Effective Innovation REVISED EDITION: The Essential Guide to Staying Ahead of the Competition

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Effective Innovation: The essential guide to staying ahead of the competition Innovation - the process of taking new ideas through to satisfied customers - is the lifeblood of any organization today. Nothing causes a company and the individuals working in it to lose enthusiasm more than a lack of interest in positive change.

You cannot stand still: either you go forwards or you move backwards. In Effective Innovation John Adair, Britain's foremost expert on leadership training, looks at both creativity and innovation and tells you everything you need to know to enable you to generate new ideas and bring them to market. Confused about buying this product or want to buy it at best price? You can help fellow community people by giving your invaluable comments too.

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Similar Searches Effective Innovation: The. Bestselling Products. Lady, You're the Boss Valuating innovative business models: quantifying the unquantifiable Building a consistent and balanced innovation portfolio Challenge 5: Nimble execution — fail fast and win big Nimble execution: learn cheaply and adapt quickly Lean development: speed and flexibility Smart money: funding innovation projects Conclusion: More brain, less storming.

The Book Navigating Innovation Every firm must maintain an entrepreneurial ecosystem and a coherent innovation strategy in order to stay ahead of the competition. Bibliography Resistance to change: disrupting routines Book Callon, M. Acting in an uncertain world. MIT press. Book Godin, S. Purple cow: Transform your business by being remarkable. The precautionary principle in the 20th century: Late lessons from early warnings.

Book Juma, C. Innovation and its enemies: Why people resist new technologies. Oxford University Press. Book Kotter, J.

The future of regulation

Our iceberg is melting: Changing and succeeding under any conditions. Book Lewin, K. A Dynamic Theory of personality-Selected papers. Read Books Ltd. Book Perez, C. Technological revolutions and financial capital. Edward Elgar Publishing. Book Senge, P. The dance of change: The challenges to sustaining momentum in a learning organization. Article Alexy, O.

Innovation Master Class: Building a Successful Innovation Program

From closed to open: Job role changes, individual predispositions, and the adoption of commercial open source software development. Research Policy , 42 8 , In theory, this should lead to unbiased and fair decisions. But some algorithms have been found to have inherent biases. And while in some countries regulations explicitly prohibit discrimination in these and other areas, gray areas exist and often the underlying algorithms are opaque. A widely cited example of algorithmic bias was found in a study conducted by Harvard faculty member Latanya Sweeny. Her study concluded that searches for stereotypical African-American names are up to 25 percent more likely to be displayed alongside an arrest-related ad.

Sweeney gathered this evidence by collecting more than 2, names suggestive of race. For example, first names such as Terrell, Tyrone, and Ebony suggest the person is black, while Amy, Jake, and Emma suggest the person is white. As government policymakers and regulators grapple with the regulatory challenges posed by digital technologies, four foundational questions are critical to address see figure 2 :. The first step in the preregulatory phase should involve a thorough review and understanding of pertinent existing regulations, looking for those that might be blocking innovation, are outdated, or are duplicative.

By current state, we refer to the whole ecosystem of regulation that could apply: from vertical service or sector regulation, for example, for motor vehicles; to convergent regulation where multiple sectors are involved; to lateral regulation such as employment or business licensing. A Deloitte analysis of the US Code of Federal Regulations found that 68 percent of federal regulations have never been updated see figure 3.

A retrospective review forces regulators to evaluate whether alternatives to regulation or adjustments to current rules could adequately address the perceived problem. This includes cutting the number of regulations in its portfolio by one-third, plans to slash the number of laws it administers from 90 to 43, and an update of all existing laws to conform to the digital age.

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How can regulators avoid the too fast or too slow problem? A number of the principles outlined in the next section of the paper particularly principles one and two, adaptive regulation, and regulatory sandboxes are designed to help answer the when question by both bringing regulators closer to the technological innovations while also shifting to a more agile regulatory model. A wide variety of potential approaches exist between heavy, precautionary regulation on one end of the spectrum and little to no regulation on the other end see figure 2. Consider regulations pertaining to unmanned aerial systems UAS , or drones.

Governments have increasingly opted for one of two paradigms in building regulatory systems: UAS Allowance broader permissiveness of UAS usage or UAS restriction usage permitted only within specific limits. The same is increasingly true for innovation. Innovators can, and increasingly will, move to those countries and continents that provide a legal and regulatory environment more hospitable to entrepreneurial activity. We have already seen this scenario play out with genetic testing, unmanned aerial systems, autonomous vehicles, and the sharing economy.

Rapid change, pivoting business models, and experimentation are hallmarks of technology-driven businesses—but are rarely the norm in regulation. Traditionally, regulators conceptualize new rules and regulations in response to market developments or new legislation.

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Next, they spend months or years drafting rules and presenting a first draft for public comment. Finally, they examine these comments—and there can be tens of thousands or even millions of them—and change the proposed draft accordingly. Adaptive approaches to regulation, on the other hand, rely more on trial and error and co-design of regulation and standards; they also have faster feedback loops. More rapid feedback loops allow regulators to evaluate policies against set standards, feeding inputs into revising regulations. Regulatory agencies have a number of tools to seek such feedback: setting up policy labs, creating regulatory sandboxes detailed in the next section , crowdsourcing policymaking, and providing representation to industry in the governance process via self-regulatory and private standard-setting bodies.

Soft law mechanisms—instruments or arrangements that create substantive expectations that are not directly enforceable—offer another tool for shifting to more adaptive regulation. While not legally binding, soft law instruments have several advantages over formal regulation in the arena of emerging technologies. They allow regulators to adapt quickly to changes in technology and business models, and to address issues as they arise without stifling innovation. One way regulators can apply soft law is to define the scope of issues to be addressed and ask industry to develop its own standards and codes of conduct in response.

Finnish officials recognized the need to reform their transport regulations to support their vision of mobility-as-a-service MaaS , which considers transportation as an integrated system of different services. Hence, the country decided not to reform or revise separate laws on taxis, public transport, roads, or the transport of goods but instead to create a new integrated transportation code. The aim is to deregulate existing transport while building the foundations for MaaS. Accelerators are designed to speed up innovation.

They often involve partnerships with private companies, academic institutions, and other organizations that can provide expertise in certain areas. Sandboxes are controlled environments allowing innovators to test products, services, or new business models without having to follow all the standard regulations see figure 5. The Canadian Securities Administrators CSA , for example, launched a regulatory sandbox that provides time-limited relaxation from certain regulatory requirements placed on startups.

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While regulation can reduce some barriers to entry by instilling confidence and bridging the trust gap, it can also erect other barriers to entry for new firms and inadvertently inhibit competition and innovation. Barriers to entry affect the timeliness, likelihood and sufficiency of competitive entry. We are still operating a voluntary breach notification system, but we are fleshing it out so that we can make use of this time to work through the operational details. Robo-advice platforms offer a number of services that are different from those of traditional advisors and may therefore appeal to investors with entirely different preferences for advice services. These restrictions and the limited direct participation resulting from them can, however, have a negative impact on competition. While these new products have the potential to stimulate economic activity, providers of these services have faced significant barriers that may be inhibiting their entry and growth. Typically, the DIY channel offers investors access to most securities available to be purchased unless the security has specific limits on distribution.

Impak will be allowed to remain in the sandbox for two years. These include operations over the heads of people, beyond the line of sight, and at night. Sandbox approaches are intended to help regulators better understand new technologies and work collaboratively with industry players to develop appropriate rules and regulations for emerging products, services, and business models. Sandboxes are not without their detractors who worry regulators might get too close to the startups and try to prop them up if they stumble in the market.

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Some of the companies in your greenhouse might fail, just like some plants in your garden die; others will grow and flourish, but there's full transparency, with some protection. The United Kingdom has been a pioneer in the use of accelerators and sandboxes as part of the regulatory process.

This sandbox allows businesses to test innovative products and services in a safe, live environment, with the appropriate consumer safeguards, and, when appropriate, is exempt from some regulatory environments. Traditionally, regulations have tended to be prescriptive and focused on inputs. When the focus of regulation shifts from inputs to outcomes, the way government intervenes in markets changes.

This shift can create operational efficiencies for regulators and greater freedom for innovators. Outcome-based regulation specifies required outcomes or objectives rather than defining the way in which they must be achieved. This model of regulation offers businesses and individuals more freedom to choose their way of complying with the law. Consider three different ways of structuring UAS regulations:. For such connections to happen, innovators need room to innovate.

Outcome-based regulation can provide the leeway needed to experiment. Australia has developed performance-based guidelines for autonomous vehicles.

Effective Innovation REVISED EDITION: The Essential Guide to Staying Ahead of the Competition

Paul Retter, NTC chief executive, believes multiple issues should be addressed before making autonomous vehicle a reality on the road. Industry stakeholders also are evaluating performance-based standards. The Australian Automobile Association suggests that standards for automated vehicles should be performance-based and technology-agnostic, and that the responsible parties and processes for certifying vehicle modifications should be clearly identified and unambiguous.

Speed to market is imperative for businesses, especially startups with business models predicated on emerging technologies. Speed to market also can make digital services and products more effective. As they are used, they usually collect data on their users. With the help of advanced analytics and, in many cases, AI, the data can then be analyzed to detect new patterns and trends, information that can make the product more accurate, safe, effective, and personalized.

Because of this iterative factor, the sooner safe and effective products get to the market, the better.