Lora's Latest Post

Bright and Shiny Objects?

This month, I traveled the globe helping companies understand the potential impact of technology innovation on the future of supply chain processes, I find the term “digital innovation” is a bit like tulip mania. How so? It is a fad sweeping across supply chain leadership teams. I am trying to help teams manage the hype and drive value.
CIOs are rebranding as Digital Innovation Officers, and consultants are knocking down doors to sell digital innovation projects. Let me start with caution: buyer beware. Consultants are rebranding traditional processes and technologies as digital innovation. My advice? Sidestep the hype and drive exciting innovation with an exciting confluence of technology as shown in Figure 1.
Figure 1: The Confluence of Technologies

In my 15 years as an analyst, I have never seen more promise. However, we are in a hype cycle. Sort fact from fiction. There is a need to manage excitement and exercise caution.
Exciting Trends.

  1. Redefinition of the System of Record. Enterprise Resource Planning (ERP) is becoming the financial system of record, but not the supply chain system of record. With the evolution of open source technologies with schema-on-read capabilities, new forms of decision support are evolving to drive insights in the enterprise, and Blockchain is becoming the system of record for B2B. Blockchain for track & trace, supply chain finance, lineage, and supply chain visibility are exciting. I am actively working with WFP to try to fund world feeding programs with less financial leakage and provide a system of record for famine projects.
  2. Driving New Outcomes. The pace of best-of-breed technologies is frenetic. The pace of innovation is accelerating. ERP-agnostic architectures using machine learning and streaming data architectures are enabling new and promising capabilities. One company that I follow worked on visibility solutions for the past five years using traditional Advanced Planning and ERP capabilities. They made little progress. Then they turned to Solvoyo and used machine learning to deliver supply chain visibility in a heterogeneous environment within two months.
  3. Digital Manufacturing. Manufacturing Execution Systems with Data Historians have inched along over the years, but we have not been able to radically change manufacturing. Now, the use of systems like Think IQ at General Mills enable Track & Trace capabilities through manufacturing conversion points. In parallel, the work at SAS on IoT is transforming asset-intensive supply chains. The combination of wearables, IoT, and analytics is a powerful combination.
  4. Analytics Redefined. Driving Data-Driven Processes. Analytics is transformational. This is much deeper than data lakes and descriptive analytics. In Figure 2, I share an overview of the analytic approaches from some recent research. (Join us this month to learn about the redefinition of analytics on our monthly webinar series.) Cognitive engines will redefine decision support, machine learning is making traditional master data techniques obsolete, and data is moving now at the speed of business.

Figure 2. Disruptive Analytics Approaches

Caution.
This is not an evolution. It is a step-change in thinking and redefines IT approaches. Far from your mother’s old-fashioned supply chain processes.
Digital innovation will make much of the past obsolete. This is a tough transition for conventional ERP, APS and consulting companies. It is a bit like watching Kodak continuing to sell packaged film when they should have been redefining photography.
Digitization of signals does not drive a digital supply chain. A digital supply chain requires the use of digitization to redefine new processes. Most companies have not defined the differences between digitization and digital processes.
To have the discussion, business leaders will need to reskill and learn. This a major barrier. It is the rare leader who will raise their hand and say, “I don’t understand.” Companies need to prove the concepts and wrestle their IT teams from long and drawn-out maintenance upgrades. This will be uncomfortable. Many IT organizations define their existance from SAP and Oracle skill sets.
The implementation processes are starkly different from those of the past. Historically, projects were large and encumbered by bureaucracy. This is not the case with digital test-and-learn programs. Side-step the large implementations with traditional consulting partners and engage in design thinking. Test innovation at the edge and use stage-gate processes to drive improvement at the core.
Wrap-up
In one of my sessions last week, a client mentioned, “This is quite interesting Lora, but we do not have the time to chase bright and shiny objects. We need to focus on the basics.” I then asked, “How do you define basics?” In the end, we found that these new techniques were instrumental in improving the gaps in customer service, and reducing demand error. As a result, master data issues disappeared and visibility increased. To me, this does not sound like a bright and shiny object. It, instead, became transformational. However, it only happened because the client sidestepped the hype, invested in learning, and was open to new approaches. Defying convention may help unleash new opportunities through new technologies. These are my thoughts on a snowy day. Good luck on your journey.
I welcome your thoughts.

Search the Archives
Search
Share this Post
Email
Twitter
LinkedIn
Facebook
Pinterest
WhatsApp
Featured Image
Recent Posts

AI Defining a Middle Ground Between Custom and Packaged Applications in Supply Chain Planning

Supply chain planning has evolved technologically, but its underlying processes remain rooted in historic practices that no longer fit today’s volatile, complex environment. Packaged applications promise faster, lower-cost, lower-risk business outcomes, yet extensive customization, fragmented data, and rigid workflows often undermine that promise. Cloud data and AI platforms like Databricks and Snowflake offer an alternative: build interoperable applications on top of existing planning systems to address gaps in direct procurement, plan consumption, bullwhip reduction, operational planning, and dynamic master data. The opportunity is not simply to automate existing processes with AI and agentics, but to redefine how work gets done through end-to-end orchestration, value-based trade-offs, and clear decision governance.

Read More »

Reflection and Celebration for the Supply Chains to Admire Methodology

The Supply Chains to Admire to is an objective, data-driven standard for measuring supply chain excellence and moves beyond industry reputation, anecdotal evidence, and technology claims. Using revenue growth, operating margin, inventory turns, and return on invested capital (ROCE, the research evaluates how companies perform relative to industry peers over time. Here Lora shares information on an upcoming event to celebrate the Supply Chains to Admire Award Winners.

Read More »

Five Things I Don’t Understand

Solutions that we never imagined years ago are emergining, but I pause when companies are unwilling or unable to roll up their sleeves and redefine work. Historic practices are not best practices, and there is a wealth of opportunity for those that do challenge the existing status quo. .

Read More »

My Answer to Joe. The Future of APS

Traditional Advanced Planning Systems (APS) are unlikely to become true enterprise platforms because organizations remain functionally siloed, metrics are misaligned, and current APS architectures were designed for an environment that has fundamentally changed. Here I share how I think that APS systems can adapt to drive more value.

Read More »

Teaching Your Organization to Jump

Remember the story of the frog in the pot of water? If the water temperature rises slowly, the frog doesn’t recognize the danger until it is too late. Put the frog directly into boiling water, and it jumps.

I think the analogy applies to today’s supply chains.

Companies are absorbing increasing volatility and complexity without fundamentally redefining how work gets done. Companies have confused historic practices with best practices. They are now taking those same processes and attempting to automate them with agents and agentic AI—without first stopping to ask a more fundamental question: Is it time to jump? Here I give a five-step action plan.

Read More »

Navigating Supply Chain Economic Downturns

In 2007, the average company took six months to sense market shifts and adapt its supply chain. My estimate, based on work with clients, is that if a downturn happened today, the average company would take 20-30% more time to adjust than in 2007. Here I give insights on preparedness.

Read More »