1.4 The IT-Enablement Hierarchy

When we call IT the great enabler, what do we mean? There are two sides to this story—what IT does, and what IT doesn’t do.

• What IT Does: IT enables many of today’s best practices in logistics, SCM, and today’s global economy. Simply put, technology, properly used, helps us do things we couldn’t do before the technology emerged to change behaviors and processes.

• What IT Doesn’t Do: Reflect on the word enable. Enable means that IT is a tool to help you create value. IT is not a solution—it is not the answer to your company’s competitive challenges.

Your takeaways: If you don’t use IT well, you won’t be able to build and manage winning processes or a competitive supply chain network. Proper use of IT means you avoid the temptation to view IT as a solution—it isn’t!

Now, let’s talk about how companies invest in IT. Keep this point in mind: Nobody wants to fight tomorrow’s competitive battles with yesterday’s technology. That means technology investment is almost always on management’s radar. Yet, as Figure 1.3 depicts, to get the most out of your investments, you need to use IT to enable four related capabilities.

Level 1: Data

Data are the raw material you use to create information and to derive insight. In the past, you may have struggled to collect needed data. Today, you are overwhelmed by abundant data. In fact, we have a new name for data: big data.

What exactly is big data? The gurus define big data using the 5V’s (see Figure 1.4).1

1. Volume refers to the huge amounts of data that are produced every day in our modern, interconnected, “Internet of Things” world.

2. Velocity recognizes that new data is generated at an incredible speed and should be analyzed equally as quickly.

3. Variety acknowledges that diverse types of data come from a wide array of sources.

4. Veracity is the notion that you can trust the data (i.e., it is authentic, credible, and can be used to make great decisions).

5. Value refers to managers’ ability to use the data to create value. Managers want to know they are getting business value from their investments.

Why is big data so important? Answer: You can use the gargantuan quantities of data generated by smart machines, barcodes, radio frequency identification (RFID), electronic sensors, click-through counts on the internet, social media content, and mobile devices to better understand customers, products, and processes. That is, you can harvest this data and use it to model human decision-making and operating system behavior.2

Now, a key question: Where is this data stored? Increasingly, your company’s critical data is stored in your ERP’s relational database.

Level 2: Information

Data has value—or worth—when it becomes information that you can use to make decisions. Can you see the role of ERP and the suite of functional applications here? Many modules (e.g., purchasing suites) increasingly include data analytic software to help you model data and make decisions. How are companies turning data into decisions? Consider the following.

Hidden Correlations

You can use big data to find and understand unique relationships among the variables you are tracking.3 When you better understand important correlations, you can make better decisions.

Customer Behavior

You can track customer behavior by tracking every purchase a customer makes. As the data accumulates, you can build a customer profile. And if the person is shopping on the internet, you can track every click as well as how long a customer stays on each page. What do you do with this data? You build a customer profile to help predict the customer's behavior.

You can also link the data you collect to secondary data sources such as census numbers, Nielsen demographics, or weather statistics. Such linkages can help you understand customer behavior on a community-by-community basis, enabling you to tailor products or promotions to specific customers. In the past, marketers could only dream about such customization capabilities.

Managing Processes

You can employ artificial intelligence to make sense of data to help you manage processes. Here are three examples:

1. Microsoft established control towers supported by machine learning to help manage the production of Xbox gaming consoles. The system reports quality issues/trends to engineers and tracks how they respond. As the system identifies a consistent managerial response to a specific problem, it learns and begins to make the decisions itself, freeing up engineers to work on less repetitive decisions.

2. Amazon relied on computer vision and artificial intelligence to develop its Amazon Go cashierless stores. Amazon Go stores use cameras, sensors, and AI to track the products that customers take off the shelves, automatically charging their accounts when they walk out the door.

3. Tyson Foods turned to computer vision and machine learning to automate inventory management. Inventory accuracy increased to the high-90 percent range, a 20 percent improvement over the manual process. The result: improved product freshness and reduced stockouts. The computer-vision system can also detect foreign objects, enhancing food safety.4

To really make sense of and leverage data, you need to learn to work closely with geeks called data scientists. Unfortunately, data scientists are in short supply. That's one reason why the median annual starting salary for a data scientist is $95,000.5 As companies turn to big data and AI, demand for data scientists will continue to boom. It's a great time for supply chain managers to add data science skills to their decision-making toolkits.

Level 3: Knowledge

Knowledge as an IT-enabled capability refers to your ability to tap into the experience and insight of your entire organization. This is the goal of knowledge management systems (KMS). 3M and Procter & Gamble set the standard for knowledge management.

• 3M Brings Employees Together: 3M employed a knowledge management system (KMS) to help employees find the right talent to develop product ideas. How does this work? A 3M employee—who also happened to be an avid fly fisherman—became frustrated by the sinking properties of existing fly lines. He used 3M’s KMS to find the right polymer expert. A good idea became a great product because a KMS helped bring the right know-how together. 3M’s Scientific Angler brand became a leader in the fly fishing market. 3M has also taken knowledge management to the internet, conducting a web-based forum “Innovation Live” experiment. The objective: Capture ideas for markets of the future. Over 1,200 3Mers from 40 countries participated, generating 736 ideas. Nine untapped new markets were identified.6

• P&G Brings the Supply Chain Together: P&G established “Connect + Develop” to take crowdsourcing/open innovation to its entire supply chain. The result: In only a half dozen years, P&G almost quadrupled the number of new product ideas that came from outside the company—from 15 percent to over 50 percent. Now, a key fact: P&G doubled its innovation success rate despite reducing R&D investment by 30 percent.7

Knowledge management has become a core feature—and benefit—of modern ERP systems.

Level 4: Wisdom

Wisdom is the ability to spur organizational learning and is the rarest form of IT enablement. Ask yourself: “How much time does it take to share a good idea (e.g., process or product improvement) across your entire organization?” One of Walmart’s secret growth drivers has been its ability to outlearn its rivals. Consider the following three examples:

1. A Walmart associate observes that Hispanic customers are asking for a specific kind of cookware known as a caldero. She shares this insight during the morning meeting. Calderos are soon on the shelf.

2. A furniture display at Sam’s Club fails, endangering customers. A worker identifies the problem, creates a solution, and within the workday, modifications are made to the display at every Sam’s Club worldwide.

3. A customer shared the following:

   I telephoned the Bentonville, Arkansas, headquarters of Walmart to complain about its store in La Plata, Argentina. The switchboard immediately rang the vice president of international operations, who picked up his own phone. He thanked me for calling, asked detailed questions about my dissatisfaction, and inquired whether or not I was willing to repeat my story for his Latin American VP. He transferred me straight away, and an even more detailed conversation followed. Then I was asked if I would be willing to talk with the Argentinian store manager if he called me. Ten minutes later, my phone in Connecticut rang. On my next trip to Argentina, a year later, the store had been transformed. No wonder Walmart is the world’s largest retailer.

What is Walmart’s “secret” formula? That is, what is your key to building a wisdom capability?

Observe + Ask + Analyze + Act = Organizational Learning

Note that observe, ask, and act are human skills that are either unleashed or held captive by your organizational culture. Of course, IT can promote more active observing and asking. Analyze, however, is where IT can help you rewrite the competitive rules. Analyze is where “big data” and AI, especially machine learning, can make a big impact. Leading ERP providers like Oracle and SAP are now touting their systems’ emerging and evolving AI capabilities.

The bottom line: At each level of the hierarchy, IT and ERP systems help you do your job, which is to make decisions that leverage resources to create value.