Is your cereal really gluten-free?

Smart manufacturing and supply chain traceability is finally coming of age — but why aren’t more brands embracing the change?

A lack of traceability comes at a very high cost

Only a few months after announcing that five of its Cheerios cereal products would be going gluten-free — a move designed to address the needs of up to 30% of consumers, General Mills announced a voluntary recall of 1.8 million boxes of original Cheerios and Honey Nut Cheerios. This is an equivalent of four and 13 days of production, respectively.

Of course, such recalls come at the expense of a brand’s money and reputation — both of which take a substantial amount of time to recover. The average cost of a recall to a food company is $10 million in direct costs, in addition to the arguably more significant costs of brand damage, loss of sales, litigation, and mandated government oversight post-incident. For larger brands, the costs can be significantly higher; 77% of respondents to a Grocery Manufacturers’ Association poll estimated the financial impact to be as much as $30 million — with 23% reporting an even greater figure.

If smart manufacturing is so much better, why are we still so analog?

In several safety-critical industries — including aerospace, pharma, and medical equipment — sophisticated and regulated provenance systems already exist. Assuring the pedigree of ingredients and components is already a standard practice, despite the cost and complexity.

“Smart Manufacturing” goes by many names, including “Digital Manufacturing”, “Industry 4.0”, and “Industrial IoT”. It is meant to illustrate fully-integrated, collaborative manufacturing systems that go beyond traceability and are able to respond in real-time to the changing demands of factories, supply networks, and customer needs. Leveraging technologies including internet-connected machinery, advanced analytics, and artificial intelligence, smart manufacturing enables the efficient, demand-driven use of resources and supplies in highly-optimized plants and supply chains — yielding a number of benefits including an estimated 3–5% productivity increase and 25% improvement in energy efficiency.

The industrial evolution: four generations of industry

Despite the value of the opportunity exceeding $2 trillion and nearly 70% of manufacturers with revenues above $1 billion reporting having smart manufacturing initiatives, only 14% consider these deployments to be a success. Why?

1. Over 50% of the organizations are not prepared for the deployment and integration of digital platforms and technologies and cannot access and analyze data from across their value chains. Many current systems are horizontally fragmented between silos (due to minimal technical synergy between agriculture, logistics, storage, processing, distribution, and retail) as well as vertically fragmented within the individual business silos (due to brittle boundaries between automation, execution, planning, and financial systems).
2. Manufacturers are struggling with lack of products and platforms that do not require extensive customization and configuration before being production-ready.
3. The potential of plant digital twin has yet to be realized — a key for “efficiency by design” and providing the right contextual information needed to unleash all of the improvement potential.

Material flow analytics are helping to address quality, yield, and traceability across the supply chain

Fortunately, new technologies are changing the economics of tracking, making batch - and item-level analysis possible in more industries and for more purposes — beyond the traditional approach of using RFIDs and QR codes to track expensive, safety-critical components in a handful of discrete manufacturing applications such as aerospace and defense.

ThinkIQ is an emerging leader in digital manufacturing and continuous intelligence — and one we believe is head and shoulders above existing solutions from incumbent ERP and industrial automation providers.ThinkIQ helps manufacturers improve yield, quality, safety, compliance, and brand confidence — while reducing waste and environmental impact. Their software solution provides a more precise understanding of manufacturing data that can be utilized to better fine-tune production execution.

The company’s fact-based granular and data-centric contextualized view of material flows and related provenance attribute data transcends the supply chain “farm to fork” and integrates directly into existing IoT infrastructures. It has already helped transform production lines at leading global brands such as General Mills, McCain, Corning, and Mars, helping customers to save tens of millions by identifying waste and underperforming assets, as well as reducing warranty reserves for quality and safety issues. But what exactly makes ThinkIQ stand out?

• A “Lego” building block approach which is software-driven and generalizable, combining the ability to connect to almost any existing system (e.g. live sensor data, MES, ERP) with the industry-leading libraries of assets common across process and hybrid manufacturing and the generic material ledger needed to build reusable and configurable semantic models (i.e. digital twins). Fulfilling the vision of becoming “QuickBooks for digital manufacturing” requires this type of laser-sharp focus on a productized offering (with minimal customization), while still enabling deployment and a clear demonstration of value within a matter of weeks.
• Proprietary material flow analytics for the traceability and analysis of materials generally lacking in unique identifiers, unlike the RFID tags approach used in high-value discrete manufacturing. While conventional batch tracing enables producers to work backward and piece together the source of an issue after the fact, ThinkIQ is able to analyze uneven time series data across raw ingredients, equipment, and processes in a near real-time state, using machine learning and semantic modelling to provide the much needed “context” around all outputs. Every detail of the production and supply chain process can be incorporated into an item’s record as it transforms from a raw material input into a product on the shelf. This data constitutes a goldmine for manufacturers and can be used to analyze quality, safety, durability, reliability, and profitability in order to create actionable and timely insights.
• A rockstar founding team that deeply understands manufacturing and industrial software, including producer pain points left unaddressed by existing solutions and approaches. Doug Lawson, CEO, is a serial industrial software entrepreneur, most recently having sold his venture-backed startup Incuity to Rockwell Automation and subsequently serving as Rockwell’s Chief Software Strategist before founding ThinkIQ. Niels Anderson, Chief Product Officer, brings an in-depth understanding of business and engineering needs of the manufacturing industry, with decades of industrial automation experience that includes being both a startup CEO and senior leader at Wonderware.

ThinkIQ, a leading digital platform for supply chain traceability and smart manufacturing, tracks material properties “farm to fork” to maximize manufacturer profitability and consumer confidence

At ArcTern Ventures, we are thrilled to be helping accelerate ThinkIQ’s next phase of growth through our investment into the company’s $11.6 million Series A alongside new investors Ecosystem Integrity Fund and Hitachi Ventures.

ThinkIQ has all of the experience, products, and engineering prowess to accelerate the transition to Industry 4.0 — saving companies millions of dollars, and giving consumers renewed confidence that labels such as “gluten-free” aren’t merely an aim — but a guarantee.