AI and the Need for Speed

Artificial intelligence (AI) holds substantial promise for organizations to reduce costs and increase quality, but how AI affects organizations’ use of and relationship to time — in reacting, managing, and learning — may be the most jarring.

Certainly costs and quality changes are nontrivial:

  • After initial development, AI-based systems may substantially reduce variable costs. Organizations can replace or increase productivity of expensive knowledge workers as AI supplants many tasks. With AI, a thousand radiologists cost the same as one. With AI, each customer can have his or her own customer service representative. Currently expensive bottlenecks may dissipate.
  • With machinelike precision (pun intended), decision making can be consistent. Without those pesky humans adding entropy, processes can work the same every time. Each of the AI radiologists performs exactly the same as the others, reaching the same diagnosis. Each AI customer service representative recommends the same resolution. And with this uniformity in place, organizations can incrementally refine and improve, ever increasing quality.

But while costs and quality are important, improved AI also heralds changes to a fundamental business limitation — time. For example:

  • Current mortgage approval processes typically take 30-45 days. “Getting a loan, even a preapproval, doesn’t happen overnight.” Why couldn’t it happen overnight? With data increasingly available to support all the information that goes into a loan application, AI approaches may be able to dramatically reduce the time required to get a loan. If you find a house you like in the morning, the mortgage application process doesn’t need to be the holdup to getting the keys that afternoon. Mortgage brokers (if they continue to exist) will simply need to be able to swipe credit cards.
  • Lawsuits can take considerable time to resolve. On average, doctors spend nearly 11% of their careers with an unresolved malpractice claim. Some of the time is in gathering data. Some is in delays due to court congestion. Some is due to deliberation and settlement. How much of this could be shortened with AI reducing discovery and decision-making time?
  • Medical diagnosis itself can also take substantial time during which the patient is not being treated. In primary care settings, the diagnosis of childhood cancers can be difficult, particularly due to the low incidence rate; but “shorter lag time could improve the prognosis, and … prolongation of the diagnosis period will badly affect the prognosis.” The potential for improved health outcomes through faster diagnosis is undeniably appealing.

Improvements in speed through AI have the potential for both monetary (e.g., worker time) and nonmonetary (e.g., customer satisfaction, reduced anxiety, improved health) benefits.

However, my sense is that most organizations are used to current timings and aren’t ready for them to change substantially. As the pace begins to increase, what do organizations need to watch out for?

  • Too fast to manage: The pace of current processes allows time for monitoring and management. If (when!) something doesn’t work as expected, there is usually still time to correct and manage the process and outcomes. But human managers may not have time to manage at a machine pace. They may not have the opportunity to intervene before the money is gone from a risky loan, the guilty walk away, or the patient suffers from incorrect treatment. In the race to optimal speed, the breakneck pace may reward risky behavior as organizations excel — until they crash. A breakneck pace is called “breakneck” for a reason.
  • Too fast to react: In an ideal competitive scenario, your organization will be able to use AI to be fast, while competitors remain slower. However, it won’t likely work out that way. Competitors won’t sit still. As you are building AI based on the environment from yesterday, your AI systems will have to compete with the competitive environment of today. The potential for rapid change by others in the environment may prevent processes from settling down into a steady state.
  • Too fast to learn: Much of the improvement in AI in the last decade stems from a transition from a rule-based approach to a data-based approach. Instead of coding rules for all expected scenarios, AI models are trained on data and learn from observing. But in an increasingly AI world, the value of data may decay quickly. The rate of decay may exceed the rate at which new data is available or the AI model can ingest it. The Netflix prize is a classic example; the company offered a prize for a substantial improvement in its algorithm that recommends movies based on historical customer data. After awarding the prize, Netflix found the algorithm was not as useful on their current data — their historical data on DVD-by-mail rentals was much less useful in understanding video streaming behavior. When AI depends on data, the rapid decay of that data may be debilitating.


MIT Sloan Management Review

Do You Diagnose What Goes Right?

“Is it the shoes?”

That’s the question director Spike Lee ponders in a classic series of Nike Air Jordan commercials in the late 1980s and early 1990s in which Lee, playing the fictional Mars Blackmon, considers the mysteries behind the gravity-defying greatness of basketball player Michael Jordan.

And thus Lee points to one of the most persistent, frustrating, and important questions a manager faces: “Is it the person, the tools, or the process?”

Sadly, we are usually asking the question in the negative: Is this thing that went wrong the person’s fault, the tool’s fault, or the process’s fault? Or, more likely, how much of it was the person versus the tool versus the process?

Humans are difficult that way. It’s hard enough to understand what makes one of us tick when we are alone in an empty room. Give us a hammer and a project plan, and the possible causes for a failure become infinite. Then cloud the analysis in a haze of pressure and disappointment, and the barriers to arriving at clear answers become that much greater.

Of course, organizations need to be up for the challenge; when things go awry, we have a responsibility to diagnose the causes. But we may find that answering the question, “What went wrong?” becomes just a little easier if we have already addressed a different question: “What goes right — and why?”

Think of a process in your organization that works well, the first thing that comes to mind. For me, it’s the production of digital content for the MIT SMR website. Our digital-production value chain includes up to seven different human beings, five different tools, and up to 15 different process steps. Time to market for an individual piece of content can range from as few as three days to stretching over several months. It works well. And, shame on me, I’d never thought to ask why.

But analyze it I now have, and here is what I have learned.

First, the process is mostly transparent. We plan a pipeline of content that is stored in a document accessible by the key participants. We track each content item’s progress on a shared project management platform. The few times we encounter bumps, a lack of information sharing is almost always at fault.

Second, our processes are well-documented. Each step in the digital publishing chain is well-understood by all participants and is easy to follow.

Third, we are using tools that fit the process. We employ a combination of spreadsheets, project management software, and editing and web publishing tools that address our digital publishing requirements. The tools are lightweight and flexible.

Fourth, we understand and respect the interdependencies. All participants are clear on their role in the process and how the ways they carry out their role impacts others.

Fifth, it is essentially leaderless. Our digital production chain operates as a bucket brigade in which all participants have equal footing.

Sixth, the talents, attitudes, and communication styles of each participant is suited to our role in the process. To borrow a concept from the management author Jim Collins, we have the right people on the bus, and they are sitting in the right seats. A successful digital publishing process requires a specific combination of technical abilities, yes — but also a commitment to cooperate, to flex when needed, to solve problems on the fly, and to communicate actively. We are lucky to have a team in which such attributes are in abundance.

My analysis is unscientific, incomplete, and perhaps even obvious. But the six drivers I have identified give me a starting point to understand successful processes in my organization. More so, I have made it a priority to identify and understand the components of process success rather than waiting to dissect a failure. And only more good can come from that.

No, Mars, it’s not the shoes.

Paul Michelman
Editor in Chief
MIT Sloan Management Review


MIT Sloan Management Review

Revisiting the Logic of Being Global

For more than 30 years, multinational corporations were in a special class, distinguishing themselves in key areas such as financial performance, productivity, and overall influence. Lately, however, large global companies have come under increasing scrutiny and are being viewed as sources of inequality. In recent months, several companies, including United Technologies Corp., have been berated by U.S. President Donald Trump for plans to move jobs out of the country. Others, including Apple Inc., have been criticized for holding billions of dollars of profits in foreign tax havens.

The state of the multinational and how “the world is losing its taste for global businesses” is the subject of a recent cover story in The Economist titled “The Retreat of the Global Company.” In the decades of the 1990s and 2000s, there was a compelling logic to multinational corporations based on scale and efficiency. Instead of conducting all of their activities in one country, companies made the most of global supply chains, produced products where profits were greatest, and minimized their tax bills. But for many multinationals, the article notes, the case for global integration has been hurt by falling profits, lower returns on capital, and increasing pressures from governments looking to protect local jobs and tax revenue. Even China, which has welcomed global investment for many years, is changing its tune. Although some 30% of its industrial output and 50% of its exports have been coming from multinational subsidiaries or joint ventures, it is now pushing for greater amounts of local sourcing and control.

The Economist says that 40% of all large multinationals have returns on equity of less than 10%. There are exceptions: top-tier technology companies (such as Apple) and corporations with strong consumer brands (such as Unilever and Procter & Gamble Co.). But for others, the headaches of being global are intensifying. Indeed, in most sectors domestic peer companies are growing faster than multinationals.

How global businesses will morph their organizations, and what the new configurations will look like remains unclear, the article says. But in the meantime, companies such as General Electric Co. and Siemens AG are establishing supply chains and production facilities that focus primarily on national versus global markets. Other companies are investing in brand development and minimizing physical assets. How the changes play out over time for workers, investors, and consumers is an open question.


MIT Sloan Management Review

Embracing a Strategic Paradox

The writer F. Scott Fitzgerald once observed, “The test of a first-rate intelligence is the ability to hold two opposed ideas in mind at the same time, and still retain the ability to function.”

But within a business, opposing ideas typically lead to conflict, and in the face of conflicting demands, managers will feel anxiety, stress, and frustration. However, our research at Aeon Co. Ltd., one of Japan’s largest retailers, suggests that a positive approach to handling conflicts between opposing ideas can create new value for a company.

Like many retailers, Aeon faces a built-in conflict in its operations. On the one hand, managers in local stores want to adapt their stock to meet local communities’ preferences and needs. On the other hand, the executive team at Aeon’s national headquarters in Chiba, Japan, strives for greater economies of scale.

In many organizations, this kind of conflict tends to be resolved on the steamroller principle, with one side or the other eventually giving way. But Aeon operates differently. Rather than simply cope with the tension, Aeon considers the conflict to be an opportunity to invent fresh solutions that add value to the whole company.

This might sound like a recipe for gridlock, but Aeon handles these disputes so well that top executives say they would actually like to have more of them. “We would like to see more competition between the two sides [stores and regional headquarters on one hand and the national headquarters on the other],” one senior manager at Aeon’s human resources department told us.

In our research, which included 46 interviews with managers at every level of the organization, we found that Aeon uses these local versus national conflicts as an opportunity to invent creative solutions that satisfy both local and national objectives. Two examples illustrate how this process works.

At a store in a Japanese ski resort community, the manager was puzzled by weak sales. The head office had mandated that her store sell a staid collection of clothes that fit the urban stereotype of what rural women wanted, but the sales were not meeting her expectations. When she looked into why, she discovered that the women in her region were actually interested in trendier, yet still not urban, fashions. She proposed a new women’s boutique based on an up-to-date, soft-color, natural-look concept. Initially, managers at both the regional and national headquarters opposed the idea, as the creation of such a boutique for local taste would likely reduce the floor space allocated for Aeon’s national collections. However, after a series of meetings, these managers gradually became supportive of her proposal, as they came to believe that deeper localization would likely boost traffic to the store and boost sales of their core products. The proposed boutique was created at the store and proved a great success.

Other times, the tension focuses on the supply rather than the demand side, such as when figuring out how to bring a local product to a national audience. The story of the Le Lectier pear is one case in point. Niigata prefecture is known as the Japanese home of a special pear, the smooth and aromatic Le Lectier, a highly valued fruit often given as a gift (the pears, packaged in an attractive box of three, can sell for around $ 50). The local Le Lectier farmers wanted to find a commercial use for pears that were too small, oddly shaped, or too scarred to be suitable as a pricey gift, but the relatively small amount of leftover fruit that they grew made it difficult to think of a product that could achieve a national scale. After many meetings between the local farmers, Aeon’s Niigata office, the regional headquarters, and top managers from national headquarters, they came up with the idea of a light alcohol drink flavored with 3% Niigata Le Lectier juice, which they branded “Niigata Le Lectier cocktail.” This solution satisfied Aeon’s historic commitment to “locally rooted retailing” and yielded a popular new product that met its scale requirement.

As these examples suggest, Aeon doesn’t always resolve these challenges in the same way. Some innovative solutions aim for more localization (as in the ski town’s fashion boutique), others for chain-wide products that use a local ingredient (as in the development of the Niigata Le Lectier cocktail). Some are led by one particular layer of management, while others develop through collaboration among the headquarters, regional headquarters, and local stores (as in the Le Lectier drinks). But in each case, managers solve the problem not by trying to ignore tensions but by acknowledging the needs of each side. They see the conflict not as an impasse but an opportunity — a set of constraints that spurs creativity.

Aeon does this by nurturing a culture that emphasizes the importance of each strategic mandate. At the national headquarters, managers are taught to focus largely on strategies that can help the entire network. Local managers, meanwhile, are trained to look for ways to meet the needs of the community and customers they serve in addition to implementing the instructions of the regional managers. Finally, the regional managers’ responsibility includes listening to both the national and local managers’ proposals, trying to understand where those demands conflict, and working through new approaches to overcome those conflicts. In addition, the people in these different layers spend time getting to know each other. Executives say this creates a social glue that helps keep the different managerial layers working together as a team despite the inevitable disputes.

The strategy of trying to reconcile opposing views isn’t a new one for the retailer. Aeon began as a family business in 1758. Founder Sozaemon Okada traded kimono fabrics and accessories in accordance with the beliefs of a group of fellow merchants (known as the Ohmi merchants) who had developed a philosophical idea of how a merchant should behave. Their theory consisted of three precepts, which don’t sound very different from contemporary ideas about sustainable business: A merchant should be good to his customers, good to his community, and good to his own company. The concept remains an important enough part of Aeon’s cultural DNA that even today, new employees are given a manga comic book that talks about the importance of being fair to every stakeholder.

Creating solutions that meet conflicting needs can do more than resolve a political dilemma. Because they are built with Aeon’s unique blend of local and national capabilities in mind, the complexity of the solutions often deters imitation. The consensus solution, whether it involves designing stylish clothes for women living in a Japanese ski village or finding a way to turn a tiny available quantity of pears into a national product, tends to be one that can be executed well by Aeon but not easily copied by anyone else.

Of course, resolving these conflicts requires ongoing work. Managing this built-in strategic paradox of pursuing both localization and nationwide standardization demands the continual attention of management. To keep the atmosphere positive, Aeon’s top management, including the CEO, frequently communicate their commitment to their dual strategy to managers at each level of the organization. Each side is encouraged to feel free to make a proposal and equally free to counter an idea with a different concept. Even when a temptingly simple one-sided solution seems plausible, Aeon’s managers find that wrestling with the problem until a solution emerges that satisfies everyone results in a better outcome. As one executive told us, “The greater the tension, the better the action.”


MIT Sloan Management Review

It Takes More Than Math to Design a Distribution Network

Distribution networks are the conduits that connect companies with their customers, so it is hardly surprising that the way these networks are designed has a critical impact on cost and customer service.

Companies commonly use mathematical optimization models to arrive at the best network design, but this approach is flawed in one key respect — it does not take into account changing market conditions during the several years it can take to complete a design project. This is particularly onerous in developing economies where markets tend to be extremely changeable.

Research carried out at the Malaysia Institute for Supply Chain Innovation (MISI) shows that supplementing mathematical models with analyses of external variables enables companies to develop the most efficient distribution networks. The research work was completed in collaboration with a leading Asian chemical manufacturer as part of a thesis project for the MIT-Malaysia Master of Science in Supply Chain Management.

Outdated models

Distribution network designs specify the locations of warehouses and how much product is allocated to each facility. A chemical company typically manufactures product in large plants to lower production costs by exploiting economies of scale. Product is shipped to numerous customer locations. The design of its distribution network, therefore, determines the total cost of delivering products to meet customer demand while maintaining the appropriate service levels.

There are many ways to configure a network to meet these goals. For example, a company can reduce its inventory holding cost by risk-pooling the inventory in a few warehouses. However, this option incurs higher transportation costs and longer lead times. Alternatively, a company could become extremely responsive to demand by stocking inventory in many warehouses. But such a strategy requires higher inventory volumes and hence higher carrying costs.

Mathematical models can be used to find the optimal solution, but this might not reflect real-world demands. External factors such as regional product demand, commercial real estate prices, and transportation costs can change markedly over the three- to five-year planning horizon that is common for these design projects.

Four-Stage Approach

The MISI research project tackled this problem in four steps.

First, an optimization model was designed to minimize total costs including the costs associated with transporting product, opening and closing warehouses in different locations, fixed warehouse operations, and maintaining inventory. The key consideration was deciding how many warehouses the company should support, and which time periods the facilities should operate within. The model also complied with various constraints such as the need to meet minimum safety stock levels.

Second, the researchers developed an exhaustive list of uncertainties that have a critical impact on the efficiency of distribution networks. Four business and macroeconomic factors were particularly relevant for the manufacturer’s operations: demand growth, oil price fluctuations, shifts in industrial real estate prices, and interest rate changes.

Third, we calculated a plausible range of values for each of these four macroeconomic factors over the planning horizon. The ranges were derived from an extensive search of industry forecasts and reports as well as expert opinion. Using these values, we ran the optimization model to create multiple scenarios based on market conditions driven by the macroeconomic factors. And we identified the optimal network design for each scenario using the mathematical optimization model. For each network design, the cost difference between each given scenario and its optimal version was calculated (known as the “regret”).

Finally, a comparison of the optimal designs — which specify which distribution centers should be operated in each period over the planning horizon — for the different scenarios suggested that one variable had the most impact on performance: the price of oil. A more detailed analysis of oil price effects was carried out.

When deciding which network design to adopt, the chemical company should look at the ones that minimize the regret for the different future scenarios.

Real-World Insights

This approach helps companies to design distribution networks that are aligned with real-world market conditions in two important ways:

  • It enhances quantitative mathematical models by considering a broad range of qualitative variables, employing techniques borrowed from scenario planning. The methodology provides a clearer picture of how a distribution network design might perform. Companies can focus on the key major environmental factors affecting the robustness of a network configuration, under various quantitative scenarios.
  • By using this approach, it is also possible to get a sense of which distribution scenarios are the most relevant, given the market changes that affect the way a network performs. It is possible to represent which of the scenarios considered are most likely to occur — a valuable insight for managers who are striving to develop the most efficient channels for distributing product to customers.


MIT Sloan Management Review