Your supply chain is no longer adequate. It’s not broken, and it’s not that the supply chain was poorly designed. It is simply that the expectations of your customers have dramatically changed and your supply chain hasn’t kept pace. You’re zeroed in on the old way of doing things that built your customer base when it’s the demanding New Customer that you must now woo (and wow) to grow that base.

The New Customer wants something different, something that the supply chains companies have worked so hard to build cannot provide. This New Customer is present in both the consumer and business markets. Companies that build a Digital Supply Chain to meet the needs and desires of the New Customer will have the advantage. But execution is hard because you must change the mindset of supply chain leaders that made their company successful by moving production to China, standardizing products and parts, improving forecast accuracy and managing the backside of the business.

The New Customer has more expansive expectations and requirements that could not have been imagined even five years ago. Here are the key elements:

Simultaneous fulfillment of demand and delivery. The New Customer expects that whatever they want will be delivered nearly instantaneously. We have been trained by Amazon to expect that delivery takes no more than two days—max. And this expectation of instant satisfaction is only getting more acute. What do you think will happen when CVS delivers “drugs by drone” to your home with no lag time? This is not just a consumer phenomenon: B2B companies expect the same treatment. While this demand seems extreme and potentially expensive, the value is not only to the New Customer. Companies can expect to move products and services faster and collect payment much quicker.

Bespoke products and services. The New Customer wants something unique to them and their business. Henry Ford’s motto (“Any color as long as it is black.”) made sense back in the day. But now people want things made to fulfill their needs. Under Armour, for example, lets customers design their athletic shoes. This is contrary to everything we know about supply chain efficiency.

Public review by anyone on everything. The New Customer expects that they will have full access to reviews by their peers. There will be no more secrets and smart marketing will no longer overshadow mediocre reviews. This means that companies must understand what the New Customer likes and be agile enough to deliver.

Price that changes, in a logical way. The New Customer understands that prices should change based on demand. Uber adjusts pricing based on market activity. Southwest manages to price fares in such a way that the passenger seated next to you may have paid half as much, or twice as much considering real-time demand. Dynamic pricing will require a Digital Supply Chain that includes, among other features, world-class data analytics.

Social values that match. The New Customer expects that companies will be able to confirm the origin of all products/services and attest to their being developed and delivered without poor labor conditions or environmentally destructive practices. In many markets, an un-aligned social value proposition will kill a product. Today, most companies are unsure of the conditions of their suppliers and may lack any insight into what Tier 2 or Tier 3 vendors are doing. Some companies like it this way. Big mistake.

Delightful user experience. The New Customer expects that the user experience will be delightful and rich. Companies like Dell understand the role of the supply chain in making this possible. Whether you are buying a server, storage or PCs, the end user (and distributors) make the process straightforward. The New Customer expects that the supply chain will deliver a joyful, not painful, experience.

It takes a community. The New Customer expects that “like-minded people” will enjoy the same product or service. These people will post about how they are using what you deliver. The New Customer expects a community. How many traditional supply chain leaders are working to create this community?

Privacy is protected. The New Customer does not like it when their data is shared. This is true for companies and individuals. Recent legislation, especially GDPR in Europe, demand the “right to be forgotten.” This movement is gaining momentum.

Sharing is okay when it’s relevant. Everyone expects that they will be offered experiences, products, and services that meet their needs. My time is wasted if I receive an offer on hair care products, but I am delighted when I receive an offer about Ducati motorcycles. Companies are no different. They don’t want to see products and services that are not suitable for their industry.

While I have covered many dimensions of the New Customer, it is important to understand that the future will rely on a new generation of Digital Supply Chains that meet the needs of the New Customer. To get there, companies have to bring people with deep analytical skills into leadership to institute the technical and cultural changes required to transform the supply chain.

This will not be easy. The hard part will be changing the mindset of supply chain leaders. But companies must understand that the New Customer requires features that fall to supply chain leaders to deliver. Companies need a new approach to enterprise supply chain management that focuses on the customer and maximizes demand. That is, they need to do what I call a Frontside Flip. In other words, flip the focus of the supply chain to the customer-facing side — the frontside — of the business. Do it now before the New Customer takes their business to your competitor.

Over the next three years, the companies that are winners or losers in their markets will be determined by how well they DAAAB.

DAAAB?

That is what I call the collection of powerful new technology and management tools reshaping global supply chains. DAAAB stands for Deep Learning, Artificial Intelligence, Algorithms, Analytics—all the essential elements for a digital transformation that will ultimately produce Business Results.

DAAAB represents some of the most exciting tools in business today because they help companies create new opportunities for visibility and agility. Companies can use DAAAB to tightly link their supply chain operations to their customers—and their suppliers, and their supplier’s supplier, as well as their customer’s customer. DAAAB is all about the data, but it is the combination of technology and management skills that companies need to master to harness the tremendous power of data to improve business operations.

Here are some straightforward definitions of the key elements of DAAAB:

• Deep learning is the software that figures out relationships (based on neural networks).
• AI (Artificial Intelligence) applies business rules to problems and gets smarter and better every day.
• Analytics is about figuring out what the data means and how one data point influences another.
• Algorithms are sets of rules or formulas that drive business operations.
• Business results are hard-number improvements in revenue, cost, and customer happiness.

Look at today’s dominant digital natives. Companies like Amazon, Google, and Facebook sit at the top of their markets and are making a fortune deploying DAAAB to create huge shareholder value.

Yet few businesses are actively managing DAAAB. They have only begun to experiment with Deep Learning. Every business leader (well, maybe not everyone) is talking about AI and Analytics. Executives are using the term algorithm, but do they have a process for developing and deploying them? That’s doubtful. Few companies have truly implemented a solution using these technologies and improved the results of their business. Many have hired data scientists, upgraded their computers and networks and committed to making more data-based decisions. Some companies are making tangible progress, but most are conducting more limited or controlled experiments.

How can you and your company use DAAAB to get results?

I had a chance to spend some time with Wes Nichols at our recent Executive Leadership Forum in Santiago. Wes is co-founder and CEO of MarketShare, the world’s largest analytics software solution for CMOs. Wes has worked with many of the largest companies to adopt data-driven decision-making, analytics and AI solutions as a serial entrepreneur turned independent board director and investor. He understands all the elements of DAAAB and has helped companies improve their business. Wes told me: “I have been working with companies on DAAAB-related deployments around the world, and virtually all companies are underestimating the power of the data they have in-house, while at the same time overestimating the quality of their home-grown analytics and algorithms.”

I bet that your company has valuable data that is not fully exploited and that you need new data that you don’t currently have. And I’ll wager that you are not actively managing or using DAAAB. Here are a few tips on how to get better, quickly:

1. Clean the data that you currently collect and obtain the new data that you need either through trading for it or using sensors/other data collection methods.
2. Use AI to help collect, clean, and analyze the data.
3. Set up a cross-functional team to develop algorithms that better link the customer to supply chain operations, as well as use analytics to improve your demand chain operations (sales, marketing, promotions, etc.)
4. Set targets for revenue growth and cost reduction and build them into performance plans

Now is the right time to ramp up DAAAB. You will beat your competitors by ensuring your supply chain is firmly tied to customer desires. You will likely need new people resources that are deep into data science and others that have market-facing experience. And don’t underestimate the degree of culture change needed to make this happen. Traditional managers often rely on gut feel and not on the insight provided by DAAAB. Change won’t come quickly. So, don’t wait to get started using DAAAB.

Now some of you may be familiar with another “Dab,” the dance move that became a global sensation thanks to Carolina Panthers quarterback Cam Newton who celebrated his team’s “victory” by doing the Dab after each touchdown. That’s how the dance move came to be associated with victory.

I don’t expect we’ll see videos of CEOs doing the “Dab” like Cam (or the French footballer Paul Pogba), but business leaders that embrace DAAAB will celebrate their victory.

One of the major hurdles companies face in transforming to a Digital Supply Chain is their inability to get data from customers and suppliers—or even from other departments in their own company. Nothing new, right?

What is new is the idea of “trading data” to overcome that hurdle and use as a catalyst for Digital Supply Chain transformation. Let me explain.

Companies are aggressively turning to artificial intelligence and machine learning (AI/ML) to gain a competitive advantage. But for that strategy to succeed, companies must develop algorithms that rely on AI/ML technology to run their business. And what is the life force behind algorithms? Data. Lots of data. That makes data trading, internally and with customers and suppliers, essential to unlocking the power of AI/ML.

The critical management question is how to do it?

Understanding how to value and trade data with other departments and with value chain partners starts with thinking about data as you would money. Once you think about data like money, it becomes clear that you have to be strategic in using it.

Consider the negotiations you have with other departments in your organization. Maybe it’s about budgets and who’s going to pay for something from their budget. Just like money, your supply chain department has data that may be really valuable to other departments such as product development or sales. And other departments certainly have data that would help your supply chain to gain more visibility into demand and risks.

Craig Moss, the leader in the data trading space, says “Data trading is not easy. But with the right approach companies can get the data they need to dramatically improve their business”.

The real power of data trading, however, comes from your supply chain. One of the most important aspects of the Digital Supply Chain is collaboration that extends beyond the boundaries of your organization. Just as you exchange money for goods and services, you can exchange your data for data from your suppliers and customers. This is where it gets interesting because unlike money, the value of data is relative. It depends on the context and how it fits into each company’s strategic puzzle.

Based on our interviews with business leaders, most companies are frustrated by the lack of data sharing with their customers and suppliers. Of course, one issue is the desire to protect proprietary data and not lose a competitive advantage. But another root-cause is the vagueness of what data sharing means to each company. Let’s be realistic, no company is going to give you all of their data. And you probably don’t need it all or wouldn’t even use it.

To get things moving, you need to go from the general concept of data sharing with customers and suppliers to the specifics of exactly what data you want and what you are willing to give of value in exchange. As with so many business relationships and business process improvements, it is more likely to happen if you start small.

That means you need to identify exactly what data would be most useful to you. For example, one consumer products brand would love to get the age and gender of the end-consumer from a major retailer. One automobile tire manufacturer would love to get the mileage and end-date of leased cars from a car company. One electronics component manufacturer would love to know the desired new product features of the end-consumer from the smartphone manufacturer. In every company, there are very specific pieces of data that would help complete the puzzle. To go from talk to action, companies must move beyond talking in generalities and get very specific.

You also need to get a clear overview of the algorithms driving your Digital Supply Chain. Taking an inventory of the relevant algorithms is important. For many companies, it is an eye-opening exercise when you see how disconnected they can be. You need to get a good understanding of the value of the data you currently have and what data you need that would optimize the performance of current algorithms.

As you become more sophisticated in your data trading strategy, think about the value of your data to third parties. Think strategically and put yourself in their shoes. Think about what specific pieces of data might help fill a hole in their puzzle. You know what pieces to the data puzzle you’re missing, and you can speculate about the pieces your customer or supplier is missing. We know that companies spend a lot of time and resources on cleaning data. What if you can provide clean data in one very specific area to a customer in exchange for getting a key piece of data that you need? And there may be other things of value other than data that your partners want. For example, they may want an early release of a product or favorable pricing or premier support.

Preparation is critical to effective data trading. We have developed a comprehensive DSCI Data Trading Framework that outlines a process you can follow to unlock the value of data sharing with your value chain partners. The DSCI Data Trading Framework consists of three key stages.

• Prepare: Think through what a customer or supplier may want. But make sure that you have agreement internally about what data you can offer before entering the negotiation. Be crystal clear about what data you need and how often you need it.
• Negotiate: There are specific issues that need to be addressed in data trading negotiations. Be realistic about your needs and actual use.
• Govern: Incorporate controls for data protection and cybersecurity into how you ultimately structure data trading agreements.

Digital Supply Chain transformation has unique challenges, such as getting critical new data from customers and suppliers. Developing a Data Trading Framework can help you obtain the data you need to unlock the potential benefits of the Digital Supply Chain. Another benefit: It helps break down silos and facilitate collaboration and gives you a way to systematically identify, value and acquire the specific data you need.

Remember, transform or fade away.

As I wrote in my last column, 2018 was a banner year for supply chains. Companies across the globe found ways to grow revenue (not just cut costs!) through the digital transformation of their supply chains. Customers demanded more, and expected more, in terms of delivery accuracy, personalization and timing. Automation of routine tasks became commonplace and new technologies, like Artificial Intelligence/Machine Learning (AI/ML) and Blockchain, were deployed.

What can we expect to see in 2019? Will we see more of the same? Are companies picking up speed or losing momentum?

At the Digital Supply Chain Institute, we have worked with nearly 100 companies on Digital Supply Chain issues. In 2018, we collaborated with companies that lead their industry–Lockheed Martin, Dell, Corning, and SAP. We met with smaller companies like Anastasia (a leading Santiago-based AI firm), MVP Workshops (a Belgrade-based Blockchain company), and Chain IQ (a Zurich-based procurement company). And we spent time with innovative companies like Under Armour, Aricent, Colgate-Palmolive and Li & Fung.

This doesn’t mean that we are a foolproof source of truth about the future in general or 2019 in particular, but our work does provide a unique vantage point to assess the currents that are carrying companies forward—and the headwinds that are causing others to falter and lose momentum. One thing is certain: Every company will navigate some, if not all, of these currents in the coming year.

Here is our view of the top five supply chain actions that the best-performing companies will undertake in 2019 to extend their leadership position in the marketplace. Put one or all of them on your list of resolutions for the New Year:

• A massive retooling of the people dimension. Our research shows that deploying a Digital Supply Chain strategy can increase revenue by 10 percent. But getting this done will require a different skill set in the workforce. Companies will need more data scientists and data stewards. We need more people who understand the customer experience and customer choices. And we need a workforce and executive team that makes decisions based on data, not just intuition. In 2019, companies will hire data scientists, acquire data science companies and undertake massive training of the workforce on data-based decision making.
• Unprecedented collaboration with a purpose. Consultants have yapped about collaboration for decades, but now we have a real incentive to change our behavior. Without collaboration within a company (e.g., Marketing and Operations) and without collaboration with suppliers and customers, building a Digital Supply Chain is simply not possible. In 2019, successful companies will work on things that require serious collaboration between companies and departments like “data-trading,” where companies swap proprietary data for data owned by another company. For example, an apparel maker may trade its sales trend data for a retailer’s data about who is actually making the purchase in the store. Companies will also form cross-functional teams—Demand Councils–that use real data to make forecast and planning decisions.
• Widespread use of algorithms. There is nothing more important to a company’s success than building the right algorithms and supporting them with AI/ML technology. Algorithms will make the company smarter every day—and dramatically improve customer satisfaction and thus help them gain market share. The algorithm race is already on and companies will have to address the first two bullet points above to effectively deploy algorithms.
• Step back and dive deep on Blockchain. The pendulum is swinging on Blockchain, once touted as bigger than the Internet, now seen as a disappointment by some. Despite what you’ve heard, Blockchain is not bigger than the Internet. It is not better than all databases and cyber security tools. Except sometimes it is. Companies have wasted money and time conducting supply chain pilot projects without first accessing if Blockchain is appropriate for the task or what return they can expect. None have scaled up. The big focus this year will be for companies to forget the hype, apply common sense and strengthen measurement, accountability and apply Blockchain where it can and will have a big impact on the supply chain.
• Make it personal. Supply chain leaders always want every car to be black and every model to be the same. But in 2019, companies will finally realize the power of personalization. That means supply chain and product development will have to take a segmented approach. For example, a supply chain in some of cases would source, manufacture and deliver products for an individual buyer. In other cases, these “personal” products may actually be aimed at a broader, yet specific segment of consumers.

The five actions above will dominate supply chain playbooks in 2019. Sure, lots of other things will happen too. But you will find companies in your industry (B2B or B2C) making a play on one or more of these five resolutions. Won’t they be surprised when they discover that their customers are flocking to you because you resolved at the start of 2019 to move on all five!

Most people don’t use the word algorithm every day. Many think it refers to lines of code or the latest Diplo beat. Yet, algorithms are ubiquitous and there is an increasing urgency of action around them.

Almost every company in the world realizes the importance of developing algorithms that help them run their business. Algorithms are formulas—sometimes digital, sometimes captured in a spreadsheet–that allow your company to operate smarter and meet customer needs. The best algorithms are proprietary; that is to say that only your company has the formula. They are also backed up by Artificial Intelligence (AI)/Machine Learning (ML) technologies so that they have the capacity to get smarter and make better decisions after each and every transaction.

Most companies recognize that the explosion of data from sensors and intelligent devices and new information from social media and other sources make now the right time to invest in a more comprehensive algorithm strategy. The truth is that most companies have a hard time managing the streams of data that they already have, let alone handling new sources of data. Algorithms are the key to making your current data useful and making smart, timely decisions based on that data possible.

What has been missing thus far is focus on how to manage this critical resource and the assets they produce. Markets will be won by companies that effectively create, manage, and deploy algorithms for everything from customer demand sensing to data cleansing to inventory management! Companies that are faster and smarter at developing and managing algorithms are going to win in industry after industry.

And yet, almost all companies report difficulty in moving ahead for several reasons:

• No one owns algorithms. They exist across business units and functions. No one is setting priorities and deciding where algorithms can make customers the happiest. Few are aligning technology investments against the most important algorithms.
• Algorithms exist in every company. They might not be backed by accurate data. They might not be shared between business units. But they exist and are being used to influence or drive some decisions.
• People know that a more data-based, analytically driven, algorithm supported management process is required. They just want management to be smart about setting priorities and getting algorithms better every day.

It is amazing how much better decisions are when, for example, an algorithm has analyzed the past eight years of purchasing data, ingested the latest social media buzz, and considered customer usage patterns as reported back by a sensor built into the product. Even the most experienced human demand planner with an Excel tool (with macros) can’t compete!

For most companies, developing an organization, culture, and process driven by algorithms requires transformational change. While Google, Amazon, and Uber are great examples of digital natives that create and use algorithms; some of the most interesting work is being done by sector-leading companies such as Dell, Colgate-Palmolive, Under Armour, Li & Fung, Corning and others.

All companies are different. They have different strategies within specific industries, different degrees of automation, and distinctive approaches to their customer. Still, there are a series of Universal Algorithm Action Steps that apply across companies and industries. Here is what can usher in your company’s Golden Age of Algorithms:

• Create an Algorithm Council comprised of representatives from Finance, Supply Chain, Sales, Marketing, IT and HR. Why? Because all game-winning algorithms exist across organizational boundaries, aka silos. The Algorithm Council will prioritize the algorithms and back them up with the necessary technology investment.
• Inventory all existing algorithms and prioritize them. Decide what improvements can be made in investment and focus. It turns out that most companies have a good start on algorithms and data. But not many have managed and invested in the space. Invest, focus and execute the great algorithms that you already have in-house.
• Develop a people strategy that will make all this happen. You are probably missing some data-driven, systematic thinking, algorithm producing people. Go out and hire them, contract for them or acquire them. Now! Sometimes these people are called data-scientists. And train your workforce in algorithm-driven decision-making.

Look at the world’s great supply chain companies like Dell, Colgate-Palmolive, Li & Fung. They continue on this journey toward algorithms that will make their customers not just satisfied, but happy–and keep their businesses expanding and generating the profit that market leaders deserve.

Maybe you should use the word algorithm every day!