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Invention is the precursor to innovation. Invention is the process of exploring a hypothesis or prototyping a new idea, while innovation translates an invention into a solution that is adopted at scale.
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Without an effective innovation process, there is no innovation or new and improved product or service, no market adoption, no revenue or impact. It’s also important to understand that at any given time in your teams and organizations, many will be thinking that innovation is a new ‘thing’, while others will be thinking it’s a ‘process’.
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If you strip away the perceived complexities and barriers from over-engineered internal systems and fear of failure, innovation is fundamentally a communication process.
It concerns most people and their social systems intersecting with technological infrastructures and economic forces, to make decisions on the design and development and adoption of new ideas.
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Design-driven innovation demands an exploratory and combinatory mindset, one that blends critical thinking with strategic thinking, and curiosity and empathy with analysis and creative synthesis.
The design mindset generates the seeing of unarticulated needs and patterns, and that triggers ideas and models for improvement that may be sketched or developed.
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Innovativeness is the capacity and willingness to actively participate in the learning activities of the innovation process. It’s like a journey. It involves thinking (head), doing (hands/body) and refecting (soul). Innovativeness as a learned trait is an important indicator of one’s level of innovation-readiness and innovative capacity. It is mindset-dependent, but transcends roles, functions and job titles.
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Human-centered design efforts require that all participants engage explicitly in divergent and convergent thinking practice. Divergent thinking involves generating many ideas or choices. Convergent thinking involves narrowing or choosing a single idea or choice.
Divergent thinking spans creative, generative and imaginative thinking modes, while convergent thinking spans analytical, critical and logical thinking modes.
When combined, these thinking modes help flex your mental muscles and push individual and team-based boundaries towards design-driven mindsets and innovative capacity-building.
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Successful projects result from effective communication, enabled by a well-articulated project brief. A brief is a document that outlines key information, a plan, and a process relating to a project. A clear brief aligns team members and stakeholders, reduces confining objectives, and enables strategic decision-making.
Innovation instructors create challenge briefs. To facilitate an effective project-based learning experience, a business challenge brief is used. The challenge brief outlines an open-ended driving question or business challenge that invites investigation and resolution.
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What problem(s) are you trying to solve? (as a problem hypothesis)? What customer problem(s) are you trying to address? (as needs)?
Who is most interested in solving this problem? Who is most influential in solving this problem?
Why does this problem matter? What is the internal stakeholder motivation to start the project and solve the problem? What is the external stakeholder motivation to resolve the need?
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Who is our intended customer/end-user for this problem/challenge? Why do they buy? Where are they located?
Who will participate in the innovation project? What is the timeline? Provide details of team members and associated tasks, activities (be feasible and realistic).
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Primary research involves direct engagement with the intended end-user or research subject population. (observation, interviews, focus groups, online chat rooms, questionnaires and surveys)
Secondary research involves reviewing and analyzing information from primary research activities. (document analysis of print or digital media reports, whitepapers, and industry reports)
Tertiary research involves referencing or citing summaries of completed analyses sourced from third-party primary and secondary research. (industry reports, mass media published articles, Wikipedia, etc)
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Thick data complements the more popular ‘big data’ (collected from large data samples), and when combined, they offer a complete view of the problem space in terms of what it is, how it occurs, and why it exists.
For organizations, big data offers quantifiable evidence from a broad sample size for informed decision-making. Alternatively, thick data offers qualitative evidence from a very small sample size, shifting the dataset from scale (macro trend) to uniqueness of experience (micro meaning) based on human motivations and choices.
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Aim: to generate information from quantifying patterns; to identify expected behavior; and validate problem hypothesis (prescriptive)
Methods: survey; questionnaire; focus group; interviews (scripted, closed)
Output: seeks to answer the ‘what’ from a research question
Value: data-driven decision-making
Example: Net Promoter Score (customer recommendation)
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Aim: to generate meaning from stories, collect data (natural language), discover patterns of meaning and behavior, and develop insights (iterative)
Methods: observational research and empathy interviews (guided, open-ended)
Output: seeks to answer the ‘what, how and why’ of a research question
Value: insight-driven decision-making
Example: Latent Need Discovery (customer pain points)
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An observation as fact is information that is observed to be true.
Facts are verifable data that we all see and which can be quantifed.
For example, we can verify that a smartphone is rectangular-shaped, broccoli is a source of iron, or that 600,000 people attended an event.
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An observation can also be an interpretation, a source of narrative data based on personal beliefs or prior experience.
For example, we believe that broccoli is a healthy food choice, or that we attended the biggest event of the year
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Qualitative data can be verified through quantifiable measures, such as noting repeating patterns of similar behaviour within a context.
For example, many people choose to add broccoli to their meal for its taste as well as for its added nutrients.
And you may conclude the concert you’re at is well attended based on scanning the venue, the long lineups to the bathroom, and the merchandise being sold out.
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Lean Research plan: outlines the design research efforts necessary to discover the needs lurking below the surface problem. Prompts: How will you investigate the problem or user need? Where will you observe and interview your target customer/end-user in your research?
Research Methods, Objectives and Outputs: outlines the desk and qualitative research methods that will be used to investigate the problem space to discover needs. Each method will have an objective and an expressed output.
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Place: Find a comfortable spot that allows for observation from a distance. With a notebook in hand, write notes on how people arrive and leave. If possible, use a camera or smart phone to capture objects and specifc locations.
People: Observe with fresh eyes. Take notes on what you see (as facts), and what you interpret (as interpretations). If possible, use a camera or smartphone to take images.
Patterns: While observing and taking notes and photos, look for patterns of behaviour shared across different types of people, objects and/or specifc locations.
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People: the demographics, roles, behavioural traits, and quantity of people in the selected environment.
Objects: the items people are interacting with, including furniture, devices, machines, appliances, tools, etc.
Environments: the visual observations about the place and space (i.e. architecture), lighting, furniture, temperature, atmosphere, etc.
Messages: the words and language overheard, and the environmental messages or signage.
Services: the organization’s offers (as services) which the target population is interacting with, within the selected feld study context.
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Sift through observed facts: Take time individually to sift through your own data and highlight some key observations as facts. . Identify each key fact as one datum and add to a data sorting board (e.g. physical or digital whiteboard). ‘I enjoy grocery shopping as an escape from the busy household’
Sift through interpreted facts: Sift individually through the interpreted facts, which are also called assumptions. These usually combine one’s personal experience or tacit knowledge of what was seen or heard, and are important contributions to the data set.
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Once the teams have generated a few problem statements, each member should vote on one problem statement that best refects the needs discovered from the data analysis process.
It’s recommended that teams employ the technique of dotmocracy, where each member of the team has two votes. Each member selects their top two statements. The statement with the most votes is selected and proceeds to a round of peer or stakeholder feedback.
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Framing is the process of defining an issue, problem, or context that influences how it’s perceived and evaluated.
Framing is important in explaining or making sense of an issue, context, or problem and is influenced by personal narratives and conceptual metaphors.
This framing effect is a well-researched cognitive bias in decision-making, and its effectiveness depends heavily on how the issue, problem, or question is presented.
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How we frame the question is critical in solving problems that seek divergent, novel and innovative solutions.
The most effective way to overcome this cognitive bias is to frame the question or problem differently and seek out individuals with different perspectives.
This strategy is all about reframing, a process of identifying and then changing the way an issue, problem or situation is viewed. The reframing effect enables biases and perceptions to be challenged and potentially changed.
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IDEAS CURATED BY
An effective communicator and business analyst with an inquisitive mind, strong analytical, problem-solving, and decision-making skills
CURATOR'S NOTE
“Business Design is like therapy for your business”— Starbucks executive
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