A Methodology Case Study
No. 01  ·  Discovery & Innovation

Turning Ambiguous
Business Problems Into
Actionable Recommendations

or, how a molecular biologist learned to run discovery —
a study of method, not secrets

✦

Teodora Malešević

Innovation Manager · Fortune 500 enterprise
Belgrade  —  Enterprise Transformation & Opportunity Discovery
The Premise

An unlikely combination,
assembled on purpose

Most business problems do not arrive as problems. They arrive as ambiguity — a hunch that something is possible, or a quiet suspicion that something is wrong. Nobody has written the brief yet. My work begins precisely there, in the fog, before anyone can agree on the question.

What I bring to that fog is a training few people combine in one head. Molecular biology taught me to sit with uncertainty and let evidence, not opinion, settle an argument. SaaS taught me how software actually gets built, adopted, and paid for. Product taught me to trade ideal against feasible. Innovation taught me to look past the present. And brand taught me that none of it matters if you can't tell the story clearly enough for someone to act on it.

IMolecular
Biology
IISaaS
IIIProduct
IVInnovation
VBrand

Five disciplines that rarely share a résumé — and the reason ambiguity doesn't frighten me.

The Discovery Workflow

Ambiguity in, decision out

Six repeatable movements — the same pipeline behind every engagement.

01
Situation
Frame
02
Stakeholders
Map
03
Research
Evidence
04
Workshops
Converge
05
Synthesis
Meaning
06
Recommend
Decide
An Anthology

Three initiatives, one method

The same six movements, played in three different keys.

Feature IAI

AI-Enabled Opportunity Assessment

The Ambiguity

How could AI make a core, document-heavy assessment process faster and more efficient — and improve collaboration with external partners, giving them clearer visibility into progress along the way?

The Insight

AI belonged in the loop with people, not in the driver's seat — an assistant, not an autopilot. The value sat in a few targeted, high-leverage tasks, not in sweeping automation.

The Decision

A clearly scoped, AI-enabled external-facing application — designed to replace six steps done manually today — concrete enough to evaluate, cost, and put in front of decision-makers.

Feature IIOPS

Global Operational Transformation

The Ambiguity

Resourcing and capacity planning across the whole organisation: many functions, countless unknowns, real technology limits. The question underneath — how do you put the right people on the right task at the right time, never over- or under-staffed, and free them from manual work for the decisions that actually need judgment?

The Insight

Mapping the critical path made the true bottlenecks visible for the first time and the end-to-end process finally legible — which brainstorming turned into an ideal future-state map in three phases.

The Decision

Not one answer but several paths — process change paired with digital enablement across a set of targeted solutions, sequenced from near-term wins to longer-horizon bets.

Feature IIIFUTURE

Future-State Innovation Initiative

The Ambiguity

What should we do next — the next big move no competitor had made yet, the one that would make us pioneers with a durable strategic advantage?

The Insight

The differentiator wasn't a new technology at all — it was a capability we already held in-house. The answer had been there all along; it only needed the right people connected and the right dots joined. A new offering: modest cost, outsized gain.

The Decision

Run a feasibility and validation study to pressure-test the opportunity canvas's numbers and assumptions — and judge whether the moment is right, or still too early to move.

Chapter I
01
Situation
Frame the ambiguous space

Agree on the question before chasing the answer

The first mistake in discovery is solving the problem you were handed instead of the one that actually exists. "We should do something with AI" is a symptom, not a problem statement. I reframe it into a sharp, testable question — what outcome, for whom, measured how — and capture it on a single canvas before discovery earns the right to begin.

PROBLEM WHO IT AFFECTS CURRENT ALTERNATIVE VALUE HYPOTHESIS SUCCESS METRIC KEY RISKS

Fig. 1 — Opportunity canvas · shaping a vague ambition into a bounded, testable hypothesis

In Practice — Fortune 500 enterprise

Across enterprise transformation work, opportunities routinely arrived as broad ambitions rather than defined initiatives. I translated these ambiguous problem spaces into evidence-based hypotheses with a clear value thesis — the difference between an interesting idea and a fundable one.

Typical Deliverables
Problem statementReframed hypothesis Opportunity canvasSuccess criteriaScope boundaries
Chapter II
02
Stakeholders
Map the people & the incentives

Every problem is really a room full of different problems

The same opportunity looks like one thing to a scientist, another to finance, and something else to the executive who funds it. Before gathering a single data point, I map who decides, who delivers, who's affected, and what each is quietly optimising for — plotting them by influence and interest so effort lands where it counts. Most of the work is translation between people who don't share a vocabulary.

KEEP SATISFIED MANAGE CLOSELY MONITOR KEEP INFORMED INFLUENCE → INTEREST → Exec sponsor SMEs Finance End users Partners

Fig. 2 — Stakeholder map · influence × interest, deciding where attention is worth spending

In Practice — Fortune 500 enterprise

I partnered with senior leaders, SMEs, finance, technology, and external partners across a global organisation — aligning multi-functional groups whose priorities and vocabularies rarely matched, and turning that alignment into a shared basis for decisions.

Typical Deliverables
Stakeholder mapDecision / RACI map Interview planAlignment summary
Chapter III
03
Research
Gather evidence from three directions

Opinion is cheap; triangulated evidence is not

I refuse to rely on a single source of evidence. I triangulate the market (what's possible, what competitors do), stakeholders (interviews that surface the real constraints), and data (patterns that support the hypothesis or quietly demolish it). The point isn't to accumulate confidence — it's to find the fastest, cheapest way to be proven wrong before anyone commits real money.

Market Stakeholders Data Insights TRIANGULATED Validated direction

Fig. 3 — Triangulation · three independent signals converge into one defensible read

In Practice — Fortune 500 enterprise

I designed validation frameworks combining market and competitive research, stakeholder interviews, experiments, proofs-of-concept, and prototypes — assessing demand, feasibility, financial viability, and organisational readiness to systematically reduce execution risk.

Typical Deliverables
Market landscapeCompetitor analysis Stakeholder interviewsPrototype / POCValidation report
Chapter IV
04
Workshops
Think together, on purpose

A well-run room decides in a day what email debates for a month

Some of the best evidence isn't found — it's produced when the right people think in one room. I run workshops as structured events: genuine divergence where every function is heard, then disciplined convergence on the few options worth pursuing. Good facilitation is quiet work — protecting the dissenting voice and ending with a decision, an owner, and a next step, not a warm feeling.

PROBLEM SPACE diverge ▸ converge SOLUTION SPACE diverge ▸ converge EXPLORE THE PROBLEM EXPLORE THE OPTIONS

Fig. 4 — Double diamond · open wide to explore, close hard to decide — twice

In Practice — Fortune 500 enterprise

I facilitated cross-functional ideation, solution design, and prioritisation across global, multi-functional groups — running assumption-testing sessions that converged diverse teams on the highest-value opportunities and the most credible ways to pursue them.

Typical Deliverables
Workshop designFacilitated sessions Idea shortlistPrioritised options
Chapter V
05
Synthesis
Turn mess into meaning

The hardest step is making the complexity disappear

By now I'm holding interviews, market data, workshop outputs, and experiment results — a pile of contradictory inputs. Synthesis resolves them into one coherent narrative: what we believe, how confident we are, what it implies. Plotting options on value against complexity lets them be compared honestly rather than argued emotionally. Good synthesis makes the conclusion feel obvious — even though arriving at it was anything but.

QUICK WINS BIG BETS FILL-INS AVOID VALUE → COMPLEXITY → Opp. A Opp. B Opp. C Opp. D

Fig. 5 — Prioritisation matrix · value vs. complexity turns debate into a defensible shortlist

In Practice — Fortune 500 enterprise

I directed opportunity assessment from initial hypothesis through business-case development — building prioritisation frameworks that balanced value, feasibility, and risk, and distilled complex, multi-source findings into clear strategic direction.

Typical Deliverables
Insight synthesisPrioritisation matrix Decision frameworkOptions assessment
Chapter VI
06
Recommendations
Make the decision easy to make

A recommendation is only finished when someone can act on it

Discovery that ends in a report has failed. The deliverable is a decision — a defensible recommendation a busy executive can say yes or no to with confidence. I author investment cases, roadmaps, and explicit go / no-go proposals, naming the risks plainly and making the trade-offs legible. The best compliment my work gets isn't "interesting" — it's a signature and a budget line.

BUSINESS CASE 1 Problem & context 2 Options considered 3 Recommendation 4 Financials & ROI 5 Risks & assumptions 6 Roadmap & next steps

Fig. 6 — Business case outline · the structure that turns discovery into a fundable decision

In Practice — Fortune 500 enterprise

I contributed to opportunity assessments representing over $50M in evaluated revenue potential, plus multi-million-dollar efficiency impact — authoring executive recommendations, investment cases, and go / no-go proposals presented to senior leadership to inform prioritisation and funding decisions.

Typical Deliverables
Business caseExecutive presentation Transformation roadmapDecision frameworkGo / No-Go recommendation
Where This Travels

One method, four rooms

The instinct — ambiguity in, decision out — doesn't care what the room is called.

I

Innovation Consulting

Shaping fuzzy possibilities into evaluated, fundable opportunities.

II

Business Analysis

Turning stakeholder needs and evidence into clear requirements and options.

III

Product Strategy

Trading value against feasibility to decide what's worth building, and why.

IV

Workshop Facilitation

Getting the right people to a real decision, not just a good conversation.

In Closing

Good discovery isn't about finding answers.
It's about making the right decision inevitable.