Most healthcare suppliers discover tender opportunities by accident. A portal alert arrives in your inbox. You spot an email from a colleague. You attend a networking event and hear about a contract that’s coming to market. By then, your competitors may already be ahead, they’ve been preparing for weeks.
But the best-performing healthcare suppliers don’t rely on chance. They forecast tender volume. They know what’s coming, when it’s coming, and how to prepare. They understand their procurement pipeline well enough to allocate bid writers, refresh case studies, and position for framework entries months before a formal tender drops.
This is the difference between reactive discovery and proactive planning. Under the Procurement Act 2023, which now mandates transparent procurement pipelines for authorities spending over ÂŁ100 million annually, this shift from reactive to proactive is no longer optional, it’s a competitive necessity. Engaging with key decision makers and understanding clients’ planning processes is now essential for effective decision making in procurement. Healthcare suppliers who can forecast expected tender volumes for the next quarter gain a strategic advantage: they right-size their teams, prioritise high-value opportunities, and position for framework renewals before competitors even know they’re coming.
The full-scale implementation of the Procurement Act 2023 has increased transparency, resulting in more tenders being advertised publicly in 2026.
This guide walks you through a practical, step-by-step methodology for building a reliable tender volume forecast using historical data, leading indicators, and seasonal patterns specific to NHS procurement. Whether you manage five portals or fifty, you’ll learn how to transform fragmented procurement data into actionable intelligence that drives your bid strategy.
Why Tender Volume Forecasting Matters for Healthcare Suppliers
Tender volume forecasting is the bridge between reactive chasing and strategic planning. Most suppliers operate in crisis mode: they react to portal alerts, chase every tender that vaguely fits their offering, and stretch their bid teams thin. Forecast-driven suppliers operate differently. They anticipate volume, prepare capture plans, and position for opportunities proactively.
Resource Allocation: Knowing expected tender volume enables you to right-size your bid team. If you forecast 150 primary care tenders in Q2 (roughly 35 per week), you can hire 2–3 additional bid writers. Without forecasting, you’re either understaffed (missing opportunities) or overstaffed (wasting money). This simple discipline prevents both scenarios. Accurate forecasting can lead to significant cost savings and other financial benefits, as it allows for more efficient allocation of resources and reduces unnecessary expenditure.
Category Prioritisation: A healthcare supplier might see 200 tenders in Q3, but only 30 are in their target categories. Forecasting by category enables you to focus resources on high-value opportunities and avoid chasing low-fit tenders. This is the difference between winning 5 contracts from 200 bids (2.5% win rate) and winning 3 contracts from 30 bids (10% win rate). The second scenario is far more profitable. Focusing on high-value categories benefits procurement teams by assisting them in making more successful bids and improving overall win rates.
Trigger Event Identification: Volume spikes signal urgency. If you forecast a 40% increase in mental health tenders in Q3 (driven by NHS England’s mental health investment programme), you can reach out to mental health trust contacts now, refresh case studies, and position for the wave. This creates urgency in sales conversations and accelerates deal velocity—a capability that enterprise-level suppliers already leverage. Forecasting can also help mitigate risks associated with sudden volume spikes by enabling proactive planning and resource adjustment.
Elective Recovery Funding Waves: The NHS received £22.6bn in additional cash uplift for elective recovery (confirmed in the UK Autumn Budget 2024). This funding is flowing into procurement in predictable waves tied to Community Diagnostic Centre (CDC) rollout phases. Diagnostic equipment tenders (MRI, CT scanners) are clustering around specific quarters aligned to these funding tranches. Suppliers forecasting diagnostic equipment volume in 2026 should expect volume spikes corresponding to CDC Phase 2 and Phase 3 rollout timelines—a category-specific leading indicator that historical data alone cannot reveal.
Framework Expiry Mapping: Framework renewals create predictable tender waves. If you know that 8 major NHS frameworks expire in Q3, you can start early engagement 6–12 months before the renewal tender, shaping requirements and building relationships. Without forecasting, you’re caught off-guard when the tender drops. From HCI market analysis conducted in February 2026, frameworks account for 75.4% of total contract value across UK public procurement, yet only 32.7% of suppliers have access to this value. Framework forecasting is a critical lock-in prevention strategy.
Competitive Intelligence: Volume trends reveal where competitors are bidding. If you forecast a spike in diagnostic equipment tenders (driven by elective recovery programmes), you know competitors will be active in that category. This enables you to benchmark your positioning and differentiate before the tender is published.
Robust spend analytics increases forecasting accuracy and assists in making better sourcing decisions, leading to more successful procurement outcomes.
Tender Volume Fundamentals: Defining Your Forecast Baseline
Before you can forecast, you need to define what you’re forecasting. Tender volume is the count of procurement notices, awards, framework calls, and mini-competitions published by a buyer in a given period. It’s distinct from tender value (the contract value). A high-volume category (e.g., GP practice supplies) might have 200 tenders per year at £50K each; a low-volume category (e.g., hospital construction) might have 5 tenders per year at £5M each. Volume forecasting helps you understand opportunity frequency; value forecasting helps you understand revenue potential.
Distinguish Volume from Value: This distinction is critical. A supplier might see 100 primary care tenders (high volume, lower individual value) and 2 acute trust tenders (low volume, higher individual value). If you only forecast aggregate volume, you miss this distinction. You need to segment by both volume and value to make intelligent resource allocation decisions.
Understand Volume Drivers: What causes tender volume to spike or dip? Several factors:
- Budget cycles: NHS England publishes budgets in Q1 (April). Trusts publish tenders in Q3 (July–September) to align with the financial year.
- Framework refreshes: When a framework expires, a renewal tender is published. These create predictable waves.
- Policy changes: The Procurement Act 2023 implementation, ICS reconfigurations, and elective recovery programmes all drive procurement waves.
- Seasonal patterns: School holidays affect primary care procurement; winter pressures affect acute trusts.
- Emergency procurement: Pandemic response or natural disasters create unpredictable spikes.
- Economic factors: Inflation and labour costs can significantly influence tender pricing. Currently, tender pricing is under upward pressure due to structural labour constraints and rising compliance costs.
Segment by Category, Buyer Type, and Route-to-Market: One aggregate forecast is useless. You need to segment by CPV category (medical supplies, IT, facilities management, professional services, etc.), buyer type (acute trusts, primary care networks, mental health trusts, social care, education, etc.), and route-to-market (open procedures, framework call-offs, dynamic purchasing systems, etc.). Different segments have different seasonality, different competition, and different strategic importance. Industry-specific factors, project complexity, and location can also influence tender volume and tender pricing, as costs and market conditions vary across sectors and regions.
A practical example: “Q2 will see 150 primary care tenders (high volume, lower value), 8 acute trust tenders (low volume, higher value), and 3 framework renewals (strategic importance). I’ll allocate 2 bid writers to primary care, 1 to acute, and 1 to framework renewals.” This segmented approach enables precise resource allocation.
Historical Baselines: Using Past Procurement Volume and Seasonality
Start by gathering tender data for the past 12–24 months. For each tender, record publication date, category (CPV code), buyer type, buyer name, route-to-market, contract value, award date, and winner name (if available). This data is available from Find a Tender Service (FTS), NHS Supply Chain, Crown Commercial Service (CCS), and regional Integrated Care Board (ICB) websites.
Normalise for Anomalies: Not all historical data is equal. Framework refreshes, policy changes, and emergency procurement create spikes that don’t reflect normal patterns. If a major framework was renewed in Q2 2024, you’ll see a spike in that category—but don’t assume Q2 2025 will be the same. If there was emergency procurement during a pandemic, don’t assume that pattern will repeat. Document your assumptions: “Q2 2024 saw 30 additional tenders due to NHS England’s elective recovery programme. I’m normalising this out because it’s not a recurring pattern.” Analyzing past procurement volume also helps firms decide where to focus their business development efforts, ensuring resources are allocated to categories with the highest potential.
Identify Seasonal Patterns: Plot your historical data by month and quarter. Look for recurring patterns:
- NHS Budget Cycle: NHS England publishes budgets in Q1 (April). Trusts publish tenders in Q3 (July–September) to align with the financial year.
- Primary Care Seasonality: Primary care tenders spike in September (new financial year) and dip in summer (school holidays).
- Acute Trust Seasonality: Acute trust tenders cluster around budget cycles and winter pressures (October–March).
- Framework Expiry Waves: If you know framework expiry dates, you can predict renewal tender waves 6–12 months in advance.
Understanding procurement cycles allows suppliers to plan bulk purchases, manage stock levels, and optimize production schedules, which helps mitigate risks, reduce costs, and ensure supply chain resilience.
Calculate Moving Averages and Trend Lines: Use simple statistics to smooth noise and identify trends. A 3-month moving average (averaging the past 3 months’ tender counts) smooths weekly and monthly noise. A linear trend line shows whether volume is increasing, decreasing, or stable over time. Seasonal decomposition (separating trend, seasonality, and noise) is more advanced but optional for initial forecasts.
Identifying Leading Indicators: What Signals Upcoming Tender Volume
The earliest signals precede formal tenders by weeks or months. Identifying these leading indicators enables you to position early.
Prior Information Notices (PINs) and Pipeline Notices: PINs are published 30–90 days before formal tenders. They signal buyer intent and upcoming volume. If you see a spike in PINs in a category, expect a tender wave 30–90 days later. This is your earliest warning signal. Clients often issue tenders when they anticipate future demand, using data analytics and predictive procurement to optimize purchasing and manage inventory. However, it is important to be careful when interpreting these signals, as market uncertainties or disruptions can affect the accuracy of forecasts.
Under the Procurement Act 2023, authorities spending over £100 million annually are now legally required to publish a 12-month forward pipeline notice. For NHS Trusts and Integrated Care Boards, this represents the single most reliable leading indicator available. These pipeline notices are published annually (typically in April) and provide visibility into upcoming procurement waves months before formal tenders are published. According to NHS guidance, the average lead time from a pipeline notice to a formal contract notice is approximately 180 days—giving you a six-month planning window that was previously invisible. This statutory transparency is a game-changer for procurement forecasting: instead of relying on fragmented signals, you now have a mandated, centralised view of what each major NHS organisation plans to procure over the next 12 months.
Contract Expiry Waves: Expiring contracts drive re-tender waves. If you know that 10 NHS acute trust contracts expire in Q3, you can forecast a spike in acute trust tenders in Q2 (when renewal tenders are published). The typical timeline: contract expires in Q3 → renewal tender published in Q2 (6 months before expiry) → award in Q3 → new contract starts in Q4. Distinguish extensions from re-tenders: some contracts are extended without re-tendering, whilst others are re-tendered. Client planning involves assessing project needs and existing supplier contracts to determine tender timing, and regulatory requirements can also affect the timing and volume of tenders issued.
Budget Announcements: NHS England budget announcements (typically Q1) drive procurement waves. When NHS England announces investment in mental health, expect mental health tenders 6–8 weeks later. When they announce elective recovery funding, expect diagnostic equipment tenders 6–8 weeks later.
Committee and Board Agendas: Procurement decisions often appear in public board papers before tender publication. Monitor NHS trust board agendas, ICB board agendas, and local authority cabinet agendas. If you see “Approval of procurement strategy for [Category]” on a board agenda, expect a tender 4–8 weeks later.
Policy Changes: The Procurement Act 2023 implementation, ICS reconfigurations, elective recovery programmes, and other policy changes drive procurement waves. Stay informed about government healthcare initiatives; they often precede tender spikes.
Methods to Create a Tender Forecast for the Next Quarter
Several forecasting approaches exist, ranging from simple to advanced. Choose based on your data availability and technical capability.
Moving Averages (Simple, Explainable): Average the past 3–6 months’ tender counts and use this as your forecast for the next quarter. Example: “Q4 2024 saw 120 tenders; Q1 2025 saw 110 tenders; Q2 2025 saw 130 tenders. Average: 120. Forecast for Q3 2025: 120 tenders.” Pros: simple, explainable, requires minimal data. Cons: ignores seasonality and trends. Use for stable categories with no strong seasonal patterns.
Seasonal Decomposition (Moderate Complexity, Explainable): Separate historical data into trend, seasonality, and noise. Apply seasonality factors to the trend to forecast. Example: “Trend is 120 tenders per quarter (stable). Seasonality factor for Q3 is 1.2 (20% higher due to budget cycle). Forecast: 120 × 1.2 = 144 tenders.” Pros: captures seasonal patterns, explainable, works well for healthcare procurement. Cons: requires 12–24 months of data. Use for categories with strong seasonal patterns (primary care, acute trusts, etc.).
ARIMA/Prophet (Advanced, Less Explainable): Statistical models that capture complex patterns (trends, seasonality, autocorrelation). Require more data and technical expertise. Pros: more accurate for complex patterns; can incorporate external variables. Cons: less explainable; requires data science expertise. Use only if you have a data science team. Predictive procurement approaches, which use machine learning and data analytics to forecast demand and identify stock needs, can be especially beneficial for procurement teams seeking to optimize tender volume and improve outcomes.
Practical Recommendation: For most healthcare suppliers, a seasonal decomposition model with leading-indicator adjustments provides 80% of the value at 20% of the complexity. Start here. Once you’ve validated the approach, add features (policy events, framework expiries) to your model. Spend data is a valuable asset for financial planning and enhances the accuracy of forecasts, assisting in better decision making for future procurement strategies.
Feature Engineering for Procurement Forecast Accuracy
The accuracy of your forecast depends on the variables (features) you track. Start simple, then add complexity. Identifying essential features and finance-related variables is critical for accurate forecasting, as these are fundamental for strategic decision-making and effective procurement planning.
Temporal Features: Month, quarter, fiscal year (captures seasonality); day of week (some buyers publish on Fridays); holiday periods (school holidays affect primary care; summer maintenance windows affect acute trusts).
Seasonality Flags: Budget cycle (Q1 planning, Q3 delivery); school holidays; winter pressures (October–March, affecting acute trusts); summer maintenance windows (affecting facilities management).
Structural Features: Framework expiry dates (signal renewal tender waves); policy implementation timelines (Procurement Act 2023, ICS reconfigurations, elective recovery); budget announcement dates (NHS England budget → trust procurement). Integrating new commodities into established sourcing processes is essential to improve visibility and forecast accuracy.
Buyer-Specific Features: Trust type (acute, community, mental health, social care); ICB footprint (regional variations in procurement patterns); buyer size (larger trusts tender more frequently); buyer procurement maturity (mature buyers follow predictable patterns).
Macro Features: Inflation (affects procurement timing and volume); workforce shortages (drive procurement in affected areas); pandemic response (drives emergency procurement); political priorities (elective recovery, mental health investment).
Practical guidance: Start with temporal features (month, quarter, seasonality flags). Once validated, add structural features (framework expiries, policy events). Only add buyer-specific or macro features if they improve accuracy.
How to Forecast Expected Tender Volumes for the Next Quarter: Step-by-Step Workflow
Here’s a practical, actionable workflow you can implement immediately. Total time estimate: 20–30 hours over 4 weeks (or 1–2 days if using consolidated data).
Procurement teams can be more successful by discussing and collaborating on forecasting efforts, ensuring that all relevant stakeholders are engaged in the process and that insights are shared for better outcomes.
Week 1: Gather and Consolidate Data
- Collect historical spend and tender volume data from internal systems.
- Identify key categories and suppliers.
- Review previous forecasts and actual outcomes.
- Subscribe to online databases that aggregate tender information to assist in improving forecasting accuracy.
Week 2: Analyse and Engage Stakeholders
- Analyse trends, seasonality, and anomalies in the data.
- Meet with business units to discuss upcoming projects, expected demand, and market changes.
- Use market data and predictive tools to assist in identifying risks and opportunities.
Week 3: Build the Forecast
- Develop a draft forecast using quantitative and qualitative inputs.
- Validate assumptions with procurement teams and key stakeholders.
- Adjust for known market or organisational changes.
Week 4: Review and Finalise
- Present the forecast to leadership for feedback.
- Refine based on input and finalise the document.
- Communicate the forecast to all relevant teams.
Effective forecasting is an ongoing process that requires continuous monitoring and centralization of intelligence to ensure accuracy and adaptability.
Week 1: Collect and Normalise Historical Data
- Gather 12–24 months of tender data from FTS, NHS Supply Chain, CCS, regional ICB websites (4–8 hours).
- Identify and normalise anomalies (framework refreshes, policy changes, emergency procurement) (2–4 hours).
- Segment data by category, buyer type, and route-to-market (2–4 hours).
Week 2: Identify Patterns and Leading Indicators
- Plot historical data by month and quarter (2–3 hours).
- Identify recurring patterns (budget cycles, seasonality, framework expiry waves) (2–3 hours).
- For your top 10 target buyers, identify expiring contracts, upcoming board meetings, policy initiatives, and budget announcements (3–4 hours).
Week 3: Choose Model and Backtest
- Select moving averages or seasonal decomposition as your baseline model (1–2 hours).
- Apply your model to past quarters and calculate accuracy metrics (MAPE, MAE, % variance) (2–3 hours).
- Refine your model if accuracy is poor (1–2 hours).
Week 4: Produce Forecast and Communicate
- Apply your model to next quarter with confidence intervals (e.g., “Q3 forecast: 120–150 tenders, 80% confidence”) (1–2 hours).
- Segment by category, buyer type, and route-to-market (1 hour).
- Present forecast to bid team, sales, and leadership, explaining assumptions and confidence intervals (1 hour).
Operationalising the Forecast in Pipeline Planning and Bid Strategy
A forecast is only valuable if it drives action. Translate your forecast into concrete decisions.
Translate Volume to Resource Allocation: If you forecast 150 primary care tenders in Q2 (roughly 35 per week), hire 2–3 additional bid writers. If you forecast 8 acute trust tenders in Q2 (roughly 2 per week), allocate 1 dedicated bid writer. If you forecast 3 framework renewals in Q2, allocate 1 resource for early engagement. Clients and contractors can use accurate forecasting to deliver on commitments, achieve more value for their organizations, and ensure resources are aligned to meet customer expectations.
Prioritise Categories: Rank categories by revenue potential, competitive advantage, and forecast volume. Allocate resources to top-priority categories first. Example: “Primary care (high volume, lower value): 2 bid writers. Acute trust (low volume, higher value): 1 bid writer. Framework renewals (strategic): 1 resource.” Understanding customer needs and leveraging economies of scale can lead to significant savings and more value for both buyers and suppliers.
Align Capture Plans: For each high-priority category, develop a capture plan: key buyers to target, competitive positioning, past performance references needed, compliance certifications required, content (case studies, testimonials, white papers) needed. Schedule content development to align with forecast volume spikes. Volume-based procurement policies can lead to significant price reductions for buyers due to increased competition among suppliers, but also create challenges for suppliers in maintaining profit margins.
Set Target Volumes: If you forecast 150 primary care tenders in Q2, set a target to bid on 30 (20% qualification rate). If you forecast 8 acute trust tenders in Q2, set a target to bid on 5 (62% qualification rate—higher because they’re higher-value). Use these targets to set weekly outreach and qualification goals. Heightened competition in volume-based procurement can result in substantial price cuts, sometimes exceeding 70%, so suppliers must mitigate these risks through careful planning and strategic resource allocation.
Identify Trigger Events: If your forecast shows a framework renewal in Q3, plan early engagement outreach in Q1. If your forecast shows a policy-driven wave (e.g., mental health investment), plan targeted outreach to mental health trusts in Q2. Use trigger events to create urgency in sales conversations.
Interpreting Frameworks and Mini-Competitions in Your Tender Volume Forecast
Framework-based procurement now dominates NHS spend. From HCI market analysis conducted in February 2026, frameworks account for 75.4% of total contract value across UK public procurement, but only 32.7% of suppliers have full visibility into renewal cycles. In public procurement, open tenders generally attract high volumes of bids, while restricted tenders limit the tender volume to pre-qualified firms. For NHS-specific frameworks, the challenge is even more acute: NHS Supply Chain manages approximately £4.5bn across 11 category towers, with most agreements structured on a 4+2 model (4-year initial term, 2-year extensions). Missing a framework renewal—or failing to position 12 months before—effectively locks you out of that category for 3–5 years. This makes framework renewal forecasting not just a revenue opportunity but a survival mechanism for healthcare suppliers.
Framework Renewals Are Predictable: Framework agreements typically last 3–5 years. Renewal tenders are published 6–12 months before expiry. If you know framework expiry dates, you can forecast renewal tender waves with high confidence. A healthy, high tender volume at renewal allows clients to select the Most Economically Advantageous Tender (MEAT), driving competition and securing the best price-quality ratio. Example: “NHS acute trust medical supplies framework expires in March 2027. Renewal tender will be published in September 2026 (6 months before expiry). I can forecast this with 95% confidence.”
Mini-Competitions Within Frameworks Are Harder to Forecast: Once a framework is awarded, framework holders can bid on mini-competitions (competitive calls within the framework). Mini-competition frequency depends on buyer activity, not just calendar dates. You can estimate volume based on historical patterns, but it’s less predictable than framework renewals. Example: “NHS acute trust medical supplies framework has 5 framework holders. Historically, they publish 2–3 mini-competitions per year. I’ll forecast 2–3 mini-competitions in Q2 2025.”
Distinguish Framework Entry from Call-Off Participation: Framework entry is a one-time, high-stakes tender to join the framework. If you miss it, you’re locked out for 3–5 years. Call-off participation is ongoing, lower-stakes mini-competitions or direct call-offs. You can participate if you’re on the framework. Framework entry is critical; call-off participation is important but less urgent.
Practical Framework Forecasting: Create a “Framework Risk Register” with framework name, expiry date, renewal tender date, current status (on framework or not), and forecast volume. For frameworks you’re on, forecast mini-competition and call-off volume. For frameworks you’re not on, forecast renewal tender date and plan early engagement. Example: “NHS acute trust medical supplies framework expires March 2027. Renewal tender: September 2026. Status: Not on framework. Action: Early engagement in Q1 2026 (6 months before renewal tender).”
Forecast Governance: Accuracy, Backtesting, and Communication
A forecast improves over time. Establish a governance process to measure accuracy, refine your model, and communicate uncertainty.
Measure Accuracy: Use MAPE (Mean Absolute Percentage Error) or simple % variance. Target: <15% MAPE. Example: “Q1 forecast: 120 tenders. Actual: 115 tenders. Variance: –4.2%. MAPE: 4.2%.”
Review Cadence: Monthly: review actual vs. forecast for the current quarter; adjust if needed. Quarterly: conduct full forecast review; update historical data, recalculate seasonality factors, backtest model. Annually: comprehensive review; update 12–24 month historical baseline, refine features, consider new methods.
Communicate Uncertainty: Don’t present point estimates (e.g., “Q2 forecast: 120 tenders”). Present confidence intervals (e.g., “Q2 forecast: 110–130 tenders, 80% confidence”). Explain assumptions and limitations. Use scenario ranges (e.g., “Base case: 120 tenders. Upside [policy-driven wave]: 150 tenders. Downside [budget constraints]: 90 tenders”).
Iterate and Refine: Forecasting is not a one-time exercise. Your model will improve over time as you gather more data and refine features. Document lessons learned and use them to refine your model for future forecasts.
How HCI Accelerates Tender Volume Forecasting
Building a tender volume forecast manually is time-consuming. Data consolidation, anomaly normalisation, and seasonal pattern identification can take weeks. HCI accelerates this process by consolidating data from 90+ portals and thousands of sources, eliminating the manual work of data collection and cleansing.
Data Consolidation: Instead of manually collecting data from FTS, NHS Supply Chain, CCS, and regional websites, you get consolidated, cleaned data in one place. This eliminates weeks of manual work.
Leading Indicator Monitoring: HCI’s Aria Intelligence monitors PINs, framework expiries, budget announcements, and contract expiry waves. Instead of manually tracking these signals, you can get personalised insights of frameworks at the click of a button.
Historical Data: HCI has 10,000+ healthcare contracts on the platform with historical data going back years. This gives you a rich baseline for forecasting without needing to collect 12–24 months of data yourself.
Category Segmentation: HCI’s CPV mapping enables category-level forecasts, not just aggregate numbers. You can forecast volume by medical supplies, IT, facilities management, etc., enabling precise resource allocation.
Dashboards and Alerts: Automated tracking of leading indicators; alerts when forecast thresholds are breached (e.g., “Volume spike detected in mental health tenders”). This enables proactive response without manual monitoring.
With HCI, you can build your baseline forecast in days instead of weeks. If manual data collection is slowing you down, HCI’s consolidated platform can accelerate your forecasting process significantly.
Be Proactive With Tender Volume Forecasting
Tender volume forecasting is the bridge between reactive discovery and proactive planning. By understanding historical patterns, identifying leading indicators, and choosing the right forecasting method, you can anticipate tender volume spikes, allocate resources strategically, and position for framework entries before competitors even know they’re coming.
Start simple. Collect 12 months of historical data, identify seasonal patterns, and build a moving average or seasonal decomposition forecast. Once you’ve validated the approach, add leading indicators and refine your model. Within 2–3 quarters, you’ll have a reliable forecasting process that informs your entire bid strategy.
The best healthcare suppliers don’t chase tenders—they forecast them. Begin your forecasting journey this quarter. Your Q3 pipeline will thank you.
Ready to forecast next quarter’s tender volume with confidence? HCI consolidates the data and surfaces the leading indicators you need. Schedule a free demo to see how HCI accelerates your forecasting process and helps you win more contracts.