To mitigate the timing issue, more organizations are pursuing the concept of continuous innovation for their supply chain
This article was originally published on TechDecisions.

When it comes to marketplace innovation, time is of the essence. Over the last two decades, 52 percent of Fortune 500 companies have gone extinct. This statistic alone proves that many businesses, even stellar ones, don’t survive for an extended period of time without going through a reinvention of some sort. The tough decision for today’s enterprise leaders is knowing when to undertake a strategic, innovative transformation; when to change a company’s core products or change its business model.

This, combined with the high risk of failure, makes the business transformation journey a harsh reality.

Harvard Business Review research has suggested that more than 80 percent of executives at large enterprises recognize the need for transformation, but only one-third of those executives are confident that they can get the job done in five to ten years. No doubt, reinvention or transformation of any sort doesn’t happen overnight; it happens over a period of time.

To mitigate the timing issue, more organizations are pursuing the concept of continuous innovation.

Today’s supply chain business is volatile, divided, and uncertain. To succeed, organizations need to:

• 1) adopt a continuous-innovation mindset
• 2) recognize and deal with failure
• 3) map, analyze, and redesign the supply chain business processes.

Adopt a continuous-innovation mindset

While delivering the Perfect Order is the ultimate goal for many supply chain managements, the primary reason it doesn’t materialize is because the supply chain ecosystem continues to work with traditional mindsets.

The journey through the supply chain ecosystem is time-consuming, and each step in the process holds potential for delays. The complexities of an extended supply chain make for overwhelming odds against fulfilling a perfect order.

So how does a supply chain organization adopt a continuous innovation mindset while responding to market demands?

It’s not easy because innovation and the risk-taking culture don’t come naturally to supply chain operations.

One solution to this conundrum is to create a twin-model talent approach, a focused approach to supply chain operations and innovation.

While the operations talent model takes care of the business as usual and continues to service customers on a day-to-day basis, the innovation talent model, on the other hand, challenges the status quo by experimenting with new technology and pushes the current limitations.

The rules by which the innovation talent model operates are fundamentally different from the operations talent model because in order to innovate, this talent group must be able to experiment, iteratively learn, fail, and repeat.

While traditional supply chain organizations struggle to embrace this parallel culture, the market realities force them to adapt.

Following winning organizations’ lead, more companies today are, in fact, embracing the twin-model talent approach to experiment with new technologies and letting the chips fall where they may.

They’re promoting a culture that suggests good ideas can come from anywhere and giving employees access to reliable and useful information so that they’re empowered to make decisions faster.

Companies need to communicate their purpose in a way that’s universally understood to gain alignment on strategy.

When companies have alignment on strategy and when their employees understand the purpose and are empowered to make decisions, the culture leads to a high-performing supply chain organization that adopts continuous innovation and gives a supply chain the much-needed drive to continuously improve and grow profitability.

Recognize and deal with failure

So why advocate for failure? Because when time is of the essence, it’s best to fail forward rather than doing nothing and falling behind.

Many of today’s most successful organizations, including Apple, Tesla, and Amazon, have failed their way to success. In fact, these very companies have used their failures as a pivot point, and there are lessons to be learned from them.

Apple, the first U.S. company to hit a market cap of $2 trillion, was once known for its design flaws, constant software glitches and lower sales.

Yet, today’s success can be attributed to streamlining its supply chain by outsourcing manufacturing. Components and materials are purchased from various suppliers and get shipped to an assembling plant in China.

From there, products are shipped directly to consumers who bought from Apple’s online store.

Apple uses multiple suppliers for the same component in its supply-chain strategy, providing it with substantial latent capacity. In addition, Apple succeeds through extraordinary inventory control.

When it comes to technology such as smart phones, tablets, and laptops, inventory depreciates very quickly, losing one to two percent of its value each week.

Looking over the past five years, Apple’s inventory turnover hit its lowest point in September 2018, when the company turned its inventory every 10 days.

Tesla, best known for its electric cars (despite many supply chain failures, including the recent Model 3 production setbacks), uses vertical integration as a competitive edge.

A vertical supply chain integration is where the business owns as much of each step in the supply chain as possible. Tesla chose to build its Gigafactories mainly in California and Nevada vs. produce parts or do assembly in either Mexico and China to reduce the expense of labor and transportation required to move parts to the next facility.

Though Amazon’s failures resulted in billions of dollars before it became the most formidable force in the global retail market, its innovative and highly efficient customer-centric supply chain is one of the driving forces behind its transformation from a simple online bookseller.

With over 130 million stock-keeping units to manage and millions of transactions to control, Amazon’s supply chain drives its customer experience to a distinct level. So how does Amazon do it? By investing 12 percent of its revenue in technology; Amazon takes controlled risks.

It’s often the first to experiment with new digital capabilities and that pays off. An impressive 40 percent of the company’s revenue is obtained through digital services.

In growing, diversifying, and managing both the physical and virtual world, Amazon is no longer simply a retail giant but a hybrid business model for the foreseeable future.

These three organizations—Apple, Tesla, and Amazon—have one thing in common: A customer centric supply chain combined with a great organization culture that understands failure is vital to success.

Map, analyze, & improve supply chain processes

A good place for mapping and measuring the supply chain processes starts with the customer and works backwards. In order to continuously improve, leading organizations benchmark their supply chain process by gathering performance data, thereby capturing organizational metrics, including everything from shipping and arrival date, quality inspection, put-away, and warehouse pick, pack and ship.

Also, they determine whether or not the data collected are valid, reliable and accurate. It’s quality data that add value, and the best organizations benchmark these data points against their own organizational goals (existing and historical) and industry standards in order to find the performance gaps that exist in their supply-chain models.

Since it’s all about time, the whole process of gathering performance data has to be improved.

Adapt advanced analytics (i.e., continuous intelligence), which include predictive analytics (those that identify data patterns and anticipate future scenarios) as well as prescriptive analytics (a set of capabilities that finds a course of action to meet a predefined objective). Advanced analytics is the conduit making the data available to all stakeholders at the right time, thus increasing efficiency and saving time and money.

Connected data provides continuous intelligence, which is the fuel enabling executives to make real-time informed decisions. For example, in the case of the aerospace industry, where a part failure could cost lives, the sensor data from the Internet of Things (IOT) will be able to perform predictive analysis to determine the probability of parts’ failure before it happens. Based on this reality, prescriptive analysis can be performed to suggest the next course of action.

Once data are gathered, the next step is to analyze the data to provide insights as to how the product flows through the supply chain ecosystem to the customer and the process inefficiencies along that path.

Based on those insights, comparisons can be made across the organization to determine performance standards.

Are the processes viable? What trends do we see? What is the forecast accuracy? Where do we stand with regard to shipments’ status, fulfillment times, on-time-deliver variances, quality rejects, etc.?

In the end, these analyses form the empirical basis of continuous improvement plans and, ultimately, supply chain redesigns.

To identify process inefficiencies, adapt the Supply Chain Operations Reference (SCOR) model:

The SCOR is a process-reference model, one that integrates data-collection, measurement and analysis, and supply-chain improvement steps into a cross-functional framework based on six functions of the supply chain:

• 1) plan
• 2) source
• 3) make
• 4) deliver
• 5) return
• 6) enable from supplier’s supplier to customer’s customer

Developed by the Supply Chain Council of the Association for Supply Chain Management (ASCM), this model is a bridge between performance to process and people.

It seeks to help companies analyze their supply chains, giving them an idea of the problems embedded within each step of their supply chain process.

According to the ASCM, “The model enables full leverage of capital investment, creation of a supply chain road map, alignment of business functions, and an average of two to six times return on investment.”

To keep up with change in times, SCOR standards have been recently revised to move from sequential chains to digital supply networks; it’s the new SCOR Digital Standard (SCOR DS).

What comes next after the analyzation of the supply chain is the improvements to the supply chain’s performance. The issue is to determine what kind.

An organization must determine whether these changes will be short-term or incremental improvements, and include recommendations for changes to processes, technology, or metrics that better align with strategic or long-term objectives.

Enter the saving grace of technology. Paired with powerful advanced analytics and the industry-recognized, standard SCOR process model, technology’s role in today’s supply chain management has fundamentally changed how companies operate, simplify and standardize operations based on customer needs.

Today’s technology is aware, thanks to sensor technology; intelligent, thanks to automated decision-making and self-learning capabilities; connected, particularly when paired with other devices; and responsive. What companies get is the ability to collect and analyze performance data and improve processes in a much more efficient way.

A great example of where supply chain companies can improve is in implementing the perfect order metric. This measures every step of a customer’s experience, from order entry, credit checks, inventory availability and picking, to on-time delivery, invoicing, and payment.

Only an order that gets everything right counts as a perfect order, and it does matter to profitability. According to Advanced Market Research (AMR) research, a three percent increase in perfect orders equates to a one percent increase in profits.

Since so many things can go wrong, it isn’t surprising that even the best organizations have considerable room for improvement in this area.

One thing is certain: Over time, companies need to review their core processes and eliminate those activities that don’t serve or add value to their customers.

Inevitably, they find system flaws and work to change them or purge them from the system. They increase their supply chain’s visibility and automate where it counts, keeping all aspects of the supply chain well-managed and improving efficiencies.

They work to enhance customer satisfaction by capturing value and telling the stories that matter to their customers.

In short, they focus on evolving their people and organization culture, their data management, their processes, and their technology in order to evolve their supply chain. It’s imperative.

Back to timing

Many innovators have held the right vision for their organizations, but their success and failures were challenged by time. In general, consider any big-name companies like Toys “R” Us, Kodak, and Compaq that have disappeared over the past decade or so.

Chances are those companies failed to execute the fundamental concepts of continuous improvement in time.

As innovation increases and the viable lifecycles of the innovations shorten, the increased pressure on the supply chain can lead to grave failures.

Understanding that failure can be used as a pivot, supply chain organizations can re-establish themselves and the innovation cycle can continue.

In an extremely crowded supply chain environment, continuous improvement is a necessary element of organizational success, if not survival.

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