Tendering process-efficiency boost
Win-rate increase across deployed markets
Margin expansion on tendered revenue
From engagement to live PoC in country one
Across 165 markets, this top-10 pharma’s commercial engine ran on a single workflow: tenders. They drove most of the company’s revenue and almost all of its competitive intensity. The leadership team knew it. They had been trying to industrialise it for four years.
They had done what every Fortune 100 does. A central platform programme. A $6M budget. Eighty countries outsourced to data vendors. The intent was a single source of truth for tendering, harmonised across every region. The result was the opposite. Data was inconsistent. Records duplicated. Local teams stopped trusting what the system said. After four years, 50 of 80 countries were nominally live on data nobody could rely on, and 30 countries were still unfinished. Win rates had not moved.
The question was no longer whether tendering needed transformation. It was whether transformation was still possible after a four-year programme had drained the budget, the time, and most of the credibility the team had to work with.
Spent on the internal programme
Timeline before Vamstar
Countries outsourced to data vendors
Went live on poor data
Local teams, burnt out on manual data entry into a system that gave them nothing back, had quietly stopped using it. Headquarters could not see the pipeline, because the pipeline was being run in spreadsheets the platform did not know about. Four years in, the programme had eroded confidence in the very workflow it was supposed to industrialise.
We had lost trust in the system before it was finished. Every time a tender came in, the team treated it like a one-off.
With a failed internal programme behind them, the team made one more call.
What they wanted was specific. Someone who could land a working answer inside the systems they already owned. Quickly.
Vamstar’s Forward Deployed Engineers spent the first phase with local commercial teams in market, not with the central programme office. The goal was to map the workflow tenders actually moved through, the data sources teams genuinely relied on, and the decision points where the system would either earn its place or be ignored.
Forward Deployed Engineering →No new platform. No parallel login. The Data Orchestration Engine and Pricing Co-Pilot were embedded directly into the existing Salesforce environment, so local users kept working in the CRM they already knew. Training stayed minimal. Adoption stopped being a fight.
Explore Polaris →The Pricing Co-Pilot was trained on pharma tender award data, competitor positioning and market signals, then tuned to the company’s portfolio. It surfaced a recommended strategy per opportunity, with the evidence to defend it. Local teams stopped guessing. Central pricing stopped second-guessing.
Explore Pricing Co-Pilot →A staged rollout, small enough to be safe, fast enough to be felt. Each phase locked in the next.
PoC
Vamstar FDEs landed in country one. The Data Orchestration Engine was wired into the existing Salesforce instance. A live, defensible pricing recommendation was running inside the CRM by the end of week two.
Stabilise
Data flow held. Local team adoption climbed. Pricing logic was tuned against live tender outcomes. The model produced an answer the country head was willing to defend to headquarters, and one headquarters could read.
Scale, wave 1
Ten further markets rolled onto the platform. Because deployment sat inside Salesforce, training was hours, not weeks. Win-rate and cycle-time deltas started showing up in the regional KPI pack within the quarter.
Scale, wave 2
The remaining priority markets came online. Local-team adoption reached 86%. Process efficiency, win rate, margin and pipeline visibility moved together, the four metrics the original programme had failed to shift in four years.
Twelve months in, the metrics that mattered moved together: efficiency, win rate, margin, adoption.
Time-to-bid collapsed across the 25 deployed markets. Headquarters could see the pipeline. Local teams stopped re-keying data into a system that had not been reading them back.
Pricing recommendations carried evidence. Bid preparation moved from days to hours. The lift compounded across high-frequency tendering markets where small bid-quality gains showed up fast.
The Pricing Co-Pilot identified where to bid sharper to win, and where to hold price because the market supported it. Discounting discipline tightened without losing share.
Adoption is the metric that exposes platform design. 86% of local users running the new workflow inside Salesforce is what made every other outcome durable.
“It’s the first time in this company’s history that tendering felt like a system we owned, not a problem we managed.”
Three components, deployed together, inside the systems they already owned.
Pulls signal from tender boards, pricing benchmarks and competitor activity, deduplicates and harmonises it across markets, and lands it inside the CRM as a native data layer.
Explore Data Orchestration →Trained on pharma award data and competitor positioning. Recommends bid strategy per opportunity with the supporting evidence, so commercial teams move from interpretation to action.
Explore Pricing AI →Embeds tender intelligence and bid preparation into Salesforce. No new login, no parallel system. Local teams keep working where they already work, and adoption stops being a battle.
Explore Tender AI →Vamstar deploys forward-deployed engineers inside the systems you already own. No new platform. No four-year programmes. Talk to us about a proof of concept in one market.
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