Menedżerowie Archive

0

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.

 

0

Kedro, McKinsey’s first open-source software tool

 

QuantumBlack, the advanced analytics firm we acquired in 2015, has now launched Kedro, an open source tool created specifically for data scientists and engineers. It is a library of code that can be used to create data and machine-learning pipelines. For our non-developer readers, these are the building blocks of an analytics or machine-learning project. “Kedro can change the way data scientists and engineers work,” explains product manager Yetunde Dada, “making it easier to manage large workflows and ensuring a consistent quality of code throughout a project.”

McKinsey has never before created a publicly available, open source tool. “It represents a significant shift for the firm,” notes Jeremy Palmer, CEO of QuantumBlack, “as we continue to balance the value of our proprietary assets with opportunities to engage as part of the developer community, and accelerate as well as share our learning.”

The name Kedro, which derives from the Greek word meaning center or core, signifies that this open-source software provides crucial code for ‘productionizing’ advanced analytics projects. Kedro has two major benefits: it allows teams to collaborate more easily by structuring analytics code in a uniform way so that it flows seamlessly through all stages of a project. This can include consolidating data sources, cleaning data, creating features and feeding the data into machine-learning models for explanatory or predictive analytics.

More: www.mckinsey.com; https://github.com/quantumblacklabs/kedro

  What are the main features of Kedro?

1. Project template and coding standards

  • A standard and easy-to-use project template
  • Configuration for credentials, logging, data loading and Jupyter Notebooks / Lab
  • Test-driven development using pytest
  • Sphinx integration to produce well-documented code

2. Data abstraction and versioning

  • Separation of the compute layer from the data handling layer, including support for different data formats and storage options
  • Versioning for your data sets and machine learning models

3. Modularity and pipeline abstraction

  • Support for pure Python functions, nodes, to break large chunks of code into small independent sections
  • Automatic resolution of dependencies between nodes
  • (coming soon) Visualise your data pipeline with Kedro-Viz, a tool that shows the pipeline structure of Kedro projects

Note: Read our FAQs to learn how we differ from workflow managers like Airflow and Luigi.

4. Feature extensibility

  • A plugin system that injects commands into the Kedro command line interface (CLI)
  • List of officially supported plugins:
    • (coming soon) Kedro-Airflow, making it easy to prototype your data pipeline in Kedro before deploying to Airflow, a workflow scheduler
    • Kedro-Docker, a tool for packaging and shipping Kedro projects within containers
  • Kedro can be deployed locally, on-premise and cloud (AWS, Azure and GCP) servers, or clusters (EMR, Azure HDinsight, GCP and Databricks)

0

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/

0

McKinsey – Getting organizational redesign right

Companies will better integrate their people, processes, and structures by following nine golden rules.

Recent McKinsey research surveying a large set of global executives suggests that many companies, these days, are in a nearly permanent state of organizational flux. Almost 60 percent of the respondents, for example, told us they had experienced a redesign within the past two years, and an additional 25 percent said they experienced a redesign three or more years ago. A generation or two back, most executives might have experienced some sort of organizational upheaval just a few times over the course of their careers. One plausible explanation for this new flurry of activity is the accelerating pace of strategic change driven by the disruption of industries. As a result, every time a company switches direction, it alters the organization to deliver the hoped-for results. Rather than small, incremental tweaks of the kind that might have been appropriate in the past, today’s organizations often need regular shake-ups of the Big Bang variety.

Frustratingly, it also appears that the frequency of organizational redesign reflects a high level of disappointment with the outcome. According to McKinsey’s research, less than a quarter of organizational-redesign efforts succeed. Forty-four percent run out of steam after getting under way, while a third fail to meet objectives or improve performance after implementation. The good news is that companies can do better—much better. In this article, we’ll describe what we learned when we compared successful and unsuccessful organizational redesigns and explain some rules of the road for executives seeking to improve the odds. Success doesn’t just mean avoiding the expense, wasted time, and morale-sapping skepticism that invariably accompany botched attempts; in our experience, a well-executed redesign pays off quickly in the form of better-motivated employees, greater decisiveness, and a stronger bottom line.

Why redesign the organization?

Organizational redesign involves the integration of structure, processes, and people to support the implementation of strategy and therefore goes beyond the traditional tinkering with “lines and boxes.” Today, it comprises the processes that people follow, the management of individual performance, the recruitment of talent, and the development of employees’ skills. When the organizational redesign of a company matches its strategic intentions, everyone will be primed to execute and deliver them. The company’s structure, processes, and people will all support the most important outcomes and channel the organization’s efforts into achieving them.

When do executives know that an organization isn’t working well and that they need to consider a redesign? Sometimes the answer is obvious: say, after the announcement of a big new regional-growth initiative or following a merger. Other signs may be less visible—for example, a sense that ideas agreed upon at or near the top of the organization aren’t being translated quickly into actions or that executives spend too much time in meetings. These signs suggest that employees might be unclear about their day-to-day work priorities or that decisions are not being implemented. A successful organizational redesign should better focus the resources of a company on its strategic priorities and other growth areas, reduce costs, and improve decision making and accountability.

The case of a consumer-packaged-goods (CPG) company that chose to expand outside its US home base illustrates one typical motivation for a redesign. Under the group’s previous organizational structure, the ostensibly global brand team responsible for marketing was not only located in the United States but had also been rewarded largely on the performance of US operations; it had no systems for monitoring the performance of products elsewhere. To support a new global strategy and to develop truly international brands and products, the company separated US marketing from its global counterpart and put in place a new structure (including changes to the top team), new processes, new systems, and a new approach to performance management. This intensive redesign helped promote international growth, especially in key emerging markets such as Russia (where sales tripled) and China (where they have nearly doubled).

By Steven Aronowitz, Aaron De Smet, and Deirdre McGinty

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

0

BCG – Twelve Forces That Will Radically Change How Organizations Work

A tidal wave of change is coming that will soon make the way we work almost unrecognizable to today’s business leaders. In an age of rapidly evolving technologies, business models, demographics, and even workplace attitudes—all shifting concurrently—change is not only constant but also exponential in its pace and scope. Companies from startups and online businesses to incumbents in all industries will experience the effects in far-reaching and transformational ways.

During a comprehensive, yearlong analysis of the global work landscape, The Boston Consulting Group identified 60 major trends propelling this tidal wave, which we’ve grouped into 12 primary forces. These forces, or megatrends, fall into four categories. The first two address changes in the demand for talent: technological and digital productivity and shifts in ways of generating business value. The second two address changes in the supply of talent: shifts in resource distribution and changing workforce cultures and values. (See Exhibit 1. For a list of all 60 trends, see the Appendix.)

Together, these forces will revolutionize the way that work gets done in companies and will compel leaders to rethink even the most basic assumptions about how their organizations function. They will need to discover new ways of organizing, performing, and leading, along with new approaches to recruiting, developing, and engaging employees. All this in organizations with limitless data, open boundaries, employees and machines working side by side, and rapidly evolving employee value propositions. BCG has assessed the impact of these megatrends on organizations. In this report, the first in the New New Way of Working series, we identify several companies that are leading the way. Yet most organizations still have far to go.

Six of the forces we identified are having a profound effect on the demand for talent. (See Exhibit 2.) We categorize them into two groups:

  • Technological and digital productivity: automation, big data and advanced analytics, and access to information and ideas
  • Shifts in ways of generating business value: simplicity in complexity, agility and innovation, and new customer strategies

By Vikram Bhalla , Susanne Dyrchs , and Rainer Strack

More: https://www.bcg.com