Generating & Evaluating Ideas

Foundations of Business Development - NIT Northern Institute of Technology / TUHH, Hamburg · part of my Technology Management MBA · study notes for revision.

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The last chapter was about spotting opportunities - reading trends, connecting dots, noticing gaps. This chapter is about the next two moves: turning a spotted opportunity into a pile of concrete ideas, and then filtering that pile down to the few worth betting on. These are two very different mental jobs, and the biggest mistake is to run them at the same time.

Tip

The one rule for the whole chapter: generate widely, then evaluate ruthlessly. First open up and chase many diverse ideas with judgement switched off. Then, in a separate step, switch judgement back on and hunt hard for the reasons each idea will fail. Mixing the two - criticising ideas as they are born - kills good ideas before they can grow.

1 · Generating ideas: diverge first, then converge

Creativity in business is not a lightning bolt that strikes the lucky. It is a process you can run on purpose. That process has two phases that must stay separate:

• Divergent thinking - spread out. Chase quantity and variety, welcome the odd and the impractical, build on other people’s half-ideas. No criticism allowed.
• Convergent thinking - narrow down. Now you sort, cluster, compare and pick. Judgement is welcome here.

Divergemany ideas · wild · no judgement

→

Cluster & combinegroup similar, merge, build on

→

Convergecompare, filter, choose

The two-beat rhythm of idea work. The whole of Section 1 lives in the amber box; Sections 3 and 4 live in the green one.

Before any technique works, you have to silence the counter-creative voices we all carry - the little rules in our heads that shut ideas down: “there’s only one right answer”, “be practical”, “that’s not your area”, “don’t be foolish”, “I’m just not creative”. Naming them is half the battle; a good facilitator bans them out loud at the start of a session.

A toolbox of creativity techniques

There is no single “best” method - each suits a different group, problem and time budget. Here are the workhorses:

BrainstormingBrainwriting / 6-3-5Six Thinking HatsSCAMPERAnalogies / lateral thinkingMorphological boxMind mappingUser observation

A working set of divergent-thinking techniques. Pick by group size, time available and how “technical” the problem is.

Technique	How it works in one line	Best when…
Brainstorming	A group calls out ideas aloud, fast, building on each other, under strict “no criticism” rules	You have a skilled moderator and an open, non-hierarchical group
Brainwriting (6-3-5)	Six people each write 3 ideas on a sheet in 5 minutes, then pass the sheet on and build on the neighbour’s ideas	Larger or unequal groups (shy vs dominant people); short time; no moderator
Six Thinking Hats	Everyone examines the problem from one fixed role at a time - facts, feelings, benefits, cautions, creativity, process	You need a complete, conflict-free discussion and a decision at the end
SCAMPER	A checklist of prompts on an existing product - Substitute, Combine, Adapt, Modify, Put to other use, Eliminate, Reverse	You want to push variations out of something that already exists
Analogies / lateral thinking	Borrow a proven solution from a distant field and transfer its principle to your problem	The problem is hard and well-defined, and high novelty is required
Morphological box	List the key attributes of a solution in rows, options per attribute in columns, then combine one option from each row	The design space is clear and you want to sweep all combinations systematically

A few things worth remembering about the table:

• Brainstorming’s rules are the whole point. Go for quantity, welcome wild ideas, no criticism during the session, and build on others’ ideas (“yes, and…”). Break those rules and it collapses into an ordinary meeting where the loudest voice wins.
• 6-3-5 fixes brainstorming’s social problems. Because ideas are written, not shouted, quiet people contribute as much as loud ones and there’s no pressure to conform - you get many ideas fast. The cost: it’s less lively, and the first idea written on a sheet can anchor the ones that follow.
• Analogies are how a lot of real breakthroughs happen - shark skin becoming a low-drag swimsuit, a termite mound’s cooling structure inspiring a building’s air flow. The hard part is reaching far, structural analogies rather than obvious surface ones.
• The morphological box is loved by engineers because it is systematic - but “garbage in, garbage out”: if your attributes are sloppy, you just generate a mountain of nonsense combinations.

A quick worked example of the analogy method, so it isn’t just an abstract prompt. Say the problem is “how do we get better shock-damping into a running shoe?” Step one: state it. Step two: ask where else do people solve hard damping problems? - think car suspensions, building foundations in earthquake zones, even how a cat’s paw absorbs a landing. Step three: pull an interesting principle from one of those distant fields. Step four: adapt it back into a sole. The distance is the value - a “far” analogy hands you a solution your competitors, all staring at shoes, would never find.

Running a divergent session well

The technique matters less than the discipline around it. A session that produces real variety usually follows the same beats:

1. Frame one sharp question. Vague prompts get vague ideas. “How might we serve a great variety of affordable food to all students without long queues at rush hour?” beats “improve the canteen”.

2. Ban the killers out loud. State the rules before you start: no criticism, quantity over quality, wild is welcome, build on others. Make it socially safe to be silly.

3. Diverge in silence first. Start with a written round (brainwriting) so quiet people and the loudest person contribute equally - then open it up to spoken build-on.

4. Push past the obvious. The first twenty ideas are the clichés everyone shares. The interesting ones come after the well runs dry - so keep going deliberately past that point.

5. Only now converge. Cluster similar ideas, merge overlaps, and let people mark the ones that inspire them (dot voting). Selection is a separate beat - never interrupt divergence to judge.

Note

Observe, don’t only ask. Many real needs are latent - customers can’t put them into words, so a survey never surfaces them. Watching people struggle in their real context (“empathic design”, the heart of design thinking) reveals workarounds and frustrations they’d never think to mention. Coca-Cola watched customers mix Sprite with cherry at its Freestyle machines for years, then launched Sprite Cherry - a hit built purely on observation.

2 · Open innovation & crowdsourcing: ideas from outside

Here is an uncomfortable truth: the best idea is almost never inside your own building. No matter how clever your R&D team, the knowledge relevant to your problem is distributed across thousands of people outside the firm - users, hobbyists, suppliers, experts in other fields. Open innovation simply means deliberately reaching for that outside knowledge instead of relying on internal ideation alone.

Closed innovation inside-only

• Ideas come from your own R&D and staff
• Limited by the firm’s existing mental models
• Prone to “not invented here” and local search - looking only where you already know
• Small, homogeneous pool of contributors

Open innovation outside-in

• Ideas drawn from users, communities and crowds
• Taps distributed knowledge across many fields
• Lead users have already built solutions for needs the mass market will feel later
• Huge, diverse pool - more variety, more surprise

Why external sources so often beat internal-only ideation: variety and distributed knowledge. The interesting ideas live at the edges you can’t see from inside.

The main channels for pulling ideas in from outside:

Channel	What it is	Why it works
Lead users	Users who face a need ahead of the market and often build their own fixes	Their homemade solutions preview tomorrow’s mainstream product
User communities	Forums and groups where enthusiasts swap problems and hacks	A living, searchable stream of unmet needs and workarounds
Idea contests	You post a challenge and reward the best submissions	Cheaply mobilises many diverse minds against one framed problem
Crowdsourcing platforms	Broadcast a task to a large, undefined crowd online	Reaches skills and perspectives you don’t employ and couldn’t find

Think of these as an outside-in funnel: the further out you reach, the larger and more diverse the pool - and the more surprising the ideas that come back.

Lead usersahead of the market

already built their own fix

Communitiesenthusiast forums

needs & hacks, in the open

Idea contestsframed challenge

many minds, one problem

Crowdsundefined, global

skills you don’t employ

From narrow-and-known to broad-and-unknown. Each step out trades control for reach and variety.

Tip

“Broadcast” beats “search” when you don’t know where the answer is. Instead of hunting for the one expert (local search, slow, and you may look in the wrong place), you broadcast the problem widely and let whoever holds the answer step forward. It flips the search around - the knowledge finds you. The newspaper simulation in the module makes the same point: running an external idea contest or hackathon often out-performs another internal boot camp.

None of this replaces internal work - it feeds it. The crowd hands you raw variety and signals about real needs; your team still has to judge, refine and combine those signals into something buildable. Open innovation widens the funnel at the top; the evaluation in the next two sections narrows it at the bottom.

3 · Evaluating ideas: predicting the innovation killers

Now judgement switches back on. The single most useful habit here is deliberately looking for reasons the idea will fail - playing devil’s advocate against your own baby. These reasons are the innovation killers, and they are dangerous precisely because they are quiet and easy to miss while you’re in love with the concept.

The classic cautionary tale is the Segway: brilliant technology, backed by top Silicon Valley investors and admired by experts, forecast to sell half a million units a year. It flopped. The killer wasn’t the tech - it was that most people found riding one uncool and a bit dorky, and it only created real value in narrow “island” contexts (tours, warehouses, campuses). A killer nobody stress-tested up front.

Caution

Assume the value proposition is fine - then go hunting anyway. The exercise is: suppose customers genuinely benefit and see the benefit. Now, what could still kill the business? Don’t get lost in minor side-issues; focus only on factors big enough to sink the whole case.

Here is a checklist of the common killers and the question each one forces you to ask:

Killer	The question it raises
No real customer need	Is there an urgent, unmet problem here - or a solution looking for a problem?
Weak value proposition	Is the benefit clearly better than what customers use today, enough to justify switching?
Strong incumbents / substitutes	Can big established players or cheap substitutes crush or copy us?
Adoption barriers & switching costs	Must customers change habits, learn a lot, or rewire processes to adopt?
Unclear business model	Do we actually know how we make money - and can we capture enough of the value we create?
Dependence on complements	Do we rely on other technologies, partners or infrastructure that may not show up?
Regulatory hurdles	Do laws, certification or approvals block or badly slow us (medical, data/GDPR, safety)?
Team gaps	Does the team lack a critical skill - tech, finance, sales - that the venture needs?

A pre-mortem checklist. Run every serious idea through all eight; a single unanswered killer can be fatal, so be honest early rather than sorry later.

The useful reframe is to score an opportunity on two axes at once - its upside potential and its challenge to pull off:

• Potential - how likely is fast adoption (urgent unmet need, clearly better, easy to adopt) and how much value can we capture (market size, growth, margins, willingness to pay)?
• Challenge - how hard is it to build (tech risk, cost, time, certification, dependencies) and how hard is it to enter the market (channels, sales cost, competition)?

A Gold Mine is high potential and low challenge; a Moon Shot is high potential but brutal to execute; a Quick Win is easy but modest; the low-low corner is simply Questionable - and usually a no.

4 · Founders vs investors: two lenses on the same idea

An idea that passes the killer checklist still gets judged twice, through two different pairs of eyes. A founder screens for “can and should I do this?” An investor screens for “will this return my money many times over?” Knowing both lenses lets you pitch to each on its own terms.

The founder’s lens should I pursue it?

• Fit with my skills, knowledge and genuine passion
• Feasibility - can it actually be built with what I can reach?
• Resource needs - money, people, time I’d have to commit
• Market size - is the prize big enough to be worth my life for years?

The investor’s lens will it return the fund?

• Team - complementary, non-redundant, flexible (“team, team, team”)
• Market size & growth - big and riding a strong trend
• Defensibility / moat - a real USP; no USP, no investment
• Traction & scalability - evidence it works, and it grows without costs growing as fast
• Exit potential & risk/return - a credible path to sell or IPO; upside worth the risk

Same idea, two filters. Founders weigh personal fit and feasibility; investors weigh team, moat, scale and exit. A pitch that only answers one set of questions loses.

Two investor prejudices worth internalising: they love scalable, growth-heavy businesses riding a trend, and they dislike sales- and marketing-intensive businesses where a big slice of every euro goes on customer acquisition - unless high prices can cover it. And above all, they bet on the team: investors will always probe the knowledge and resources the team does not yet possess.

Note

The Andrea Kaneb case - the investor’s lens in action. In the module’s case study, an MBA student assesses whether to found Parlay, a system to help hearing-impaired people follow conversations in noisy restaurants. Seen through the investor filter, the strengths and gaps line up neatly: a large, growing market and a founder with deep first-hand insight into the problem - but an incomplete team (she openly lacks finance and software-development partners), an unproven concept (no prototype yet), an undecided business model, and looming regulatory questions (FDA / FCC). Her real decision isn’t “is the idea nice?” - it’s a hard Go / No-Go: which critical uncertainties must she resolve before family-and-friends money, and which before she can credibly ask professional investors to back her. That is the investor’s lens turned on your own venture. (We reference the case only to illustrate the lens - the details stay in the case itself.)

The mindset: separate the two jobs

If you take one thing from this chapter, take the discipline of keeping generation and evaluation apart in time:

1. Generate widely. Run a divergent session with judgement off - quantity, variety, wild ideas, building on others. Reach outside the firm for most of your best material.

2. Then evaluate ruthlessly. Switch modes. Play devil’s advocate, hunt the killers on purpose, and be honest early - a killer found in a workshop is cheap; one found after launch is fatal.

3. Judge through both lenses. Ask the founder’s question (fit, feasibility, resources, market) and the investor’s question (team, market, moat, traction, scale, exit) - and pitch to each accordingly.

Revision summary

Tip

The one-minute recap

• Generate widely, then evaluate ruthlessly - and never at the same time. Diverge (quantity, no criticism) → cluster → converge (filter, choose).
• Creativity is a process, not luck. Silence the counter-creative voices, then use the right tool: brainstorming (needs a moderator), brainwriting / 6-3-5 (large or unequal groups), Six Thinking Hats, SCAMPER, analogies (far, structural), the morphological box. Observe latent needs, don’t just ask.
• Open innovation & crowdsourcing pull ideas from outside - lead users, communities, idea contests, crowdsourcing platforms. They win because relevant knowledge is distributed; broadcasting a problem beats searching for the one expert.
• Predict the innovation killers by playing devil’s advocate: no real need, weak value prop, strong incumbents/substitutes, adoption barriers & switching costs, unclear business model, dependence on complements, regulatory hurdles, team gaps. Remember the Segway.
• Two lenses: the founder screens for fit, feasibility, resources and market size; the investor screens for team, market size & growth, defensibility, traction, scalability and exit. The Andrea Kaneb / Parlay case shows the investor’s Go / No-Go lens turned on your own venture.

Next: Creating Customer Value → - what “value” really means to a customer.