Twin brothers Roland and Richard Mokuolu are the founders of Partsimony (formerly Inventaprint), a digital platform at the intersection of prototyping, sourcing, and supply chain management. Their backgrounds — in civil and mechanical engineering, respectively — inspired a solution that allows hardware companies to better collaborate with existing manufacturer networks.

Supply chain innovation is causing companies, from enterprise to mid-market, to rethink structure, intent, and strategy. But beyond the need for greater efficiency and faster speeds, few are tackling the tough questions around flexibility and dexterity; the true outputs of increased connectivity. Roland and Richard Mokuolu of Partsimony (formerly Inventaprint), a Newlab member company, have identified a niche opportunity to quantify how connectivity tangibly impacts sourcing, inventory, capital, design intent, and production.

1. What does Industry 4.0 promise in terms of supply chain digitization? How does Partsimony fit in?

Industry 4.0, that is a connective ecosystem, is not a new concept. At least not to people in the industry. Companies know what Industry 4.0 is but they haven’t nailed down the ‘how’ yet since connectivity changes depending on how a supply chain is structured. Companies have a lot of data that wasn’t made for Industry 4.0 because it lacks cohesiveness: data may be missing or miscategorized and there are silos within teams. Connectivity requires one source of truth that automatically updates. Partsimony is scaling that knowledge gap to be the source that ties everything together and improves with an evolving supply chain strategy.

2. A lack of connectivity creates the most impact on working capital but many companies focus on speed to address supply chain dysfunction. Why isn’t there a focus on solving for capital?

Simply put, it’s a harder problem to solve. It’s easier to focus on time, guarantee expedited turnaround times at a high cost, and be reactive. Our end goal is to look down the pipeline and understand what’s coming. If there is a tariff in China, we may already have manufacturers in Mexico that can spool up production. If there is a reduction in volume for a specific product line, it’s critical to ensure you’re managing inventory appropriately.  Working capital is what enterprises, like the GEs of the world, ultimately care about.

3. What does it mean to have a cognitive supply chain? And how can a company become more predictive?

A cognitive supply chain is defined by agility, flexibility, personalization, and adopting a unified technology approach to align the thousands of internal influences and external variables (e.g. supplier networks, sensor data) to reach an optimal output. To achieve operational effectiveness and become more predictive in managing working capital and supply chain planning, companies must adopt an ecosystem rooted in clean, structured data and machine learning, AI, or blockchain approaches. Especially, given the ever-changing landscape within the hardware space (e.g. tariff wars).

At Partsimony, we are building a cognitive ecosystem that helps to effectively manage supplier networks by using component specifications to predict ideal suppliers to manufacture any given part, and enrich organizations sourcing execution strategy after the supplier connection has been made.

4. We have this idea — especially in tech — that to be the best you have to replace what came before you. But when it comes to Supply Chain 4.0, it would be irresponsible to not build upon the past 50+ years of manufacturing innovation. What are smaller, but critical, steps companies can take to digitize their supply chain?

Leveraging historical structures and learnings is key. 20 years ago, the paradigm shift was about ease of transactions and identifying suppliers. Now, it’s about how to make sure data is accurately captured to become a better negotiator or enhance leverage with suppliers. No one was really thinking about it in this way back then since that knowledge tends to be siloed within organizations.

Today, we’re building a connected environment to help quantify data flowing through the supply chain and use it to drive those negotiations. We’ve seen enterprise customers over-complicate process given their scale and need for layered structures, whereas mid-market brands over-simplify due to a lack of centralized data points, which can tarnish negotiation leverage. The first step is to ensure the process in place is optimized to be a central source of truth with clean data that has been validated to be accurate and relevant.

5. Do you predict that supply chain digitization will scale domestically before going global?

If you look at where supply typically comes from, it’s from lower-cost countries. The US and Europe are leading in adopting this vision in the short term. But countries like Nigeria — where we’re from — Mexico, or Vietnam, even though they don’t have the infrastructure in place, will come up to speed quicker because they need to. When you talk about a connective, cognitive supply chain they have to be involved and build the vision. They’re the ones making the supplies. There is no Industry 4.0 without those countries.

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