
ORSSA Annual Conference 2026
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About this event
ORSSA Annual Meeting 2026
Event type: Operations Research, Analytics, Data Science, Optimization, Decision Science, Academic & Industry Conference
Likely audience profile: Researchers, lecturers, postgraduate students, analysts, consultants, data teams, optimization practitioners, operations managers, supply chain leaders, technology vendors, and policy/strategy professionals
Important note: To finalize the best buyer list for your client, I need your client’s website and a short note on what they sell. The ideal buyers change a lot depending on whether your client offers software, consulting, education services, analytics tools, recruitment solutions, research services, or enterprise technology.
The ORSSA Annual Meeting 2026 is best understood as a specialist decision-science and optimization gathering rather than a broad consumer event. That makes it very valuable for targeted attendee-list sales, especially when the goal is to reach technical decision-makers, research professionals, analytics buyers, and organizations that actively work with modeling, forecasting, logistics, simulation, scheduling, and optimization.
1️⃣ Who attends: Buyers / Attendees
This event typically attracts a focused mix of academic, research, and industry professionals. The strongest buyer segments are not general visitors; they are people who influence tools, training, software, data platforms, consulting, and research investments. In many cases, attendees are already working on problems that require advanced analytical thinking, which makes them highly relevant for vendors selling software, services, and enterprise solutions.
Main attendee groups:
- Operations research academics, professors, lecturers, and researchers
- Postgraduate students, PhD candidates, and early-career researchers
- Data scientists, business analysts, and analytics managers
- Optimization specialists and quantitative modelers
- Supply chain, logistics, planning, and forecasting professionals
- Consultants in strategy, analytics, operations, and transformation
- Technology vendors offering simulation, BI, AI, and optimization tools
- Government, public sector, and policy professionals focused on resource allocation and systems efficiency
- Industry practitioners from finance, telecom, healthcare, transport, mining, manufacturing, and energy
In buyer terms, this audience is valuable because many attendees either directly purchase tools or strongly influence procurement through recommendations, research validation, pilots, or implementation projects.
2️⃣ Where the show is happening + attendee geographic origin
Show location: The exact venue for the 2026 meeting should be confirmed from the official event announcement. ORSSA annual meetings are generally hosted in South Africa, with a strong local academic and professional presence.
Likely attendee origin: Predominantly South African, with possible participation from neighboring African countries and a smaller international research community depending on the host city and speaker lineup.
Geographic targeting strategy:
- Local: Strong concentration from the host city and nearby provinces
- National: South African universities, corporates, consultancies, and government bodies
- Regional: Southern African organizations with analytics and optimization needs
- International: Research partners, software vendors, and academic collaborators with Africa-facing programs
For attendee-list value, the strongest records will likely come from South Africa-based universities, research centers, consulting firms, and enterprise teams with analytics mandates.
3️⃣ Audience reach: Local / National / Global
Primary reach: National
Secondary reach: Regional and niche global
This is usually a nationally anchored event with highly specialized regional relevance. While it is not a mass global expo, it can still draw international attention because operations research, optimization, and analytics are globally relevant disciplines. The best interpretation is: national audience density with global technical credibility.
For list-building purposes, this means the event can be excellent for precise B2B targeting even if total footfall is smaller than a trade show. In many cases, a smaller specialist conference delivers better lead quality than a larger generic event.
4️⃣ Sample buyer company names + websites
Below is a sample buyer list designed for attendee-list research. These are organizations that commonly benefit from analytics, optimization, forecasting, simulation, and decision science. If your client’s product is different, I can refine this list once you share the client website.
| Priority | Company | Website | Best Title to Target | Why This is a Good Buyer Fit |
|---|---|---|---|---|
| 1 | Deloitte | deloitte.com | Manager, Analytics Consulting | Strong buyer for decision science, optimization, and enterprise analytics services. |
| 2 | Accenture | accenture.com | Data & AI Strategy Lead | Frequently invests in data platforms, transformation programs, and analytical capability. |
| 3 | PwC | pwc.com | Director, Data Analytics | Relevant for risk, forecasting, operations, and advisory-related analytics use cases. |
| 4 | KPMG | kpmg.com | Manager, Business Intelligence | Potential buyer for optimization, audit analytics, and advisory solutions. |
| 5 | EY | ey.com | Director, Data & Analytics | Good fit for transformation, forecasting, and enterprise decision-making support. |
| 6 | Standard Bank | standardbank.co.za | Head of Analytics | Banking teams often invest in predictive modeling, risk, customer analytics, and optimization. |
| 7 | FirstRand | firstrand.co.za | Manager, Decision Science | Financial services buyer with strong demand for modeling, forecasting, and automation. |
| 8 | Absa Group | absa.africa | Head of Data Science | Relevant for analytics, operational efficiency, and customer decision systems. |
| 9 | Vodacom | vodacom.com | Senior Manager, Network Planning | Telecom planning, capacity optimization, and forecasting make this a strong fit. |
| 10 | MTN Group | mtn.com | Analytics Product Manager | High need for large-scale operational analytics and customer intelligence. |
| 11 | Sasol | sasol.com | Operations Excellence Manager | Industrial optimization, planning, and resource allocation are highly relevant. |
| 12 | Transnet | transnet.net | Manager, Network Planning | Transport and logistics optimization are core needs for this organization. |
| 13 | Shoprite | shopriteholdings.co.za | Supply Chain Analytics Manager | Retail demand forecasting, inventory optimization, and distribution planning are key needs. |
| 14 | Woolworths | woolworths.co.za | Head of Supply Chain Planning | Retail analytics and optimization align well with conference themes. |
| 15 | Anglo American | angloamerican.com | Manager, Operational Excellence | Mining operations benefit from simulation, scheduling, and resource optimization. |
| 16 | South African Reserve Bank | resbank.co.za | Economic Research Manager | Research-heavy environment with strong relevance to forecasting and modeling. |
| 17 | University of Pretoria | up.ac.za | Head of Department / Research Director | Academic buyer and collaborator for research tools, conferences, and partnerships. |
| 18 | University of Johannesburg | uj.ac.za | Professor / Research Coordinator | Strong attendee profile for academic research, events, and collaboration opportunities. |
| 19 | CSIR | csir.co.za | Principal Researcher | Public research organization with clear alignment to optimization and applied analytics. |
| 20 | GIBS Business School | gibs.co.za | Programme Director, Executive Education | Relevant for decision science learning, executive training, and applied analytics programs. |
Top 5 sample buyer targets to send first: Deloitte, Accenture, Standard Bank, Transnet, and CSIR. These represent consulting, enterprise analytics, finance, logistics, and research—five different buyer paths with strong relevance to an operations research audience.
5️⃣ Job profiles, industries & event type
This event is highly useful for targeting technical and strategic decision-makers. The right job titles are usually not junior generalists. Instead, you want people who own analytics agendas, efficiency programs, research methods, or digital transformation projects.
Best job profiles to target:
- Head of Analytics
- Director of Data Science
- Decision Science Manager
- Operations Research Analyst
- Business Intelligence Manager
- Supply Chain Planning Manager
- Forecasting Manager
- Optimization Specialist
- Research Director
- Professor / Senior Lecturer
- Academic Programme Coordinator
- Consulting Manager
- Operational Excellence Manager
- Strategy Manager
- Transformation Lead
- Data Engineering Manager
- Risk Analytics Manager
- Economic Research Manager
Best industry filters to use:
- Education Management
- Higher Education
- Research
- Information Technology & Services
- Computer Software
- Financial Services
- Banking
- Management Consulting
- Telecommunications
- Logistics & Supply Chain
- Transportation/Trucking/Railroad
- Retail
- Utilities
- Mining & Metals
- Oil & Energy
- Government Administration
- Public Policy
- Professional Training & Coaching
- Industrial Automation
- Mechanical or Industrial Engineering
Event type classification: Academic conference, professional society meeting, research symposium, analytics networking event, decision science knowledge exchange.
6️⃣ Estimated attendance / expected footfall
Since ORSSA annual meetings are specialized professional events, attendance is usually smaller than large trade fairs but stronger in quality and relevance. The exact 2026 number should be confirmed from the official organizer, but a sensible planning range would often be:
- Estimated attendance: 150 to 500+
- Primary value: Quality of attendees rather than raw volume
- Best attendees to monetize: Academics, consultants, corporate analytics teams, and industry sponsors
If the agenda includes workshops, tutorials, sponsor booths, or industry panels, the effective buyer value rises because attendees tend to be more solution-oriented and willing to engage with vendors.
7️⃣ Key focus areas & buyer engagement
Likely key focus areas:
- Optimization and mathematical modeling
- Decision support systems
- Data analytics and business intelligence
- Simulation and forecasting
- Supply chain and logistics optimization
- Operations planning and scheduling
- Risk analysis and scenario planning
- Machine learning applications in operations research
- Research methods and quantitative problem solving
- Industry-academic collaboration
Buyer engagement angle:
This audience responds best to highly relevant and technical messaging. The strongest value proposition is not broad “attendee access,” but targeted access to people who are actively shaping decisions about software, data, research, training, and operational improvement. Messaging should emphasize measurable outcomes such as:
- Improving efficiency and reducing cost
- Enhancing forecasting accuracy
- Optimizing planning and resource allocation
- Supporting research, innovation, and applied analytics
- Connecting with academic and industry experts
For sponsor or exhibitor outreach, positioning around “decision science professionals,” “optimization leaders,” and “analytics decision-makers” will resonate more than generic event language.
8️⃣ Client-product fit note
Please share your client website before finalizing the best buyer list. This is especially important for a specialist conference like ORSSA because the best buyers depend heavily on the product category.
How the buyer list changes by product:
- If your client sells software: target analytics managers, data science leads, BI heads, operations research professionals, and IT decision-makers
- If your client sells consulting services: target strategy, transformation, optimization, and operations excellence leaders
- If your client sells training or education solutions: target universities, executive education teams, and research leaders
- If your client sells research tools or statistical platforms: target lecturers, researchers, and postgraduate program heads
- If your client sells enterprise data services: target finance, telecom, logistics, retail, mining, and energy analytics teams
Once you share the client website, I can rank the best-fit buyers more accurately and filter out weak matches.
9️⃣ Industry suggestions based on the industry list you provided
Based on your industry list, the most relevant filters for this event are the ones that match technical, analytical, research, academic, consulting, and data-driven buyers.
Best industry categories to use:
- Research
- Education Management
- Higher Education
- Professional Training & Coaching
- Information Technology & Services
- Computer Software
- Management Consulting
- Financial Services
- Banking
- Telecommunications
- Logistics & Supply Chain
- Transportation/Trucking/Railroad
- Retail
- Utilities
- Mining & Metals
- Oil & Energy
- Government Administration
- Public Policy
- Industrial Automation
- Mechanical or Industrial Engineering
If you want the list to be even sharper, I would group buyers into four practical buckets: Academic, Corporate Analytics, Consulting, and Public Sector / Research. That structure makes outreach and segmentation much easier.
Final recommendation
ORSSA Annual Meeting 2026 is a strong niche event for attendee-list sales if your client sells anything connected to analytics, optimization, forecasting, data platforms, research tools, consulting, education, or decision-support solutions. It is not a mass-market event, but it is exactly the kind of specialist meeting where the attendee quality can be very high.
Best buyer segments to prioritize:
- Analytics and data science leaders
- Operations research and optimization professionals
- Supply chain and planning managers
- Consulting and transformation teams
- Academic researchers and university departments
- Government and public-sector strategy teams
Quality rating for B2B attendee-list sales: 8.5/10
The main reason for the strong rating is buyer relevance. Even if the attendance is modest, the audience is specialized, decision-oriented, and highly aligned with analytical products and services.
Next step: Send me your client website, and I will review it and give you the best buyer companies, the best job titles, the best industries, and the most relevant attendee segments for this specific event.
Data sheet
| Event Name | ORSSA Annual Conference 2026 |
| Event Date | 17 June 2026 |
| Event Status | Completed |
| Venue | Salem Convention Center |
| City | Salem |
| State / Region | Oregon |
| Country | United States |
| Organizer | Organizer name not publicly confirmed from current-year official event materials available at time of research. |
| Official Event Website | Current-year official event page not publicly verified at time of research. |
| Event Type | Operations Research, Analytics, Data Science, Optimization, Decision Science, Academic & Industry Conference |
| Primary Category | Science & Research |
| Secondary Applicable Categories | IT & Technology; Education & Training; Business Services |
| Audience Reach | Likely Regional to National |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for company-level attendance and footfall due to lack of publicly verified current-year attendee directory, exhibitor list, or official post-event release. |
| Main Purpose of Event | Professional exchange around operations research, analytics, optimization, modeling, decision science, and applied industry use cases, with likely emphasis on networking, knowledge-sharing, talent visibility, and solution discovery. |
ORSSA Annual Conference 2026 appears to be a specialist professional meeting positioned around operations research, analytics, data science, optimization, and decision support. Based on the event title, venue details supplied, and the stated audience profile, this is best classified as a focused academic-and-industry conference rather than a large general trade show. Its value comes from the concentration of technical practitioners, researchers, educators, and business-side professionals who influence analytical methods, tools, and implementation strategies.
For B2B lead generation, the event matters most where a supplier is targeting analytics buyers, research communities, optimization users, supply chain and operations teams, consulting groups, or organizations evaluating decision-support platforms and specialist services. Publicly verified current-year attendee, sponsor, and exhibitor detail was limited at the time of research, so company-level targeting should be treated as a precision outbound opportunity rather than a confirmed attendance-list sale opportunity unless additional official event materials become available.
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| Academic researchers and lecturers | Universities, research institutes, business schools, engineering departments | Influence software selection, research tools, training programs, datasets, and collaborative projects | Strong fit for analytics tools, simulation software, optimization platforms, publishing, and professional education |
| Postgraduate students and doctoral candidates | Universities, research labs, fellowship programs | Emerging users and evaluators of technical platforms; future enterprise buyers and hiring candidates | Useful for talent-branding, education offers, software trials, and long-term pipeline building |
| Analytics and data science teams | Enterprises, consulting firms, technology companies, public agencies | Evaluate modeling tools, decision engines, forecasting methods, data platforms, and implementation partners | High relevance for SaaS, cloud analytics, MLOps, optimization software, and specialist consulting |
| Operations and supply chain leaders | Manufacturers, retailers, logistics providers, distribution networks, public infrastructure operators | Can sponsor operational improvement projects and purchase decision-support solutions | High-value segment for planning, scheduling, inventory optimization, routing, and scenario-modeling solutions |
| Consultants and advisory professionals | Management consulting, analytics advisory, operations improvement firms | Influence tool recommendations and downstream buying decisions across multiple clients | Strong channel and referral opportunity for software, research, and implementation services |
| Technology vendors and solution architects | Software companies, cloud providers, specialist analytics vendors | Partnership, integration, reseller, or co-sell influence rather than end-user buying only | Relevant for partnership development, ecosystem outreach, and technical alliances |
| Policy, strategy, and public-sector analysts | Government departments, public agencies, transport and planning bodies | May influence procurement for modeling, policy analytics, and scenario planning | Relevant for public-sector analytics, forecasting, optimization, and evidence-based policy tools |
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Salem | Local academics, analysts, business professionals, and public-sector participants | Low to Medium | Host-city attendees likely include nearby institutions and organizations seeking a one-day specialist conference. |
| Oregon | Statewide participation from universities, consulting firms, logistics operators, manufacturers, and technology teams | Medium | Likely strongest practical catchment area based on venue and one-day schedule. |
| Pacific Northwest | Attendees from Portland, Eugene, Corvallis, Seattle, Tacoma, Vancouver, and nearby regional hubs | Medium to High | Strong regional relevance for supply chain, technology, research, and applied analytics communities. |
| United States | Selective national attendance from specialist researchers, speakers, and practitioners | Medium | National draw is plausible for niche technical audiences, but not publicly confirmed. |
| International | Possible but unverified | Low | No current-year official evidence reviewed confirming international attendee mix. |
| Reach Level | Assessment | Explanation |
|---|---|---|
| Regional | Primary classification | Based on the Salem, Oregon venue, one-day format, and specialist subject matter, the most likely audience footprint is regional with selective national participation. |
| National | Secondary potential | Technical conferences in analytics and operations research can attract U.S.-wide practitioners, but this was not publicly confirmed for the 2026 edition. |
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Current-year buyer organizations not publicly verified | N/A | No official 2026 attendee list, exhibitor directory, sponsor roster, or speaker-organization page was publicly verified during research. | N/A | Procurement lead, analytics director, operations research manager, data science lead | Not publicly confirmed |
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Director of Analytics | Analytics / Data | Director | Often owns applied analytics strategy, team tools, and implementation priorities. |
| 2 | Head of Data Science | Data Science | Head / Director | Key buyer for modeling frameworks, platforms, infrastructure, and specialist talent solutions. |
| 3 | Operations Research Manager | Strategy / Optimization | Manager | Directly relevant for optimization, simulation, and decision-support offerings. |
| 4 | Supply Chain Director | Supply Chain | Director | Influences procurement of forecasting, network optimization, routing, and planning solutions. |
| 5 | Operations Director | Operations | Director | Decision-maker for efficiency, scheduling, resource allocation, and productivity improvement projects. |
| 6 | Professor / Research Lead | Research / Academic | Senior | Important for research adoption, institutional partnerships, grants, and educational software purchasing. |
| 7 | Analytics Consultant | Consulting | Manager / Director | Can influence multiple downstream clients and create partner-led demand. |
| 8 | Chief Data Officer | Executive | C-Level | Relevant at larger enterprises and public agencies where analytics investment is strategic. |
| 9 | Program Manager | PMO / Transformation | Manager | Useful contact for analytics implementation, modernization, and cross-functional project delivery. |
| 10 | Strategic Sourcing Manager | Procurement | Manager | Relevant if the client offers enterprise software, consulting, or research services requiring formal vendor onboarding. |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Higher Education | Strong fit for faculty, researchers, postgraduate programs, and institutional analytics users. | Research software, training, data access, academic partnerships |
| 2 | Research | Core relevance to modeling, experimentation, and applied quantitative methods. | Decision science tools, collaboration, technical datasets |
| 3 | Information Technology & Services | Enterprise buyers often sit in analytics and digital transformation functions. | Analytics services, implementation, managed data projects |
| 4 | Computer Software | Relevant for optimization, simulation, AI, and analytics platform vendors and buyers. | Platform sales, integrations, partnership outreach |
| 5 | Management Consulting | Consultancies apply OR and analytics in client engagements. | Partner channel, service collaboration, subcontracting |
| 6 | Logistics & Supply Chain | Operations research is heavily used in network design, routing, and inventory optimization. | Planning, forecasting, and optimization deployments |
| 7 | Transportation/Trucking/Railroad | High operational complexity makes this sector a natural OR buyer. | Scheduling, routing, cost optimization |
| 8 | Industrial Automation | Optimization and process improvement are relevant to industrial operations. | Operational efficiency, simulation, planning |
| 9 | Mechanical or Industrial Engineering | Technical and engineering-led teams often adopt OR methods. | Optimization software, consulting, technical services |
| 10 | Government Administration | Public agencies use analytics for planning, policy, resource allocation, and service delivery. | Decision support, forecasting, public-sector modernization |
| 11 | Utilities | Utilities use optimization and forecasting in planning and operations. | Load planning, asset optimization, scenario analysis |
| 12 | Hospital & Health Care | Healthcare operations increasingly use scheduling, capacity, and workflow optimization. | Operational analytics, workforce planning, patient flow modeling |
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Unconfirmed | No verified official event release reviewed | Do not use for forecasting list size without organizer documentation. |
| Exhibitor count | Not publicly confirmed | Unconfirmed | No verified exhibitor prospectus or floorplan reviewed | May be limited if the format was conference-led rather than expo-led. |
| Buyer count | Not publicly confirmed | Unconfirmed | No verified attendee segmentation data reviewed | Likely mixed practitioner and academic audience rather than pure procurement attendance. |
| Speaker count | Not publicly confirmed | Unconfirmed | No verified agenda reviewed | Speaker organizations would materially improve account targeting once published. |
| Sponsor count | Not publicly confirmed | Unconfirmed | No verified sponsor page reviewed | Sponsors would help identify commercial ecosystem participants. |
| Historical attendance | Historical figure not publicly verified for use in this report | Historical / unavailable | Insufficient official archive evidence reviewed | Use caution before extrapolating demand volume. |
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Optimization | Better resource allocation, scheduling, routing, and cost control | Demonstrate measurable ROI and time-to-decision improvement | Optimization engines, scenario tools, consulting |
| Data Science | Modeling workflows, experimentation, forecasting accuracy | Offer tool integrations, deployment support, and governance capability | Analytics platforms, model management, data services |
| Decision Science | Improved strategic decisions under uncertainty | Position around business outcomes and decision quality | Decision-support software, advisory services, training |
| Supply Chain Analytics | Inventory optimization, demand planning, logistics efficiency | Use case-led outreach to operations and planning teams | Forecasting, routing, digital twins, planning tools |
| Simulation and Modeling | Test scenarios before operational deployment | Engage technical leads with proof-of-concept messaging | Simulation tools, engineering analytics, advisory support |
| Education and Training | Upskilling in OR, analytics, and quantitative methods | Position courses, certifications, workshops, and academic collaboration | Training programs, curriculum partnerships, certification support |
| Digital Transformation | Move from spreadsheet-driven planning to scalable analytical systems | Speak to modernization, automation, and executive visibility | Enterprise software, cloud implementation, analytics consulting |
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | High | Strong if the client sells analytics, optimization, research, training, or enterprise technology solutions. |
| Decision-maker availability | Medium | Audience likely includes influencers and technical evaluators; pure final-budget owners may be fewer than at procurement-led events. |
| Data collection potential | Low to Medium | Public attendee intelligence is limited without official directories or sponsor lists. |
| Apollo targeting potential | Very High | Titles, departments, and industry filters map well to analytics, research, and operations personas. |
| Geographic targeting potential | High | Pacific Northwest and U.S. national account clusters can be segmented effectively. |
| Best outreach approach | High | Use use-case-led outreach focused on optimization ROI, research productivity, or operational impact rather than generic event messaging. |
| Overall lead quality | High | Niche but qualified audience with strong technical alignment. |
| Best use case | High | Persona-led prospecting, account-based outreach, partnership mapping, and sponsor-targeting support. |
| Limitations / risks | Medium | Limited public verification reduces confidence in attendee-list monetization and current-year company attendance claims. |
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Higher Education; Research; Information Technology & Services; Computer Software; Management Consulting; Logistics & Supply Chain; Transportation/Trucking/Railroad; Industrial Automation; Mechanical or Industrial Engineering; Government Administration; Utilities; Hospital & Health Care | Captures the most likely analytics and optimization buyer environments. |
| Departments | Data / Analytics; Information Technology; Operations; Supply Chain; Engineering; Research; Strategy; Procurement; Consulting | Focuses on functions most likely to evaluate or sponsor decision-science purchases. |
| Seniority | Manager; Senior Manager; Director; VP; Head; C-Level; Professor / Principal Investigator equivalent where available | Targets both technical influencers and budget owners. |
| Job titles | Director of Analytics; Head of Data Science; Operations Research Manager; Supply Chain Director; Operations Director; Chief Data Officer; Analytics Manager; Optimization Lead; Strategy Director; Program Manager; Research Director; Professor; Principal Data Scientist | High-fit titles for the event’s likely subject matter and attendee profile. |
| Geography | Oregon; Washington; California; Idaho; British Columbia; United States | Prioritize Pacific Northwest first, then expand nationally. |
| Employee size | 11-50; 51-200; 201-500; 501-1,000; 1,001-5,000; 5,001+ | Covers both specialist consultancies and larger enterprises with formal analytics teams. |
| Keywords | operations research, optimization, decision science, simulation, forecasting, analytics, prescriptive analytics, supply chain optimization, mathematical modeling, scheduling, resource planning | Improves precision when event-specific attendee lists are unavailable. |
| Technologies, if relevant | BI tools, Python/R ecosystems, cloud analytics stacks, simulation software, optimization solvers | Useful if the client sells complementary software or services. |
| Revenue range, if relevant | $5M-$50M; $50M-$500M; $500M+ | Helps separate smaller specialist firms from enterprise-scale operations buyers. |
| Company type | Private; Public; Nonprofit; Government; Educational Institution | Matches the mixed academic, public, consulting, and enterprise composition likely at this event. |
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| User-supplied event brief | User-provided input | Event title, venue, city, state, country, and dates | Medium |
| Salem Convention Center | Venue website | Venue identity and host-location plausibility | High for venue only |
| ORSSA official association website | Association website | Association identity context for ORSSA acronym; current-year Salem event page not publicly verified in this report | Medium |
| Research verification note | Analyst assessment | No publicly verified 2026 attendee list, exhibitor list, sponsor roster, or detailed agenda was available for confirmation at the time of research | High as a limitation note |
🎯 Selling to this event's audience? Get a free tailored buyer list
Tell us your work email and our AI instantly builds a buyer list matched to ORSSA Annual Conference 2026 — the best‑fit companies to target, the exact decision‑maker job titles, and the industry filters that fit what you sell.