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Operations Strategy Empowering AI Leadership

Contents

Introduction | Examples | Responsibilities | Oversight | Agenda | Resources | Endnotes

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Introduction

Artificial intelligence (AI) is important for many reasons, but at the root of them all is this: AI can radically transform how work gets done. Companies have used AI to re-engineer processes in nearly every business and government function – sales, marketing, customer service and fraud detection; manufacturing, resource exploration and research and development; IT, human resources, finance and security. AI is giving strategy-makers new means to achieve differentiation and market penetration, and managers new ways to improve productivity and performance. But AI also raises customer expectations and obliges every employee and leader to use its powers responsibly. AI-enabled processes that use biased data and algorithms that are not fit for purpose will destroy value and reputation, not enhance it.

Companies are using AI to:

  • Create new processes that are exponentially faster and higher-performing than the ones they replace. Companies are already using AI to speed up and improve process performance by between 200% and 1000%.[1] And, since AI systems can learn, processes based on AI continually improve. As AI gets better at identifying patterns, predictions of customer preferences and equipment breakdowns grow more accurate, recognition of the images, sounds and signs of fraud exceed human capabilities, and quality issues in manufacturing and data processing are identified, repaired and prevented more quickly. AI is already being used to predict maintenance and customer needs, clean data, improve product quality, classify incoming emails and forms, answer questions in chat conversations, reduce electricity use and identify tumours. These operational improvements can lead to higher customer satisfaction, lower operating costs and environmentally friendlier operations.
  • Do work that wasn’t previously possible or practical. AI is giving companies capabilities they lacked or could not afford. It is providing vehicles and drones with the ability to operate themselves with no or minimal human intervention. Researchers are discovering new medical treatments and chemical compounds, or new uses for old ones, using AI to discover patterns in vast amounts of scientific data. AI tools are aiding innovation, too. Product designers are arriving at previously unimagined concepts through the use of new processes – drawing on AI to generate hundreds or thousands of design options that meet product requirements. Also, by using clouds to deliver AI services, the cost of AI has become affordable for many more businesses.[2]
  • Improve productivity and reduce costs by augmenting and automating work. AI can automate routine, repeatable and predictable work. But companies receive even more value when AI helps people do more of, and be better at, what they do better than machines: leading and managing organizations, finding solutions to new, difficult and irregular problems, doing creative work, making recommendations, and bringing human insight, empathy and ethical sensitivity to their job. For example, car manufacturers in pursuit of flexible assembly lines that can easily personalize cars, or switch between models, are using a new generation of AI-enabled “cobots” that assist workers. Rather than eliminating assembly-line jobs, these companies hired more workers.[3]

Dramatic process improvements, innovative new processes and novel AI-augmented ways of working make new strategies possible. Reducing operating costs with AI frees up cash to fund the transformation needed to pursue those strategies.[4] It’s the job of management, not the board, to use AI to transform operations and build a better operating model. But it falls under the board’s oversight responsibility to ensure management is performing its role well. Boards should see that AI is being applied to the tasks that matter to strategy, and that management is making wise, ethical and legal choices about the AI algorithms and models it deploys, the data it uses and the way it operates AI-enabled processes.

Figure 1: AI has the potential to transform organizations by providing new opportunities for process innovation.

Examples

Crédit Mutuel

Crédit Mutuel’s advisers previously received 350,000 emails a day related to enquiries such as loan options or insurance coverage. It has now embedded AI solutions across all of its business lines to better serve the bank’s 12 million customers. These solutions assist 20,000 Crédit Mutuel advisers in 5,000 branches and agencies by identifying frequent requests, determining the level of urgency, and responding quickly and accurately. This saves 200,000 working days annually, which are then reassigned towards training, upgrading advisers' skills and expanding sales activities. The bank is also better equipped to manage issues such as anti-money laundering and the financing of terrorism, with tighter controls and monitoring.

Kone

Kone, a lift manufacturer headquartered in Finland, has connected an internet of things (IoT) cloud platform to lifts, escalators and automated doors. The company uses AI and advanced analytics to predict its maintenance requirements, and to suggest resolutions to potential problems. This means less downtime, fewer faults and more detailed information for maintenance crews about the performance and usage of equipment. For people who use lifts and escalators, it means less waiting time, fewer delays and the potential for new, personalized experiences.

Toshiba

In Taiwan, where there is a shortage of doctors, caregivers can efficiently provide at-risk patients suffering from heart conditions with wearable devices made by Toshiba Electronics Taiwan Corporation, a subsidiary of Toshiba, Japan. Using AI and the IoT, biometric sensors in the devices collect a constant stream of data, such as heart rate and blood-oxygen levels. Trained to read and interpret patterns in this data, the cognitive solution can distinguish between healthy and abnormal patterns with increasing accuracy. In the event of abnormal readings, the system raises an alert to help patients and caregivers take preventive action. The devices provide Toshiba with a new market – consumer health and wellness – and a subscription-based revenue stream.

Responsibilities

While the G20/OECD Principles of Corporate Governance do not specify operations and process improvement in their list of responsibilities, boards cannot carry out their oversight duties without considering how their companies use and manage technology and management’s major technology plans, investments and partnerships.

Many responsibilities that apply to other modules pertain to operations and processes:

  • To act in good faith, with due diligence and care, boards should be fully informed about plans for applying AI in strategy, AI’s alignment with core values and ethical standards, the risks associated with AI strategy, and regulations affecting the use of AI. Directors should have access to accurate, relevant and timely information.
  • To oversee corporate strategy, major plans of actions, risk management, and budgets and business plans, boards should review and guide management’s vision, goals, actions and expenditures for AI, its support for innovation and the use of new AI resources, management’s awareness and plans for legal compliance and ameliorating AI risk, and competitors’ use and plans for AI.
  • To oversee corporate performance, expenditures and acquisitions, boards should review and guide AI’s alignment with strategy, shareholder values, ethics, performance and risk indicators, implementation of AI plans, the effectiveness of AI to accelerate processes and improve productivity, major investments in AI systems and talent, and acquisitions.

To carry out these responsibilities, boards should also review and guide these technology-specific concerns:

Act in good faith, with due diligence and care.

Directors should:

  • Be fully informed about their company’s and competitors’ use of AI for process innovation, cost reduction and new competencies.
  • Learn about the implications of these new processes for skill requirements and jobs.
  • Be fully informed about the adoption of AI in their environment and the demands and expectations important partners will place on their company.
Oversee corporate strategy, major plans of actions, risk management, and budgets and business plans.

Directors should know:

  • Whether management is developing strategies that take advantage of the new capabilities AI can bring to business processes.
  • Whether investments in AI for operational transformations target important business outcomes and not only operational improvements with little impact on the top or bottom line.
  • How the enterprise’s acquisitions and partnerships affect its ability to use AI to advance its strategy, and whether they introduce new risks.
  • Whether processes using AI have identified bias and other ethical risks when AI is applied to business processes, and whether the plans of action include measures to address them.
Oversee corporate performance, expenditures and acquisitions.

Directors should know:

  • What progress the company is making in applying AI to processes that differentiate their company from competitors.
  • Whether management is building the resources needed to implement and operate AI-enabled process change.
  • Whether, and how, AI should be factored into performance objectives for management.
  • Whether key performance indicators (KPIs) and key risk indicators (KRIs) for business processes are aligned to the AI-enabled strategy.
  • How the innovation process using AI is being encouraged across the organization.
  • Whether the data used to train and operate AI systems is being properly managed.
  • How internal control processes are reported to the board (pp. 58/66, principle D7).
  • How to monitor and manage potential conflicts of interest of management, board members and shareholders, including misuse of corporate assets and abuse in related party transactions (pp. 57/66, principle D6).

The analysis in this section is based on general principles of corporate governance, including the G20/OECD Principles of Corporate Governance, 2015. It does not constitute legal advice and is not intended to address the specific legal requirements of any jurisdiction or regulatory regime. Boards are encouraged to consult with their legal advisers in determining how best to apply the principles discussed in this module to their company.

Oversight

This section includes three tools to help directors oversee management as it uses AI for process innovation and creating new operating models for the company.

The knowledge management tool helps board members assess whether they possess, or have access to, the knowledge required to independently judge management’s actions on using AI to improve processes.

View Appendix 1 for the knowledge assessment tool here

The performance review tool consists of questions boards can ask management about their knowledge of AI and process innovation, and the progress and performance of their actions. It offers the SCEPTIC framework to help directors assess the answers they receive.

View Appendix 2 for the performance review tool here

The guidance tool offers possible actions by the board in an “If, then” format.

View Appendix 3 for the guidance tool here

Agenda

The following suggestions can help the individual who prepares the board discussion and sets the agenda on process and operating model innovation through AI.

Before leading the first meeting

  • Prepare yourself: Become familiar with AI, what it can do today to transform processes, and what it will be able to do in the future as the field advances. Separate the hype from reality by looking at the research and the sources behind the claims, and the issues that complicate the implementation of the technology. The resources section provides readings about AI and process improvement. Speak to senior IT, security and public affairs executives about any ethics issues on their minds.
  • Gauge board member interest in AI and process innovation: Speak to other board members. Learn what importance they place on AI and the concerns they have about planned AI investments and partnerships. Identify the board members who are most interested in moving forward with new AI investments, and those who have concerns or lack interest.
  • Set goals: Think ahead about the desired outcomes from the board discussion.

Set the initial agenda

Create a strategy for process innovation pilots. Agenda items can include:

  • Presentation: Arrange for a briefing on how AI is being used to transform or improve the organization’s most important processes for generating revenues and serving customers. The presentation can include examples from competitors and potential use cases uncovered by researchers. They should also include revenue and other quantified benefits when possible. The presentation should also introduce major risks and responsibilities that the company will have to manage, and the requirements that must be met to run AI, such as the data for training AI systems.
  • Discussion: Identify processes that are good candidates for pilots, based on: high potential value; availability of data; ability to implement and scale up if successful.
  • Delegate: Decide which members of the executive team will be responsible for selecting and running the pilots as well as deciding what support is needed (technology, development platforms, innovation sandboxes etc.).
  • Engage: Decide how the board will stay current with developments in process innovation.

Set follow-up or alternative agenda items. These can include:

  • Innovation and experimentation: Discuss how the company is developing a culture that supports innovation with AI. This conversation can enquire about rewarding risk-taking, incentives, creation of innovation centres, office design and corporate values.
  • AI in the ecosystem: Examine how AI will change the way companies work together within the supply chain, and what companies expect from suppliers. The discussion can include how AI can shift the bargaining power and the position of companies inside an ecosystem.
  • The operating model of the future: Envision the new ways, end-to-end, in which the company gets work done, the new capabilities and cost structure this provides to the company, and how the new operating model supports or enables new business strategies.
  • AI in R&D: Discuss how AI can be used to aid scientific researchers, product developers, competitive intelligence and market analysis, and the next steps.
  • Future of work: Look at the new skills and roles the company will need to make AI process transformation a reality, and how the company will migrate to them. This can also include changing how employees work by providing them with AI tools.

Resources

(All links as of 2/8/19)

Books

  • Michael L. George Sr, Dan Blackwell, Michael L. George Jr, Dinesh Rajan, “Lean Six Sigma in the Age of Artificial Intelligence: Harnessing the Power of the Fourth Industrial Revolution”, McGraw-Hill Education, 2019.
  • Paul R. Daugherty and H. James Wilson, “Human + Machine: Reimaging Work in the Age of AI”, Harvard Business Review Press, 2018.

Reports

Articles

Endnotes

(All links as of 2/8/19)

Other modules:

Home | Audit | Brand Strategy | Competitive Strategy | Customer Strategy | Cybersecurity | Ethics | Governance | Operations Strategy | People and Culture | Responsibility | Risk | Sustainable Development | Technology Strategy | Glossary