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Optimize for Both Social and Business Value

Building resilient businesses, industries, and societies

As we approach a new decade, we are also approaching a tipping point for business, with new benchmarks for what constitutes a good company, a good investment, and a good leader. The defining expectation: good companies and investments will deliver competitive financial returns while helping society meet its biggest challenges, and in so doing will enable sustainable business.

Leaders with foresight and courage will use this dynamic to create new opportunities for growth, sustained returns for shareholders, and greater societal impact. To do this, they will need to think in new ways, create new modes of competitive advantage, pursue deep and broad business model innovation, and engage strategically with ecosystems. They must merge the two currently disconnected uses of the “S-word” in business: sustainability and sustainable competitive advantage.

The implications for companies, capital, and capitalism are profound. Here, we share our take on the emerging era of business value, and the CEO agenda for value and the common good.

Why Is Corporate Capitalism at a Tipping Point?

Stakeholders are beginning to pressure companies and investors to go beyond financial returns and take a more holistic view of their impact on society. This should not surprise us. After all, we have lived through two decades of hyper-transformation, during which rapidly evolving digital technologies, globalization, and massive investment flows have stressed and reshaped every aspect of business and society.

As in previous transformations, the winners created new dimensions of competition and built innovative business models that increased returns for shareholders. Many others found their businesses at risk of being disrupted, with familiar formulas no longer working. To meet the unwavering demands of Wall Street, many companies relentlessly optimized operating models, streamlined and concentrated supply chains, and specialized their assets and teams—leaving them less resilient and less adaptable to shifting markets and trade flows. The resulting waves of corporate restructuring, consolidation, and repositioning have fractured companies’ cultures and undermined their social contracts.

Furthermore, this hyper-transformation cascaded beyond individual companies and created socio-economic dynamics that left many people and communities economically disadvantaged and politically polarized. Combined with the increasing shared anxiety that the earth’s climate is changing faster than the planet can adapt, a global zeitgeist of risk and insecurity has emerged. We will enter the 2020s with more citizens, investors, and leaders convinced that the way business, capital, and government work must change—and change quickly.

We now must rethink the sustainability of the whole system in the face of extreme externalities—or risk losing social and political permission for further progress. The 2030 UN Sustainable Development Goals (SDGs) identify the moral and existential threats that we must meet head-on. While some question the SDGs’ breadth and timeline, most agree that, if achieved, they would create a more just, inclusive, and sustainable world. Goal 17 calls for new engagement by companies and capital in partnership for collective action across the public, social, and private sectors. Five years into the SDG agenda, there is ample evidence that governments, investors, and companies are beginning to exercise their capacity to create much-needed change.

More: https://www.bcg.com/publications/2019

Authors: David Young, Wendy Woods, and Martin Reeves

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Financial crime and fraud in the age of cybersecurity

As cybersecurity threats compound the risks of financial crime and fraud, institutions are crossing functional boundaries to enable collaborative resistance.

In 2018, the World Economic Forum noted that fraud and financial crime was a trillion-dollar industry, reporting that private companies spent approximately $8.2 billion on anti–money laundering (AML) controls alone in 2017. The crimes themselves, detected and undetected, have become more numerous and costly than ever. In a widely cited estimate, for every dollar of fraud institutions lose nearly three dollars, once associated costs are added to the fraud loss itself. 1 Risks for banks arise from diverse factors, including vulnerabilities to fraud and financial crime inherent in automation and digitization, massive growth in transaction volumes, and the greater integration of financial systems within countries and internationally. Cybercrime and malicious hacking have also intensified. In the domain of financial crime, meanwhile, regulators continually revise rules, increasingly to account for illegal trafficking and money laundering, and governments have ratcheted up the use of economic sanctions, targeting countries, public and private entities, and even individuals. Institutions are finding that their existing approaches to fighting such crimes cannot satisfactorily handle the many threats and burdens. For this reason, leaders are transforming their operating models to obtain a holistic view of the evolving landscape of financial crime. This view becomes the starting point of efficient and effective management of fraud risk.

The evolution of fraud and financial crime

Fraud and financial crime adapt to developments in the domains they plunder. (Most financial institutions draw a distinction between these two types of crimes: for a view on the distinction, or lack thereof, see the sidebar “Financial crime or fraud?”) With the advent of digitization and automation of financial systems, these crimes have become more electronically sophisticated and impersonal.

Financial crime or fraud?

For purposes of detection, interdiction, and prevention, many institutions draw a distinction between fraud and financial crime. Boundaries are blurring, especially since the rise of cyberthreats, which reveal the extent to which criminal activities have become more complex and interrelated. What’s more, the distinction is not based on law, and regulators sometimes view it as the result of organizational silos. Nevertheless, financial crime has generally meant money laundering and a few other criminal transgressions, including bribery and tax evasion, involving the use of financial services in support of criminal enterprises. It is most often addressed as a compliance issue, as when financial institutions avert fines with anti–money laundering activities. Fraud, on the other hand, generally designates a host of crimes, such as forgery, credit scams, and insider threats, involving deception of financial personnel or services to commit theft. Financial institutions have generally approached fraud as a loss problem, lately applying advanced analytics for detection and even real-time interdiction. As the distinction between these three categories of crime have become less relevant, financial institutions need to use many of the same tools to protect assets against all of them.

One series of crimes, the so-called Carbanak attacks beginning in 2013, well illustrates the cyber profile of much of present-day financial crime and fraud. These were malware-based bank thefts totaling more than $1 billion. The attackers, an organized criminal gang, gained access to systems through phishing and then transferred fraudulently inflated balances to their own accounts or programmed ATMs to dispense cash to waiting accomplices (Exhibit 1).

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Significantly, this crime was one simultaneous, coordinated attack against many banks. The attackers exhibited a sophisticated knowledge of the cyber environment and likely understood banking processes, controls, and even vulnerabilities arising from siloed organizations and governance. They also made use of several channels, including ATMs, credit and debit cards, and wire transfers. The attacks revealed that meaningful distinctions among cyberattacks, fraud, and financial crime are disappearing. Banks have not yet addressed these new intersections, which transgress the boundary lines most have erected between the types of crimes (Exhibit 2).

More: https://www.mckinsey.com/business-functions/risk

Authors: Salim Hasham is a partner in McKinsey’s New York office, where Shoan Joshi is a senior expert; Daniel Mikkelsen is a senior partner in the London office.

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The Company of the Future

In the coming decade, companies will increasingly need to compete on the rate of learning. Technology promises to play a critical role: artificial intelligence can detect patterns in complex data sets at extreme speed and scale, enabling dynamic learning. This will allow organizations to constantly adapt to changing realities and surface new opportunities, which will be increasingly important in an uncertain and fast-changing environment.

But for companies to compete on learning, it is not enough to merely adopt AI, which alone can accelerate learning only in individual activities. As with previous transformative technologies, unlocking the full potential of AI—and of humans—will require fundamental organizational innovation.

In other words, to win the ’20s, leaders will need to re-invent the enterprise as a next-generation learning organization.

The next-generation learning organization will need to be redesigned to fulfill several key functions: (See Exhibit 1.)

  • Learning on All Timescales. The growing opportunity and need to learn on faster timescales, driven by technological innovation, is well known—algorithmic trading, dynamic pricing, and real-time customized product recommendations are already a reality in many businesses. But it is perhaps under-appreciated that slow-moving forces are also becoming more important. For example, trade institutions, political structures, wealth stratification, and social attitudes are slowly changing in ways that could have a profound impact on business. Gone are the days when business leaders could focus only on business and treat these broader variables as constants or stable trends. But such shifts unfold over many years or even decades. In order to thrive sustainably, businesses must learn on all timescales simultaneously.
  • Combining Humans and Machines Optimally. Machines have been crucial components of businesses for centuries—but in the AI age, they will likely expand rapidly into what has traditionally been considered white-collar work. Instead of merely executing human-directed and designed processes, machines will be able to learn and adapt, and will therefore have a greatly expanded role in future organizations. Humans will still be indispensable, but their duties will be quite different when complemented or substituted by intelligent machines.
  • Integrating Economic Activity Beyond Corporate Boundaries. Businesses are increasingly acting in multicompany ecosystems that incorporate a wide variety of players. Indeed, seven of the world’s largest companies, and many of the most profitable ones, are now platform businesses. Ecosystems greatly expand learning potential: they provide access to exponentially more data, they enable rapid experimentation, and they connect with larger networks of suppliers of customers. Harnessing this potential requires redrawing the boundaries of the enterprise and effectively influencing economic activity beyond the orchestrating company.
  • Evolving the Organization Continuously. The need for dynamic learning does not apply just to customer-facing functions—it also extends to the inner workings of the enterprise. To take advantage of new information and to compete in dynamic, uncertain environments, the organizational context itself needs to be evolvable in the face of changing external conditions.
  • By reconceiving the external and internal workings of the organization as a flexible, evolving ecosystem, businesses can handle much greater dynamism and complexity. This requires subjecting all aspects of the organization to market forces, enabling it to learn and adapt in response to new opportunities. And it requires internal systems that adjust automatically to new information, allowing learning and resource reallocation to occur at algorithmic speed. When combined, these capabilities can create a “self-tuning enterprise” that constantly learns and evolves according to its environment. (See Exhibit 3.)To harness the power of ecosystems throughout and beyond the organization, leaders must:
    • Engage external partners to create a shared vision of the future.
    • Develop capabilities for collaboration and information sharing at scale—for example, platforms and APIs.
    • Redesign internal processes to be more adaptive and data-driven, allowing the organization to become “self-tuning.”

By reconceiving the external and internal workings of the organization as a flexible, evolving ecosystem, businesses can handle much greater dynamism and complexity. This requires subjecting all aspects of the organization to market forces, enabling it to learn and adapt in response to new opportunities. And it requires internal systems that adjust automatically to new information, allowing learning and resource reallocation to occur at algorithmic speed. When combined, these capabilities can create a “self-tuning enterprise” that constantly learns and evolves according to its environment. (See Exhibit 3.)

To harness the power of ecosystems throughout and beyond the organization, leaders must:

  • Engage external partners to create a shared vision of the future.
  • Develop capabilities for collaboration and information sharing at scale—for example, platforms and APIs.
  • Redesign internal processes to be more adaptive and data-driven, allowing the organization to become “self-tuning.”

By Allison Bailey, Martin Reeves, Kevin Whitaker, and Rich Hutchinson

More: BCG https://www.bcg.com/

The BCG Henderson Institute is Boston Consulting Group’s strategy think tank, dedicated to exploring and developing valuable new insights from business, technology, and science by embracing the powerful technology of ideas. The Institute engages leaders in provocative discussion and experimentation to expand the boundaries of business theory and practice and to translate innovative ideas from within and beyond business. For more ideas and inspiration from the Institute, please visit Featured Insights.

 

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The agile manager

The agile workplace is becoming increasingly common. In a McKinsey survey of more than 2,500 people across company sizes, functional specialties, industries, regions, and tenures, 37 percent of respondents said their organizations are carrying out company-wide agile transformations, and another 4 percent said their companies have fully implemented such transformations. The shift is driven by proof that small, multidisciplinary teams of agile organizations can respond swiftly and promptly to rapidly changing market opportunities and customer demands. Indeed, more than 80 percent of respondents in agile units report that overall performance increased moderately or significantly since their transformations began.

What do managers in agile organizations do?

These small teams, often called “squads,” have a great deal of autonomy. Typically composed of eight to ten individuals, they have end-to-end accountability for specific outcomes and make their own decisions about how to achieve their goals. This raises an obvious and seemingly mystifying question for people who have worked in more traditional, hierarchical companies: Who manages in an agile organization? And what exactly does an agile manager do?

Aaron De Smet is a senior partner in McKinsey’s Houston office.

More: McKinsey https://www.mckinsey.com

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BCG – The Science of Organizational Change

There is a gap between where most organizations are today and where they will need to be to succeed in the coming decade. The companies that win in the 2020s will be designed to constantly learn and adapt to changing realities, combine artificial and human intelligence in new ways, and harness the benefits of broader business ecosystems. Reaching this necessary future state will require a fundamental transformation.

This change effort will be challenging. Many businesses have deeply entrenched operating systems that are predicated on hierarchy and human decision making. They will need to redesign their internal processes and build new capabilities and business models. Furthermore, this will not be a one-time change effort: the dynamic nature of business will require organizations to build capabilities for ongoing large-scale change to keep up with evolving technology and competition.

Traditional approaches to enacting organizational change are generally not very effective. Change management is generally thought of as one-size-fits-all and based on plausible rules of thumb. But our research shows that only about one in four transformations succeeds in the short and long run, and the success rate has been trending downward. Meanwhile, the stakes are extremely high: the cumulative difference between success and failure for the largest transformations over a decade can add up to the company’s entire market value.

Leaders need to take a new approach to change—one that deploys evidence, analytics, and emerging technology. In other words, leaders must apply the emerging science of organizational change, which is based on five key components. (See Exhibit 1.)

  1. Ground change programs in evidence.
  2. De-average change strategies according to the nature of the challenge at hand.
  3. Embrace uncertainty and complexity in change management.
  4. Use technology to identify the right talent to execute change.
  5. Tap into emerging science to enhance change programs.

By Lars Fæste, Martin Reeves, and Kevin Whitaker

More: www.bcg.com/publications/2019/