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Grupo de Análise de Mercado

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Rezo Davydov
Rezo Davydov

How Bad Decision Making Could Undermine Good Innovation ((EXCLUSIVE))


You may choose different categories depending on the size and maturity of your company. The key is having some way to sort the types of decisions being made to ensure the right people are making them.




How bad decision making could undermine good innovation


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Next, you will need to identify decisions that may require cross-functional collaborations. At the intersection of marketing, sales, R&D, and manufacturing, for example, there might be a need to coordinate innovation or product launch decisions. If the organization is in high-growth mode, there may be a need for a cross-functional council tasked with onboarding and retaining top talent. Your goal should be to make decision making across teams and departments as seamless and efficient as possible.


Second, information linkages must be identified between governing groups. Each group has a predictable set of information flowing into their meeting, and a defined set of decisions and conclusions coming out. Those inputs and outputs contain information that is critical to other decision-making groups. Defining how information moves between these groups, by whom, and in what time frame will help ensure that your organization stays aligned. Information linkages include things like group members acting as liaisons to other groups, succinct post-meeting updates, and online portals where real-time decisions and meeting minutes are posted. Linking governing groups through shared calendars, and technology that fosters transparency also keeps the entire organization updated on where decisions are made, and the rationale behind them.


The best governance designs monitor and track their effectiveness. Whether this is done through gathering employee feedback or an annual evaluation of the systems in place, the quality of your decision-making processes must be regularly assessed so that you can identify what is and is not working. One company I worked with monitored their decision-making process by scheduling a 10-minute check in at the end of every standing meeting to evaluate whether or not they had accomplished what they intended. During this time, they reviewed the decisions that were made and solicited feedback from employees to gauge if people understood how and why the choices affecting them most were made. In addition, they wanted to know whether or not employees felt they were able to contribute adequately to those choices. In this way, the company was able to continuously reiterate and improve their processes.


To align their decision-making processes with agile approaches, businesses need to include diverse (customer, local, data-informed, and outside) points of view; clarify decision rights; match the cadence of decisions to the pace of learning; and encourage candid conflict in service of a better experience for the end customer. Only then will all that rapid experimentation pay off.


Businesses need to strengthen and speed up their creative decision-making processes by including diverse perspectives, clarifying decision rights, matching the cadence of decisions to the pace of learning, and encouraging candid, robust conflict in service of a better experience for the end customer. Only then will all that rapid experimentation pay off.


Research has long shown that diverse teams are better at identifying opportunities and risks in any problem-solving situation. But in organizations that are learning to experiment, four perspectives tend to be underrepresented in decision-making:


Especially in years like the past one, when the business environment was in constant flux, relying on past experience to guide innovation efforts may lead a company astray. Lean methods call for testing ideas and using near-real-time quantitative and qualitative data to decide next steps. The challenge lies in making that information accessible to every decision-maker.


Data visualization provides a solution: It can allow timely, complex information to be interpreted by people from a variety of functional backgrounds, leveling the playing field so that those who are less data savvy can fully engage when making decisions.


As they recognize the need to bring together many points of view, a lot of organizations are relying more on decentralized networks of cross-functional teams, both permanent and ad hoc, to increase their agility. But this can have a downside: Involving more voices in a decision can mean less clarity about who ultimately owns it, slowing the innovation process and often prompting frustration and disengagement.


Established companies tend to make innovation decisions on a fixed schedule, through quarterly or annual reviews at which senior teams step back, assess past plans, and make new ones. But in agile companies, innovation is based on discovery-driven learning. With each experiment, data and insights emerge that should be taken into consideration in setting up the next one. Leaders must encourage decisions to be made at a pace aligned with the learning cycle.


The many decisions that come up daily in experimentation often call for continuous processes. For example, in one Indian organization we studied, the design team created a WhatsApp forum to collect rapid feedback on its proposals from the whole organization, including remote employees working closely with end users in the field. Because the channel was always available, designers could spontaneously solicit feedback from employees and apply it to decisions immediately.


Policies based on the precautionary principle almost always stand in the way of innovations that can help the public, and this report identifies 11 policies that would limit the benefits of AI. The remainder of this report provides an overview of AI, lists policies based on the precautionary principle that threaten AI, and analyzes ten detrimental impacts of such policies. To close, it discusses what governments should do to reduce and rectify cases where AI use could be harmful.


AI is a field of computer science devoted to creating computer systems that perform operations characteristic of human intelligence, such as learning and decision making. The term does not imply human-level intelligence and the level of intelligence in any implementation of AI can vary greatly. For example, the intelligence level needed for Roomba vacuum cleaners is significantly lower than what is needed for autonomous vehicles.[24] Regardless, the development of better hardware, including faster processors and more abundant storage, large data sets, and more capable algorithms in the last decade have helped AI make significant advancements and unlocked new applications.[25]


Such a right undermines the purpose of automating tasks, which is to perform a task faster, cheaper, and easier than a human could.[93] Requiring manual review also disregards the many laws that already exist that guarantee a right to an explanation for certain high-impact decisions, such as why a company fired an employee, whether the firm used AI or not.[94] But there are other significant decisions made by humans, such as refusing a loan, where firms only have to tell applicants what their decisions are based on but not the logic of their reasoning.[95] Requiring AI systems to explain the reasoning for all their decisions creates an artificial and unnecessary hurdle to using AI.


Conflicts of interest abound at the board level. They constitute a significant issue in that they affect ethics by distorting decision making and generating consequences that can undermine the credibility of boards, organizations or even entire economic systems.


Many corporations require board members to sign a conflict of interest policy at the time of appointment or to declare any conflicts of interest at the beginning of board meetings. Conflict of interest policies normally specify how directors should avoid conflicts of interest. This narrow focus only scratches the surface, given the scope, responsibilities and dynamics of decision making in the boardroom.


Tier-I conflicts are actual or potential conflicts between a board member and the company. The concept is straightforward: A director should not take advantage of his or her position. As the key decision makers within the organization, board members should act in the interest of the key stakeholders, whether owners or society at large, and not in their own. Major conflicts of interest could include, but are not restricted to, salaries and perks, misappropriation of company assets, self-dealing, appropriating corporate opportunities, insider trading, and neglecting board work. All board members are expected to act ethically at all times, notify promptly of any material facts or potential conflicts of interest and take appropriate corrective action.


The trust placed in directors gives them maximum autonomy in decision making, and decisions are not questioned unless they are deemed irrational. This business judgment rule protects directors from potential liabilities, as their decisions are not tainted by personal interest. Though directors are not allowed to act in their own interests, they can promote the interests of a particular stakeholder group against the company, or the interests of one group of stakeholders against another, or they can favor one subgroup over another within the same stakeholder group. It is up to directors to make wise decisions when stakeholders are in conflict.


Could certain stakeholder groups, such as management, creditors, or shareholders benefit specifically from corporate decisions that could potentially hurt the other stakeholders? This is apparent when the value increase for one class of stakeholders is directly linked to the value reduction of another class of stakeholders.


Our readers will probably recognize some of these ideas and tools as techniques they have used in the past. But techniques by themselves will not improve the quality of decisions. Nothing is easier, after all, than orchestrating a perfunctory debate to justify a decision already made (or thought to be made) by the CEO. Leaders who want to shape the decision-making style of their companies must commit themselves to a new path.


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