The provenance of the information being presented must be readily available and a part of the data-based problem-solving story.
Define the problem or opportunity based on reliable information: Some organizations waste a lot of time and tens of thousands of dollars reacting to problems/challenges, but never really solving anything, only creating more problems. Many complex problems are usually difficult to define, indeed, part of the difficulty is that there is a mixed bag of good information and misinformation; good information can either enforce cognitive understanding or sometimes be misleading, and misinformation perhaps causes distraction due to incomplete information or false knowledge. Also, businesses often try to use decision-making processes to define the problem, and in doing so often fail to really define the problem, and then try to solve that problem by using more decision-making logic and wonder why the actions you have taken have made the situation worse.
To frame the right problem, it’s important to improve information quality, and separate the “exploration/discussion” phase from the “decision-making phase” as the logic being applied is inherently different and mixing the two will cause confusion. Until you have made a first cut at defining the opportunity, issue or problem that needs a decision ("Framed the Issue"), you are not ready to start on decision making. Let quality data make sound judgments. Data Management needs to be well embedded into the key business processes to identify risks or opportunities. Data-based insight is being able to identify the root cause of a problem or the core issues of a situation that leads to understanding and defining problems with accuracy.
Options: Digital is the age of choice, it provides the opportunity to think of better ways to do things and solve problems holistically. To make a wise choice of data-based problem-solving, it’s important to understand both intrinsic and extrinsic values of information. The intrinsic value of information is about turning the most invaluable information and knowledge assets into precious insight to improve problem-solving effectiveness. gaining new and wider views, discovering unusual dots and build unexpected connections between our starting points and its rich environment, the digital ecosystem, to spark innovation, broaden varying perspectives
It is easy for us to observe how other people become emotionally charged and reactive to problems/challenges; it's even easier for ourselves to become ignited/emotionally charged and reactive towards problems/challenges. To the very least, problem-solvers should at least explore their options and possibilities, since being data-savvy is becoming a norm either professionally or at the organizational level today. The extrinsic value of information is to broaden varying perspectives ecologically, sociologically, or technologically, etc for solving problems holistically.
Running a business is about continuously solving problems large or small. Say, it’s important to provide choices for customers on how to solve their issues by listening to their feedback, solving customers’ problems by tailoring their needs and delivering solutions that delight them. You can analyze the data even more to find out which audiences are likely to buy certain products and which audiences are not likely to purchase other products, so that you can maximize your marketing dollars by targeting people who are more likely to purchase. Provide choices for talented employees on how they would like to get the work done, stop micromanagement and foster autonomy, you solve their problems and they solve customers’ problems.
Recommendation - based on facts or data: Choices are great, but how to make the right choice based on trustful information in order to solve problems with an optimal solution? Ofen problem-solvers too narrowly look at specific problems, with available data and handy requirements, but lack a broad view of their organization and long term strategy for the business, sometimes, their solutions could be too short term focused or narrow-focused. The relevant and reliable information helps to understand the situation, understand the people working with us as well as the people receiving the "solution," understand expectations from each group involved, understand motivation drivers, understand how everyone is integrated to the solution, and understand and differentiate the results from the impacts to ensure the engagement.
So good data is fine, but the refined insight of holistic understanding of situations and foresight driven recommended solutions are in demand to drive intended progress. The intention is not about finding the perfect solution but making progressive problem resolution. For business leaders or professionals, information is only a part of the story in problem-solving, the right dose of gut-feeling is perhaps another necessary ingredient to make effective decisions and solve many issues fluently. It's important to explore the new solutions and pursue "perfecting" via making the continuous adjustment.
Outcome: You cannot choose between alternatives without being clear about your desired outcome. Understand what your high-level outcomes are related to the issue, opportunity or problem. The desired outcome of problem-solving is to fix the root causes with little side-effects. Keep in mind, even if you take all critical steps in smart problems, you may still not reach the desired outcome because variables or circumstances constantly change. What is needed today is top-down to be more about the vision of the outcome.
So outcome based analysis is about finding the factors involved in the final "incorrect" outcome: See if you can measure or weigh each factor's contribution to the result, or the description of the unit of measure. Build a hypothetical equation that describes your "incorrect" outcome. See how changing any of these gets better or worsens that outcome.
The provenance of the information being presented must be readily available and a part of the data-based problem-solving story. The real problem will always be to make sense of data from a problem-solving perspective, let the data do the talking and create a lasting effect of storytelling, allowing consolidation and segregation of data to provide an in-depth understanding; allowing deep and thorough data analysis; assisting in prioritizing business problems or opportunities, and solving them in an intelligent manner. Last but not least, learn from the past problems and challenges along with encouraging others to learn from the problems that have happened, and believe that problems are the opportunity to show others you're a good problem-solver.
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