2 items tagged "adaptive businesses"

  • Adapting businesses are always ahead of their competition

    Adapting businesses are always ahead of their competition

    Firms need a new formula for success to stay competitive in the age of the customer, agility alone is not enough. We see many CIOs and their teams doubling down on agility as a means to cope with the accelerating pace of business. This is a result of people and technology evolving in complex upward spirals.

    While being agile is a good delivery strategy within a set business model, research finds that to stay ahead of technology-human loops, businesses must proactively rethink themselves and adapt or risk getting left behind.

    These firms, which we call 'adaptive businesses', will likely dominate firms that only deliver with agility. Adaptive businesses will win by identifying future opportunities and proactively reconfiguring themselves. Forrester’s 2019 North American Online Innovation Survey shows that advanced adaptive companies have 3.2 times greater revenue growth compared to industry averages, while beginning firms are not growing at all.

    Agility is a foundation, but to achieve this level of growth and future market leadership, adaptive businesses firms must become more adaptive by doing several things better. Here are three main ones:

    • Acting on insights. An adaptive business alters its business concept based on insights that improve the company’s odds of fulfilling future customer demand. For example, CVS understood the customer trend toward self-service and clinic-based healthcare far ahead of its competitors in its pivot from beauty supplies to prescriptions and through its acquisition of MinuteClinic. It is carrying that conviction forward by transforming itself into a healthcare powerhouse through further acquisitions such as Aetna.
    • Leveraging platforms to deliver new value. Technological advancements lower the barriers to change, so companies that are more technologically sophisticated will more easily transition to new business models. Mastercard was far ahead of its competition in building a big data analytics platform. Today, it has leveraged its technology platform to extend its core business with fraud solutions, B2B payments, and business optimization services like Mastercard Track.
    • Building a culture that embraces change. Adaptive businesses adopt new business models more quickly and thus require employees to have more mental flexibility and less fear of change. While the industry has overused Netflix as a platform example, we think is culture as expressed by its now famous “five rules” established a culture of adaptability. By inspiring employees, the company has evolved from an antiquated mailing service to streaming pioneers, to original content production.

    The idea of business adaptiveness is a core theme of research that draws together two research streams: technology-driven innovation and the future of work, as well as many other of the most important research ideas on insights, digital platforms, and agile delivery. It is an advanced concept that we are holding up as the bar for future business excellence.

    Is your bsuiness becoming 'adaptive'? We hope so.

    Author: Brian Hopkins

    Source: Inofrmation-management

  • Continuous improvement requires continuous intelligence

    Continuous improvement requires continuous intelligence

    Business leaders must take the initiative to leverage their data using new technologies and approaches to adapt and succeed in the digital world.

    The digital age has presented businesses with a significant challenge: adaptation. Organizations can only hope to survive in this new era if they are able to adapt to the new reality of doing business.

    For the past few years, adaptation efforts have fallen under the umbrella of digital transformation. It is now widely understood that organizations must engage the groundswell of digital data and refine it into a byproduct that can inform decisions or instantaneous actions. However, because digital data flows continuously, the data engagement model should also be continuous, leveraging advances in machine learning, AI, IoT, and analytics. This sort of continuity will catalyze organizations to adapt and thrive in the new digital reality.

    Continuous intelligence

    Because IT has historically focused on batch processing, the concept of continuous processing is fairly new to most organizations. Continuous intelligence waits for nothing. Not data collection periods, not resource availability, not processing time. It is the non-stop generation of insight and actions based on operational data stores as well as streams of data and events generated in the moment. It is the ability to harness an ever-changing environment where the data is constantly flowing and the insights and actions are perishable.

    According to Gartner, success can only be achieved in a world that is constantly changing by implementing a continuous approach. Gartner suggests that continuous intelligence is at the heart of fast-paced digital business and process optimization. However, continuous intelligence is not only about IT architectures. Successful implementation requires a change in managerial approach as well.

    New leadership approach

    Conway’s Law gave us the insight that system designs reflect the communication structures of the organizations that design them. Because designing continuous intelligence requires new architectures, it is critical that the organizations designing them reflect the architectural intent.

    Most organization structures today assume they are performing in a batch-processing world. One team works to complete a task before handing it off to the next team, there is no continuity of visibility or activity. Initiating a continuous intelligence effort with the limitations inherent in a batch processing management model will produce feet but no wings.

    To fully implement the continuous intelligence approach, business leaders need to adapt to agile management methodologies. Just as the DevOps world engages continuous integration across teams, so must the larger IT organization engage in a more active and constant way. The rate of engagement is necessarily radically higher, that is the only way for the broader team to understand what’s going on in the organization. This approach will facilitate initial success and be the foundation for staying ahead in an era of new, dynamic technologies and continuous change.

    The need for speed

    One of the fundamental changes to the IT stack required for continuous intelligence is a new data processing layer designed to perform at extremely low levels of latency. Regardless of whether the data already exists in operational data stores or arrives in event-based streams, the concept of continuity is at odds with latency.

    Our traditional systems of record do not have this design point, nor should we expect them to. They will continue to do their job well while a new, complementary data processing layer is added.

    Innovations in IoT, machine learning, and AI assume both constancy and immediacy. Business value has become inextricably linked with real-time action. New applications require speed and scalability in the underlying data processing to produce responses as well as to 'feed the beast' to inform models. The money is in the microseconds, whether the data is at rest or in motion.

    Digitization has permanently changed the business landscape. Continuous intelligence is achievable. Business leaders must take the initiative to leverage their data through new technologies and approaches to adapt and succeed in the digital world.

    Author: Kelly Herrell

    Source: TDWI

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