of B2B transactions
For the last two decades, we have been trying to squeeze pennies from business-to-business (B2B) transactions through hands-free processing and automation. We now have the opportunity to use blockchain to redefine and redesign these practices.
For example, blockchain could be used to better track quality control and chain of custody in the cold chain, improve lineage/track-and-trace to ensure brand integrity, and redefine multiparty finance. Leaders can now start to think about how to drive true value with suppliers instead of focusing on payment concerns such as how to extend payables, increase fines and/or penalties, or use third-party outsourcing to handle payments.
The Need to Change Thinking!
These changes can only happen, however, if we can learn from the past, rethink the future, and “unlearn” old ways of thinking about the supply chain. Many companies, however, are hamstrung by “legacy thinking” that focuses on functional optimization rather than on driving improvements across the entire supply chain network. The challenge lies in “unlearning” outdated approaches.
It won’t be easy for companies to change their thinking when it comes to supply chain technology, but here are some early lessons and observations I believe will be helpful.
A separate innovation team will produce the best results
Having the digital innovation team embedded in the information technology (IT) organization is like drilling a hole in bedrock. It just does not work. Most IT departments are loyal to their enterprise resource planning (ERP) providers and legacy consulting relationships.
Their fear of change slows down the adoption of innovative technologies and business processes. To create new business models using new technology, you need testing and learning to be done by small, scrappy teams.
It is not sustainable for system integrators/consultants to build software
When it comes to cutting-edge technologies, many consultants are playing catch-up. In some cases, the innovations occurring on the technology front pose challenges to their traditional business models, so consultants may not fully embrace them.
Innovation will never come from consolidating applications
History has shown that software aggregation reduces the software’s market value. Across the decades in the supply chain market, the acquisition of software products by technology vendors only provides value for the venture capitalists or the owners of the companies. There are few acquisitions that add value to the end-user or lead to innovation.
Supply chain leaders who believe they have all the answers need to be fired
We don’t have the answers, and we don’t have best practices for now and the future. What we have are historical practices and stalled progress on metrics. Supply Chain Insights has found that 90 percent of companies are not making progress on key supply chain metrics, such as cost, inventory, growth, and return on invested capital (ROIC).
We are seeing innovation, but it’s happening at the edge. The question is how to move it to the core of the business. We need to challenge the fundamentals of the past and redefine the processes of the future. Doing this requires executive leadership. It cannot happen at the functional level.