Business Design Thinking and Doing - Deepstash
Business Design Thinking and Doing

Business Design Thinking and Doing

Angèle M. Beausoleil

39 ideas


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Don`t confuse invention with innovation

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.


249 reads

Demystifying Innovation

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’.


182 reads

New and Evolved leadership skills

  • Problem diagnosis skills: To effectively solve problems, you must first learn how to diagnose, define, and frame the right problems
  • Navigating complexity skills: Today’s and tomorrow’s leaders need to develop the ability to deal with complexity and ambiguity and learn to adapt to changing needs of customers, contexts and climates.
  • Communication skills: Those who have the willingness and courage to communicate their thoughts and ask more questions and solicit ideas from their team will prevail.
  • Innovation-readiness: Those who are open to new experiences, accept failure as pre-condition.


167 reads

Four stages of Design-driven innovation

  • First stage: initiating a project based on a problem hypothesis, creating a project (design) brief, and developing a research plan to investigate the assumed problem.
  • Second stage: investigating and validating the needs associated with the problem hypothesis.
  • Third stage: integrate insights and ideas into prototypes, frame and reframe the problem to solve, and test prototypes with external and internal stakeholders.
  • Fourth stage: designing, testing and implementing final prototypes, and then designing and delivering a solution to the problem


151 reads

Business Design practices

  1. Strategic Design: design principles and practices to guide strategy development and implementation towards innovative outcomes. 
  2. Business Model Design: designing or redesigning of an organization’s or division’s business model to create value and prosper.
  3. Employee Experience Design (EXD): design methods to designing programmes and experiences that employees desire. 
  4. Service Design: design principles and methods to service planning, development and implementation.
  5. Customer Experience Design (CXD): marketing principles and design methods to designing product/service experiences


59 reads

Examples of design-as-process activities

  • What are we designing? (R&D, Sales, Marketing, HR, Management and Finance)
  • Who are we designing for? (Marketing and HR=customer facing)
  • Why are we designing? (Strategy and CEO)
  • How will we design it? (Production/Operations and Finance)
  • How will we know if we succeeded? (Management and Finance)


47 reads

Four basic types of designed business innovations

  • Product/Service: changing what you do or offer (e.g. mobile phone, OXO Company - Good Grip series)
  • Position/Market: changing who consumes it (e.g. new user)
  • Process: changing how you do it (e.g. Lean, Six Sigma, etc.)
  • Paradigm: changing why it matters and what value it creates (e.g. platform (iTunes) and organizational culture (fat or decentralized)


45 reads

Innovation as communication process

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.


30 reads

Human-Centred Design Mindsets

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.


30 reads


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.


31 reads

The key competencies associated with a design mindset and innovativeness

  • Communication skills: first listen and observe, and then speak, write, and interact effectively with others.
  • Perspective-taking skills: take on someone else's point of view when thinking and acting.
  • Analytical and critical thinking: analyze (processing data and facts into information), evaluate (questioning bias and interpretation), and conclude (converging on a decision or statement).
  • Strategic thinking: analyze critical factors and macro variables, and to synthesize information into an intent or vision for a course of action.
  • Creative problem-solving: think creatively about a problem


30 reads

Divergent and Convergent thinking practice

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.


26 reads

Challenge briefs

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.


22 reads

Key elements of innovation design brief

  • Problem hypothesis: summarizes a situational or contextual analysis of the proposed problem and target end-user population. 
  • Stakeholder map: key individuals or groups that have a stake in, directly influence, or are impacted by the assumed problem.
  • Stakeholder motivations: the goal-oriented drivers behind human decision-making and action
  • Target end-user population: a group that shares similar characteristics and is an intended audience for product, service, or process design research.
  • Project team schedule: who will lead which task on which day and over what timeframe.
  • References and sources


22 reads

Guiding Questions (part 1)

  • Problem hypothesis: 

What problem(s) are you trying to solve? (as a problem hypothesis)? What customer problem(s) are you trying to address? (as needs)?

  • Stakeholder map:

Who is most interested in solving this problem? Who is most influential in solving this problem?

  • Stakeholder motivations: 

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?


24 reads

Guiding Questions (part 2)

  • Target end-user population:

Who is our intended customer/end-user for this problem/challenge? Why do they buy? Where are they located?

  • Project team schedule:

 Who will participate in the innovation project? What is the timeline? Provide details of team members and associated tasks, activities (be feasible and realistic).


30 reads

Quantitative research

  • Aim: to generate confrmatory insight from structured datasets
  • Deductive methods: survey, questionnaire, poll and lab experiment
  • Inquiry: seeks to answer tangible ‘what is’ or ‘what was’ queries: e.g. ‘how much’, ‘how many’, ‘where’ and ‘when’
  • Value: numbers-driven decision-making
  • Output: transactional data patterns, statistics and broad segment-level trends.


14 reads

Qualitative research

  • Aim: to generate exploratory insight from unstructured datasets
  • Abductive methods: interview, focus group and observational or feld research
  • Inquiry: seeks to answer narrative ‘what, how and why’ or ‘what if’ queries below ‘where’ and ‘when’
  • Value: needs-driven decision-making
  • Output: narrative data patterns, latent needs and niche population-based insights


11 reads

Qualitative research data is often referred to as unstructured, narrative, or ‘thick description’ data

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)


12 reads

Big Data with Thick Data

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.


12 reads

Big data

  • Big data is a combination of structured and semi-structured data collected by organizations that can be mined for information, machine learning, and predictive modeling.
  • Big data draws broad patterns from massive amounts of data from large end-user or customer samples
  • Big data is used for informed decision-making to improve operations, customer service, marketing campaigns, generate revenue models, and proft-oriented strategies
  • Big data aims to answer ‘what’ happened or happens based on transactional events


11 reads

Thick data

  • Thick data is unstructured data in the form of thick description or narratives, that is mined for insights on human behaviour
  • Thick data draws deep human-centred patterns from small end-user or customer samples
  • Thick data is used for insightful decision-making to better understand people, their contexts, motivations and behaviour, and to design desirable products, services and impactful strategies
  • Thick data aims to answer the ‘why’ behind what consumers do or think


11 reads

Needs analysis

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)


10 reads

Need finding

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)


10 reads

Need finding research (and analysis) aims to generate

  • Observations: Both ‘facts’ and ‘interpretations’. Facts describe a situation or object as explicitly seen or heard. Interpretations describe a situation that is judged based on tacit knowledge of a similar context.
  • Findings: ‘Summarized facts’ that propose common meanings or themes refecting the facts, based on patterns and/or bias.
  • Insights: Synthesized interpretations of the facts, findings, and patterns refecting a deeper understanding of the people and situation or context


10 reads

Observation as fact

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.


10 reads

Observation as interpretation

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


12 reads

Qualitative data can be verified through quantifiable measures

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.


12 reads

Creating a Lean Field Research Plan

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.


9 reads

Preparing for Field-Based Research

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.


9 reads

POEMS framework

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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  • A need is something that is necessary; a critical tension with a present state
  • Need owners focus on the present state, since it is something that is essential or very important; wanted or required
  • A need requires immediate action, since it demands satisfaction or resolution
  • Needs can be diffcult to detect. Unlike a problem, a need is something that may kill you if you don’t address it. For example, protecting your bare feet in the snow to avoid frostbite is a need


9 reads


  • A problem is an issue; a tension between the present, and a desired future state
  • Problem owners focus on the desired state since it involves resolving issues associated with goals, values and preferences
  • A problem may or may not be solved, based on priorities and the type of unsatisfed needs
  • A problem is surfaced as something that costs time, money or energy. The solution must be an improvement over simply living with the problem. For example, a problem is that you want new boots for use in the snow


9 reads

Data Sorting: Sift, Sort and Label (Step 1/3)

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. 


9 reads

Data Sorting: Sift, Sort and Label (Step 2-3/3)

  1. Sort both observed and interpreted facts: Sorting involves moving the key data points into thematic groups based on themes and/or patterns that are observed individually and as a team.
  2. Label facts into themes: Labelling involves questioning each theme or pattern that you have surfaced and sorted, which are supported by both facts and interpretations.


9 reads

Вraw insight from your investigation efforts (Example)

  • We observed that some customers combine their food shopping with personal ‘me time’.
  • We learned that some customers view the grocery store as an escape from their daily routine, where they can spend time listening to their favourite playlist or podcast, while also getting food for their family.
  • We infer that remote working grocery shoppers need an escape from their busy lives, and want an experience that combines a mini getaway with practical meal planning.


6 reads

Setting up the feedback loop for the problem statements.

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.


7 reads

What is Framing?

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. 


6 reads

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.


7 reads



An effective communicator and business analyst with an inquisitive mind, strong analytical, problem-solving, and decision-making skills


“Business Design is like therapy for your business”— Starbucks executive

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