The hardest question in competitive intelligence is not "what is our competitor doing?" It's the question that comes before it: "who are our competitors?"
That sounds simple. It isn't. Most organizations operate with a narrow, static view of their competitive landscape — the three or four companies they've always tracked, the compounds they've always benchmarked against. That view is comfortable, and it's dangerous. The competitors you don't see are the most dangerous ones.
Competitor identification is the foundational step in competitive dynamics. Get it wrong, and everything downstream — your threat assessments, your positioning, your launch strategy — is built on incomplete information. Get it right, and you give your organization a structural advantage: the ability to see the full competitive picture before decisions get made.
A competitive landscape analysis is the CI deliverable that makes this visible. It maps every relevant competitor by development phase, mechanism of action, threat level, and timeline — and presents it in a format that a brand team or executive can act on in a single meeting. It's one of the six core CI deliverables, and in my experience, it's the one that most directly shapes strategic decisions.
This guide covers the full process: defining competitive boundaries, choosing a framework for identifying competitors, building the landscape step by step, selecting the right visualization format, and keeping it current. The methodology applies to any industry, but the examples draw on pharmaceutical CI because that's where the competitive dynamics are most complex — multiple development phases, overlapping mechanisms of action, regulatory milestones, and competitive sets that shift with every new data readout.
For the broader CI framework this deliverable sits within, see What Is Competitive Intelligence?. For the pharma-specific application, see Pharma Competitive Intelligence.
Building a competitive landscape is a structured process, not a one-off analysis. From initiation to delivery, expect a 3–4 week workflow:
Week 1: Define scope and gather requirements. Which therapeutic area, indication, or market segment? What decisions will this landscape inform? Who are the stakeholders? This is where you align the landscape to specific Key Intelligence Questions — the landscape should answer something, not just document everything.
Week 2: Research and categorize. Systematic secondary collection across clinical trial registries, regulatory filings, investor presentations, conference abstracts, and published literature. Organize competitors by mechanism of action class, development phase, and competitive positioning.
Week 3: Analyze and assess. Apply threat-level methodology. Validate competitor status. Identify gaps that require primary research follow-up. Build the visual format.
Week 4: Validate and deliver. Review with key stakeholders, incorporate feedback, finalize the landscape and any accompanying timelines or threat assessments. Establish the update cadence.
This timeline assumes you have a solid intelligence baseline. If you're building a landscape for a therapeutic area you haven't covered before, add one to two weeks for foundational secondary research.
The discipline is in the process. A landscape that takes three months to produce is stale before it's delivered. A landscape built in three days without proper sourcing gives false confidence. The 3–4 week window balances thoroughness with timeliness — and timeliness matters, because intelligence has an expiry date.
Before building the landscape, you need to decide who belongs in it. This is more complex than it appears, and it's where most competitive analyses go wrong. Research across management, marketing, and industrial organization economics identifies four distinct perspectives on competitor identification — each reveals competitors the others miss.
The most intuitive approach: competitors are all firms operating in the same product or geographic market. In pharma, this means all companies with compounds targeting the same indication. In technology, all companies selling the same category of software. In consumer goods, all brands on the same shelf.
This approach is useful for understanding industry structure, but it has a blind spot: it defines competition by product-market boundaries that may be too narrow or too broad. A pharma company tracking all anti-TNF biologics might miss a JAK inhibitor that's about to reshape the competitive dynamic. An enterprise software company tracking other CRM platforms might miss that their real competitor is a spreadsheet.
Not all firms in an industry compete equally. This perspective groups competitors based on similar strategic positions — comparable resources, capabilities, market approaches. Companies within the same strategic group tend to be more direct competitors than companies across groups.
This is particularly useful in industries with clear segmentation. In pharma, you might have a strategic group of large pharma companies with full commercial infrastructure competing in a specific therapeutic area, and a separate group of smaller biotechs with innovative science but limited commercial capability. The competitive dynamics within and between these groups are fundamentally different.
This one is uncomfortable but important. Competitors are partly constructed through perception. Managers build mental models of their competitive environment, and those models shape which competitors get attention and which get ignored.
The problem is that managerial mental models can be outdated, narrow, or biased. When managers' frames of reference don't match reality, competitive blind spots emerge. I've seen this happen — a team so focused on their direct competitors in one mechanism of action class that they completely missed a disruptive entrant from a different therapeutic approach. The competitor identification was driven by habit, not by analysis.
Research shows that geographic proximity also shapes mental models: companies tend to identify competitors that are geographically close, even when the most significant competitive threats are international. This is a particular risk for US-based teams that underestimate European or Asian competitors.
This perspective identifies competitors by analyzing who customers — physicians, patients, payers — see as alternatives. Customer-based competitor identification frequently reveals threats that industry-based analysis misses.
In pharma, a physician's treatment algorithm may position your product against options you wouldn't consider direct competitors: a generic in a different class, a non-pharmacological intervention, watchful waiting. These aren't competitive threats in the traditional pipeline sense, but they absolutely compete for the same patient population. Understanding how customers perceive alternatives gives you a competitive map that no industry analysis can provide.
Each perspective captures different parts of the competitive picture. The industry lens shows you the playing field. The strategic groups lens shows you who's playing a similar game. The managerial cognition lens reveals your own blind spots. The customer lens shows you who you're actually competing against in the minds of the people making treatment decisions.
Research on competitive dynamics — particularly the work on market commonality and resource similarity — shows that competitive tension is highest between firms that share both markets and resources. That's intuitive. But the research also shows that firms often fail to identify competitors that share resources but not markets, or markets but not resources. Those asymmetric competitors are precisely the ones that launch surprise attacks — entering your market with capabilities you didn't expect.
Relying on any single framework creates gaps. The organizations that build the most accurate competitive landscapes use multiple approaches — and they use the discomfort that comes from seeing unexpected competitors as a signal that their analysis is working, not failing.
I'll give you a practical example. A brand team I worked with was tracking eight competitors in the same MoA class. Their landscape was comprehensive within that boundary. But when we applied the customer lens — analyzing what physicians were actually prescribing as alternatives — we identified three additional competitors from adjacent classes that were capturing a significant share of new starts. None of those compounds appeared in the team's competitive tracking. All three turned out to be more relevant to their launch positioning than half the competitors they were already monitoring.
That's the value of multiple lenses. Not theoretical completeness — practical accuracy.
For how competitor identification feeds into structured competitor profiling, see Competitor Profiling.
With the scope defined and the competitor identification framework applied, the construction follows a systematic process.
Organize competitors by mechanism of action, development phase, and route of administration. In pharma, this is the structural backbone of any landscape. Group compounds by MoA class — for example, checkpoint inhibitors, CAR-T therapies, bispecific antibodies — and then sort within each class by development phase: preclinical, Phase I, Phase II, Phase III, filed, approved.
Outside pharma, the equivalent is organizing competitors by their core value proposition, go-to-market approach, or technology platform, and then by market maturity.
The class categorization determines how stakeholders will read the landscape. Get the grouping wrong — too broad, too narrow, or using categories that don't match how the market actually segments — and the landscape will confuse rather than clarify.
Not all competitors in the landscape represent the same type of threat. Direct competitors share the same mechanism of action or product approach and target the same patient population. Indirect competitors achieve similar outcomes through different mechanisms. Potential competitors are in adjacent spaces and could enter.
This distinction matters for threat assessment. A direct competitor with strong Phase III data is an immediate tactical threat. An indirect competitor with a novel mechanism that could redefine the treatment paradigm is a longer-term strategic threat. Both belong in the landscape. They don't belong in the same risk bucket.
The "differentiators vs. substitutors" distinction from competitive dynamics research captures this well. Differentiators compete within a strategic group — they offer similar products with incremental differences. Substitutors compete from outside the group — they offer fundamentally different approaches that could displace the entire category. Both are competitive threats, but the response strategies are different.
For each competitor, assign a threat level: High, Medium, or Low. The assessment combines three dimensions:
Clinical data strength. How robust is the competitor's efficacy and safety profile? How do their endpoints compare to yours? Are they running head-to-head trials?
Commercial capability. Does the competitor have the commercial infrastructure to launch and compete? A biotech with strong data but no sales force is a different threat than a large pharma with global commercial reach.
Timeline proximity. How close is the competitor to filing or launch? A Phase III competitor 18 months from filing is a more immediate threat than a Phase I competitor with similar data.
The weighting depends on context. For a pre-launch brand, timeline proximity matters most. For a launched brand facing lifecycle management decisions, clinical data strength and commercial capability drive the assessment.
For key competitors, develop timelines based on benchmark analog data. How long did similar compounds take to progress from Phase II to Phase III? What accrual rates are typical for the indication? What regulatory pathways are available?
Timelines should include uncertainty ranges — the best-case and worst-case scenarios for each competitor's progression. A timeline that shows a single date for each milestone creates false precision. A timeline that shows ranges gives decision makers the information they actually need: when could this competitor realistically reach the market, and what's the range of uncertainty?
The format determines whether the landscape drives decisions or decorates a slide deck. Four visualization formats serve different purposes:
A broad view of all compounds organized by development phase — preclinical through approval. Each compound is a unit, color-coded by MoA class or threat level.
When to use it: Executive summaries, portfolio reviews, and situations where the primary question is "how crowded is this space?" The funnel gives a clear, immediate sense of competitive density.
Compounds plotted by proximity to market — near-term threats in the center, long-term threats on the outer ring. The radar format emphasizes temporal urgency.
When to use it: Threat assessment presentations and launch planning, where the primary question is "what's coming first?" The radar is particularly effective when stakeholders need to prioritize competitive threats by timeline.
A milestone-based view with compounds on the vertical axis and time on the horizontal axis. Benchmarked milestones — IND filing, Phase III start, regulatory submission, expected approval — are plotted with uncertainty ranges.
When to use it: Clinical development planning and scenario analysis, where the primary question is "when will we face competition?" The timeline is the most analytically rich format because it forces explicit assumptions about competitor progression.
All competitors grouped by development phase in a stacked format, color-coded by threat level or MoA class. The stacked bar shows competitive density at each phase.
When to use it: Competitive landscape overviews for brand teams and strategic planning, where the primary question is "what does the competitive field look like across all phases?" The stacked bar is the most common format for competitive landscape deliverables because it balances comprehensiveness with readability.
The right format depends on the question the landscape needs to answer and the audience. For an executive who has 10 minutes, use the funnel or stacked bar. For a brand team in launch planning, use the timeline. For a threat assessment workshop, use the radar.
In practice, most CI programs develop the landscape in the stacked bar format as the primary deliverable and produce timelines as companion documents for specific competitor clusters.
The biggest risk in any competitive landscape is defining the boundaries too narrowly. Market definition drives competitor identification — and if you define the market too tightly, you systematically exclude the threats that matter most.
A pharma brand team tracking only same-class competitors — compounds with the same mechanism of action in the same indication — may miss several categories of competitive threat:
The practical principle: be expansive in thinking about possible kinds of competitors, then narrow deliberately based on strategic relevance. Start broad — capture everything that could conceivably compete for the same patient, customer, or budget — and then categorize by proximity and threat level. The competitors you exclude should be a conscious, documented decision, not an oversight.
The competitive readiness checklist provides a useful structure for boundary-setting. Ask three questions:
This three-layer approach — current, future, and guideline-driven — catches most of the blind spots that single-layer analysis misses.
Competitive boundaries aren't static. They shift with every new data readout, every regulatory decision, every M&A announcement. A competitor that was low-priority six months ago may become the primary threat after a strong Phase III readout. A company that wasn't in your landscape at all may acquire an asset that puts them directly in your competitive set.
Names change, companies get acquired, assets move between portfolios. A Phase II compound that seemed like a distant concern becomes an immediate threat when its parent company gets acquired by a global pharma with full launch capability. A pipeline asset in a different indication becomes a direct competitor when the sponsor initiates a label expansion study in yours.
The landscape must evolve as the competitive dynamics evolve. A landscape built once and updated never is worse than having no landscape at all — it creates false confidence.
The practical discipline: every time you update the landscape, ask two questions. First, has anything happened that changes the competitive boundaries? Second, is there a competitor we should be tracking that we aren't? If you're not asking those questions at every review cycle, the landscape hardens into a static document — and static competitive assumptions are how organizations get surprised.
A competitive landscape is only as useful as its last update. Building it is the hard part. Keeping it current is the discipline.
At minimum, review and update the competitive landscape quarterly. But the more important trigger is events, not calendar dates. Major competitive events that should trigger an immediate landscape update:
Use a coverage assessment matrix to ensure monitoring covers the full competitive set without blind spots. Map each competitor in your landscape against the intelligence sources covering them. If a high-priority competitor is covered by only one source, that's a vulnerability. If a competitor cluster has no dedicated monitoring at all, that's a gap.
AI-powered monitoring platforms have changed the economics of coverage. What used to require significant analyst time — scanning multiple databases, press releases, clinical trial registries, regulatory filings — can now run continuously at a fraction of the cost. The technology handles the detection. The analyst handles the interpretation. This is where the combination of AI and human expertise creates the most value in landscape maintenance.
The competitive landscape should be a living document — updated with each significant competitive event, reviewed quarterly with stakeholders, and formally rebuilt at least annually. The rebuild forces you to challenge your competitive boundaries, reassess threat levels, and question assumptions that may have become outdated.
One discipline that strengthens the landscape over time: after every significant competitive event, compare what actually happened to what the landscape predicted. Was the competitor's timeline accurate? Was the threat-level assessment right? Those retrospective checks calibrate your analytical models and build credibility with stakeholders.
A competitive landscape that doesn't inform strategy is a wall decoration. It's a slide people nod at in a brand planning meeting and then forget. The landscape's value isn't in the visual — it's in the decisions it drives.
The landscape feeds directly into three strategic processes:
Competitive threat assessment. The landscape provides the factual foundation for evaluating which competitors pose the greatest risk. Without the landscape, threat assessments become subjective — based on which competitor the brand team happens to be most worried about, not which competitor objectively poses the greatest commercial threat. For the full threat assessment methodology, see Competitive Threat Assessment.
Positioning and differentiation. The landscape shows where clinical and commercial differentiation is possible. Where are the gaps in the competitive field? Which mechanisms of action are underrepresented? Where is there an opportunity to position against a weak competitor cluster rather than a strong one?
Launch planning and competitive readiness. For pre-launch brands, the landscape is the foundational input to competitive readiness. It answers the questions that every launch team needs: who will we compete against on day one? Who's coming in the next 12–24 months? Where are we clinically differentiated, and where are we vulnerable?
The competitive landscape at launch is one of the most critical CI deliverables — it shapes the brand strategy, messaging, field force training, and counter-detailing approach. A launch team that enters the market without a current, comprehensive competitive landscape is flying blind.
For how the landscape connects to the full CI process, see How to Build a Competitive Intelligence Program.
A competitive landscape analysis is a systematic identification and assessment of all competitors relevant to a specific market, indication, or product. It maps competitors by development stage, mechanism of action, competitive positioning, and threat level — and presents them in a visual format that decision makers can act on. It's one of the six core CI deliverables. The landscape answers the foundational competitive question: who are we competing against, and what does the competitive field look like?
Quarterly at minimum, with event-triggered updates whenever a significant competitive development occurs — new clinical data, regulatory decisions, M&A, new market entrants, or guideline changes. A landscape that's only updated on a fixed schedule will miss critical developments. The most effective CI programs maintain the landscape as a living document, with real-time updates for high-priority competitors and quarterly formal reviews for the full competitive set.
The competitive landscape is the broad view — all relevant competitors mapped in a single framework, showing how they relate to each other and to your position. A competitor profile is the deep dive — a detailed analysis of a single competitor's strategy, capabilities, clinical program, commercial infrastructure, strengths, and weaknesses. The landscape tells you who's in the field and where they stand. The profile tells you what a specific competitor is likely to do next.
Use multiple frameworks. The industry lens shows you direct competitors in the same product-market space. But indirect competitors — those achieving similar outcomes through different mechanisms, different modalities, or non-pharmacological approaches — only become visible when you apply additional lenses: strategic groups analysis (who has similar resources and capabilities?), customer-based analysis (who do physicians and payers consider as alternatives?), and deliberate boundary expansion (what emerging technologies could disrupt the current treatment paradigm?). The key principle: be expansive first, then narrow deliberately.
It depends on the question and the audience. For executive summaries and portfolio overviews, use a pipeline funnel or stacked bar — they communicate competitive density immediately. For launch planning and clinical development timing, use a timeline with uncertainty ranges. For threat assessment, use a pipeline radar that emphasizes temporal proximity. Most CI programs maintain the stacked bar as the primary format and produce timelines as companion documents.
A structured competitive landscape takes 3–4 weeks from initiation to delivery: one week for scope definition and requirements, one week for research and categorization, one week for analysis and threat assessment, and a final week for stakeholder validation and formatting. If you're building a landscape for a therapeutic area you haven't previously covered, add one to two weeks for foundational research. Faster than that risks gaps in coverage. Slower than that, and you risk delivering a landscape that's already outdated.
Threat-level assessment combines three dimensions: clinical data strength (robustness of efficacy and safety data relative to your product), commercial capability (does the competitor have the infrastructure to launch and compete effectively?), and timeline proximity (how close are they to filing or market entry?). Score each dimension and combine them into an overall High, Medium, or Low threat rating. The weighting changes by context — timeline proximity matters most for pre-launch brands, while clinical data strength matters most for post-launch competitive dynamics.
Salvador Carlucci is the founder of the Atacana Group and has spent over two decades building competitive intelligence functions for pharmaceutical and healthcare companies worldwide. He is co-author of the seminal articles on CI in biotech published in Nature Biotechnology.
© CompetitiveIntelligence.com