Top 10 Takeaways from the Gartner Supply Chain Planning Conference 2019

My 10 Takeaways from the Gartner Supply Chain Planning Summit 2019

A lot of people have asked me about my thoughts on the recent Gartner Supply Chain Planning Summit, so I thought I’d share my thoughts in this article.

First, I must say it was encouraging to see all the company and vendor participation at the event. It was first rate and held at the new Gaylord Rockies convention center near the Denver Airport. We’ve come a long way from when I worked with Eli Goldratt positioning finite forward scheduling. APICS considered us heretics at the time. We had to stand outside their events passing out our white papers because we couldn’t get on the venue! It has now been about 20 years since I was granted my patent on “Extended Enterprise Planning Across a Supply Chain” and it’s great to see how well the market has evolved.

The goal is to move beyond a digital supply chain and into a digital ecosystem that enables industry-based marketplace trading throughout the network. - Joe Bellini @onenetwork Click To Tweet

#1 Technology has now become a true disruptor: Evolving from chains to networks.

If I could pick a theme overall for this year, it seemed to be that technology has now become a true disruptor to our historical processes used for supply chain decision making. Reflecting this thought, I noticed that in many of the presentations the wording has evolved from supply “chain” to supply “network”. The technology to enable a network-based approach to problem solving, planning and execution around demand, supply, logistics, and fulfillment in a multi-party transaction is finally being recognized as having moved past the early adopter phase.

Recommended: Supply Chain Networks Revealed (ChainLink Research)

In a presentation on strategy, the analyst pointed out that the journey to stage 5 required a company to move to becoming a member of an operating network within their industry. This makes a lot of sense and was backed up in a different session by another analyst who defined the vision of the digital roadmap is to get to a point where you had moved beyond a digital supply chain or value chain and into a digital ecosystem which would enable industry-based marketplace trading throughout the network.

2# Companies aren’t moving fast enough to leverage available capabilities and technologies.

Naturally there were lots of survey results presented which in summary basically said that while the technology is now available, companies aren’t moving fast enough to leverage the capability and create competitive advantage. Most are stuck halfway up the maturity curve. They went on to discuss case study examples of companies who had moved forward and generated significant returns. One in particular noted that they had automated 997 out of 1000 planning decisions.

A big reason discussed for the slow market start was the struggle companies were having in being able to translate their business strategy into a digital strategy. This is not surprising, given we are now at a point where technology and business are forever intertwined in terms of serving and shaping market demand, but the functions within and across trading partners remain largely segmented.

#3 Planning and execution are converging in continuous, real-time decision-making.

Another key point that was made was that the boundary between planning and execution had become very fuzzy as part of looking at problems holistically through the network control tower. In the old days, planning was measured in months, execution was weeks, and the two shall never meet.

Now we have a continuous and real time data network where decisions can be made related to customer service even hours prior to consumption rather than having to live with all the expensive inventory, capacity, and expediting costs used to buffer for the supply/demand mismatch. The analysts called this “bridging between S&OP and S&OE”, but really what I think they were saying is that digital technology now allows us to solve all problems across the network and the choices will vary based on how far out we are from consumption when solving the problems, and the types of analytics applied. In fact, with network technology we can track all time-phased decisions through milestones, and not have to worry about whether it is planning or execution.

The end of planning vs. execution? With network technology we can track all time-phased decisions through milestones, and not have to worry about whether it is planning or execution. - Joe Bellini @onenetwork Click To Tweet

#4 Digitization strategies will lead to restructured organizations.

Of course, with all this change related to process and technology, the people side of the equation was also a big topic for discussion. There were a number of presentations on organization strategies related to digitization strategies. The way I think about this is that I fully expect that the org chart at Uber is different from the org chart of an old cab company. With digitization of the supply network becoming a priority for all companies, how does the old cab company restructure their org before another Uber comes along and eats their lunch?

#5 AI is finally coming into its own.

And as part of this digital shift, companies are looking for technology to make things simple at the process level. Not just the automation mentioned earlier, but applying artificial intelligence (AI) and machine learning (ML) based insights for better decision-making, along with a workbench/dashboard environment that provides an easy and cognitive workflow.

CEO Digital Goals - Gartner Supply Chain Planning Summit 2019

 

#6 Companies are unlocking value with multi-echelon inventory optimization (MEIO).

Given that inventory is still a big cost driver, the analysts spent quite a bit of time digging into various ways to segment inventory and risks/opportunities to leverage technology to reduce those inventories. Much was discussed around MEIO which was a good in-depth analysis around the potential for improvement across the network. Taking this a step further, in a network platform which is multi-party, you can run transactions where you consider not just the inventory buffers, but the orders, capacities and logistics all at the same time, optimizing simultaneously.

Multi-party network platforms enable you to consider, not just the inventory buffers, but the orders, capacities and logistics, all at the same time, optimizing simultaneously. - Joe Bellini @onenetwork Click To Tweet

#7 Enterprise-centric ERP struggles to support network-scale business.

Of course, the bully pulpit of a conference is a chance to throw a few darts, and in one case study a company described the nightmare they had in trying to extend their enterprise ERP system to work in the network. After much pain and expense due to customization they abandoned this approach and moved to a dual platform strategy using a network technology platform for their business operating system and keeping the ERP as the backend.

#8 Digital representations of supply networks are great enablers.

The term digital twin was introduced in a few of the presentations. From my perspective a good digital representation of a supply network is a great enabler, from being able to provide full visibility and control, to providing alerts, to prescribing actions, to simulating demand, supply, capacity, and fulfillment, to modeling an end-to-end network environment, to providing a trading community master data management system (MDM). As part of this, it was pointed out that it is really the ability to provide a dashboard/workflow for the human to interact with the analytics so that the right decisions can be made at the right time for complex situations and the more repetitive decisions can be done automatically.

Recommended: How to Drive Supply Chain Performance with Community Master Data Management

#9 Predictive improvements mean less “air cover from inventory or capacity” is required.

Analytics were broken down as we typically see them — descriptive/ diagnostic/ predictive/ prescriptive, but now we have the math advancement of AI/ML/DL to consider in terms of making better predictions. As a mathematician myself, I have studied this closely and am seeing predictive improvements by as much as 10% as compared to our old analytical approaches across the same data sets. And, of course, with better predictions we don’t need as much air cover from inventory or capacity. That unlocks significant value as well.

#10 Agile implementation approaches are the gold standard. Period.

Finally, implementation was addressed and the popular theme was to apply an agile approach so that the full benefit of the flexible technology offered through the network platforms could be applied to the business. Plus, this allows a focus on improving high value processes first, as part of a dual platform approach.

In Summary

So overall the analysts did an excellent job of showcasing where technology is today and where it is heading, along with all the upside and gotchas along the way. We are evolving from chains to networks and based on that business potential pulling the people, process, and technology along with us. As much as I enjoyed the supply chain evolution we drove in the mid 90’s, I believe that the supply network revolution will be even more compelling. And based on the success of early business network pioneers like Uber, Airbnb, Alibaba, and Facebook, who are we to argue?

Recommended: Watch Now – AI for Supply Chain Practitioners

 

Joe Bellini

Chief Operating Officer at One Network Enterprises
Joe Bellini is Chief Operating Officer at One Network where he provides leadership across the various departments which focus on delivering network-based value across multiple industry segments and geographies. Joe brings his business solution and technology expertise gained through his work experiences at some of today’s leading technology companies, including General Electric, HP/EDS, Brooks Automation, IRI, R1/Accretive Health and Oracle. Joe holds a patent in Supply Chain Planning and is the co-author of the business strategy book, “The Real-Time Enterprise.” Joe holds degrees in Mechanical Engineering, Applied Mathematics and Statistics, is an alumnus of Harvard Business School, and is certified in Artificial Intelligence and Machine Learning from MIT Sloan.