Working towards digitally integrated supply chains

Digitally integrated supply chains are set to transform the way manufacturers deliver value to their customers, and represent a great opportunity for businesses that “make.” Disconnected links and waste in the supply chain have traditionally caused bottlenecks, late order fulfillment, and missed sales—frustrating manufacturers.

But according to a McKinsey study, companies that achieve a high level of supply chain integration could slash operational costs by up to 30 percent and reduce missed sales opportunities by 75 percent. Meanwhile, some 89 percent of C-suite executives expect a higher level of collaboration with partners over the next 3 to 5 years.

By improving production times, reducing response and transit times, and removing barriers to information exchange with partners, manufacturers will be able to build more responsive and enduring supply lines that produce higher quality, more competitive products.

Manufacturers can pursue the fruits of supply chain integration in four simple steps:

1. Double down on core competencies and outsource inefficient processes to take advantage of economies of scale.
2. Integrate Internet of Things (IoT) technologies to create a digital twin of machines, processes, and products to gain end-to-end visibility of the supply chain.
3. Forge data-share partnerships to integrate external information into internal decision making.
4. Adopt the tools for change to make digitally integrated supply chains a reality.

You can’t do it all, so even don’t even try

As the saying goes, “You can’t be all things to all people.” Manufacturers who try to manage all processes involved in the production and delivery of products are likely to accrue a significant amount of unnecessary waste. Just because a firm has the resources and capability to execute certain processes doesn’t mean that they should.

Play to your strengths

In many cases, instead of attempting to pull all of the strings, manufacturers would be better off doubling down on their core competencies. For a machine components manufacturer, this may mean producing high-quality replacement parts, but not necessarily delivering them to factories around the globe in a timely fashion.

Let’s look at Dell; Dell’s core business value is speedy construction and delivery of consumer PCs and computer hardware, but their software solutions have consistently lost out in popularity to industry leaders like Microsoft.

In recognition of this, Dell sold off its software business in 2016 in favor of focusing on the production and sale of made-to-order PCs, servers, and storage products. By leaving the software to software companies, Dell has reallocated its resources to its core business model of built-to-order hardware. Thanks in part to this decision, Dell’s total revenue grew by 15 percent to reach $90.6 billion for the 2019 fiscal year, and it experienced double-digit growth in all three of its business units.

Many manufacturers adopt a similar strategy of eliminating inefficient processes by partnering with logistics companies to deal with inbound and outbound shipments. General Motors, for example, contracts Ryder Logistics to deliver parts to its factories and finished vehicles to car dealers around the country. By doing so, GM not only outsources its shipping logistics, but the time, cost, and expertise that would be required to maintain a freight vehicle fleet.

What not to outsource

As important as it is to eliminate inefficient processes, it’s equally important to never outsource the core value of your product. Take IBM Personal Computers as a cautionary tale. IBM introduced one of the first ever personal computers back in 1981, and by 1985 held more than 40 percent of the PC market share.

However, instead of developing the capability to design and manufacture their PCs in-house, they outsourced production to companies like Intel. Within a few short years, competitors were using the same original equipment manufacturers (OEMs) as IBM to build and release product alternatives. By 1995 IBM’s PC market share had fallen to 8 percent, and by 2005 IBM’s PC business had been acquired by Lenovo.

Relinquishing control of your core competencies places you at an arm’s length distance from the value that you offer to customers—your intellectual property, your product, and even your company are at risk of being replaced.

If you are unsure of your company’s core competencies, ask yourself these questions to narrow it down:

• Who are your most important customers and what keeps them coming back?
• Where do the majority of your profits come from?
• What unique value do you offer that competitors will find difficult to imitate?
• Which aspect of your value proposition will appeal to the greatest number of people?

Cloning isn’t just for mad scientists anymore

The ultimate goal of IoT technologies is to achieve a digital twin of the machines, processes, and products in a manufacturing environment. A digital twin is like a digital replica of the physical assets in factories, in transit, and even in the hands of customers.

Using sensors, cameras, and other automatic data capture techniques, this twin can provide a rich source of information which manufacturers can use to avoid production downtime, increase on-time deliveries, offer a higher level of after-sales service and more.

Engineers can use a digital twin of a connected machine or even an entire production system to simulate changes in the production process. Once engineers are satisfied with the twin simulation, changes can be put into practice on the factory floor. This reduces the uncertainty and risk of adjusting processes.

Connected Machines

Connected machines provide a constant stream of data to factory managers and the engineers that oversee them. They can provide alerts that a part needs to be changed, a system reconfigured, or an impending material shortage. With connected machines, preventative maintenance is the norm, and diagnostics and troubleshooting can be performed remotely.

This is precisely what German manufacturing conglomerate, Siemens, has achieved at their Amberg plant, where 75 percent of production is managed by connected machines. Monitoring statistics from each machine, operators can adjust fan speeds, humidity, temperature, and other factors. Using their digital twin, engineers preview and test the production process for a new product before putting it into action. Using this smart factory setup, the Amberg plant has increased productivity sixfold, while maintaining the same number of staff.

Connected Transit

Late or missing material shipments can bring production to a halt, while delayed product deliveries can place retail contracts in jeopardy. Luckily, connectivity doesn’t need to be confined to the walls of your factory or warehouse.

Vehicle fleets equipped with sensors and integrated with GPS can create a digital twin of transit processes, making more precise shipment tracking possible at a reasonable cost. If items in transit are delayed, receivers can check the exact location and investigate the cause of the delay, instead of receiving a status update that simply says, “scanned at Industry, California – in transit to St. Louis, Missouri.”.

The data contained in barcodes or RFID tags also allow products within large shipments to be traced by bin number, lot number, serial number, and even isolated by batch and raw material source.

In the food industry, one growing use of IoT is temperature sensors in the shipment of perishable goods. By monitoring the temperature food items are exposed to during transit, suppliers can guard against spoiled goods and update expiration dates in real-time.

Connected products

Finally, there is the digital twin of the product in the hands of the customer. From smartphones to cars, data collection from products in the field is already widespread, and with the number of IoT connected devices expected to surpass 40 billion by 2020, remote data collection will continue to expand.

By collecting and analyzing data from products in use, manufacturers are able to perform proactive diagnostics, and suggest maintenance before products break down, ultimately saving their customers time and money, and boosting the value of the service they offer.

For instance, by monitoring the health of equipment in the field, heavy equipment manufacturer, Caterpillar, is helping its customers shift to a model of “repair before failure.” A practical example is air filter replacement. If an air filter needs to be replaced, Caterpillar is able to send the customer a notification and instruct them on how to replace it with an augmented reality application.

In addition to maintenance, data insights from active products can inform other types of after-sales support offered, and the design and engineering of future products.

Creating your own twin

The first step to creating a digital twin is integrating IoT technology to the process, product, or machine in question to collect and analyze data. Just as when adopting any new technology, you can’t make all upgrades at once and be successful. When creating your first digital twin, first decide which benefits you hope the twin can provide.

Are you after reduced production cycles? Predictive maintenance? Fewer defects? Based on this goal, choose one process to serve as proof of concept (POC) and proof of ROI. This is not to say pick only the low hanging fruit, but choose a process that has high potential to yield results and the ability to scale across your organization later. Once your POC is successful, you can add more data points to your initial twin or bring new twins online.

Software companies like Autodesk offer solutions that support the creation of digital replicas of assets and processes. Remember, twins can have varying levels of sophistication and will have different technological needs.

Increase visibility with data-sharing relationships

Integrating IoT technologies allows manufacturers to collect and use data from all parts of the product management lifecycle process they are responsible for. However, as we mentioned in the first section of this article, it is usually inefficient for one entity to manage all aspects of the product life cycle. Therefore, in order to gain greater visibility into each link of production, manufacturers need to forge data-share relationships with partners both upstream and downstream of the supply chain.

Downstream collaboration

The Caterpillar case above is an example of leveraging downstream data to inform current operations and service offerings. Another form of downstream information that can be very useful to suppliers and manufacturers is point of sale (POS) data.

POS data gives a picture of true demand, sell-through rates, on-shelf availability, seasonal trends, and more. Manufacturers can use this data to optimize materials procurement, standing inventory levels, and production cycles. For example, after obtaining POS data from retailers, chemical and textiles manufacturer, Milliken and Company, was able to reduce lead time from order to receipt from 18 weeks to 3 weeks.

A more advanced level of collaboration with downstream partners comes in the form of a vendor managed inventory agreement. Under this type of partnership, rather than simply sharing data, the retailer turns over almost all aspects of inventory management to the supplier. Using a shared database, the supplier is able to see real-time sales, retailer safety stocks, and pending orders—they then use this info to optimize and replenish retailer stocks.

This is the arrangement Kimberly-Clark and Costco has for stocking the branded diaper, Huggies. By making Kimberly-Clark responsible for product inventory, Costco was able to reduce its on-hand diaper inventory by 50 percent, save costs on staffing, and avert stockout situations.

Upstream collaboration

Downstream collaboration helps improve last mile supply chain efficiencies, but it’s usually problems one or two links upstream of the supply chain that disrupt production. With greater insights into upstream processes, manufacturers can use data on wages, strikes, natural disasters, government regulations, etc, to build more durable supply chains.

For example, with geopolitical data, an analysis might reveal a region is prone to seasonal weather disruptions, leading manufacturers to diversify the geographical sourcing of raw materials. With data on vehicle fleet breakdowns and fuel costs, manufacturers can negotiate higher standards of logistics service or search for more reliable partners.

Manufacturers can also reap great benefits by sharing production plans with suppliers. Earlier in this article, we mentioned Dell as an example of doubling down on core competencies.

Dell managed to do this not only eliminating things it wasn’t good at but by cultivating more efficient supply chain processes with upstream information sharing. With a specially designed extranet, Dell shares information with suppliers about inventory levels, components quality and defects, and new part transitions. By making sure its suppliers are well informed, Dell ensures they have the materials they need for production.

Meanwhile, Kimberly-Clark not only utilized downstream retailer data but entered into data-share agreements with its own upstream suppliers. By sharing production plans with its velcro supplier, the firm was able to cut velcro stocks by 60 percent, saving millions of dollars. Kimberly-Clark’s combined up and downstream data sharing efforts resulted in trimming supply chain management costs by more than $200 million.

How you can start with digital integration

All of the examples of supply chain integration discussed in this article were supported by robust IT solutions that made greater collaboration possible: Caterpillar with IoT products and software diagnostics, Dell with its extranets, and Kimberly-Clark and Costco with shared databases.

In order to realize the potential of supply chain integration, manufacturers need to have the right IT infrastructure in place. As a prerequisite to working more closely with partners, your organization needs to first have its own house in order. This means consolidating all core digital processes with a business management solution built for manufacturers.

With a single solution for inventory management, purchase order management, sales fulfillment, and business insights, your business will be in a better position to work more closely with both internal and external partners.

While sharing proprietary data like on-time delivery to commit records or product designs is necessary to achieving a more integrated supply chain, data transfer can be a cause of concern. Luckily, new software solutions like those offered by Identify3D can protect digital assets so that even with regular data sharing, information does not become vulnerable to misuse, corruption, or theft.

Industry 4.0 solutions like these and others are paving the way for manufacturers to build closer ties with partners and take advantage of digitally integrated supply chains.

Recap

Digitally integrated supply chains are part of the larger drive to deliver valuable, personalized product experiences. For manufacturers looking to transition to a digitally integrated supply chain, the following initiatives are a great starting point:

• Double down on core strengths and outsource inefficient processes
• Integrate IoT technologies to gain insights into assets in production, in transit, and active in the market
• Cultivate data-share relationships with partners upstream and downstream of the supply chain to inform decisions and production planning
• Adopt the technology tools needed to facilitate internal and external collaboration

Making supply chains digital closes information gaps that have previously separated various points of the product life cycle. With processes and people more connected throughout the supply chain, manufacturers can bring efficiency to their operations, and greater value to their partners and customers.