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What You See When You Log In
Six views, each ending in a recommended action rather than a chart to interpret.
Consumption & Burn Rate
Item-level usage by department and site, with the run-rate that tells you how many days of cover you actually hold.
Stockout & Expiry Alerts
Early warnings on lines about to run short, batches nearing expiry and slow movers tying up working capital.
Spend & Price Variance
Where you are paying above your own contracted rate, and how spend splits across category, vendor and site.
Reorder Recommendations
Suggested quantities and timing built from your own history, ready to convert into an order in a click.
Substitution & Rationalisation
Where two SKUs do the same job, and what consolidating them saves per quarter.
Service & Fulfilment
Fill rate, lead-time drift and short-supply history by line, so escalations start from evidence.
The Signal Inside Your Consumption Data
Procurement data is a clinical record in disguise. What a facility buys, in what quantity, in which month, from which department, describes the case mix walking through its doors — and read across a network, it describes a season, a district, a shift in disease pattern. Insights reads that layer for you, alongside the cost and stock view.
Disease & seasonality patterns
Antibiotic, antipyretic, IV fluid and rapid-test movement tracked week on week — the early shape of a dengue, respiratory or gastro season before it shows up in admissions.
Case-mix shifts
Changing ratios across surgical, dialysis, maternity, cardiac and diagnostic consumables show which service lines are actually growing, not which ones were budgeted for.
Departmental variance
Two wards of the same size consuming very differently is a protocol question, a wastage question or a documentation question — the data says which.
Benchmark against peers
Anonymised, aggregated comparison against facilities of similar size and mix, so "high" and "normal" stop being guesses.
Demand forecasting
Seasonal curves plus your own growth trend produce a forward view of what you will need next quarter, per item.
Outbreak and surge readiness
Cover levels stress-tested against a surge scenario, with the shortlist of items that break first.
Facility-level data is never shared or identified. Benchmarks are aggregated and anonymised, and clinical interpretation stays with your medical team — Insights surfaces the pattern and the action, not a diagnosis.
What an Actionable Insight Looks Like
Every view ends in a finding, a recommended action and the outcome it moved. Representative examples of what the platform surfaces — the specifics depend on your data and the goals you set.
Disease pattern
Finding. Paracetamol, ORS and NS1 kit movement rose 40% across three weeks in one district — three weeks before OPD footfall did.
Action. Pre-position dengue-season stock at those sites and brief the OPD roster.
Two sites avoided a mid-season stockout; no emergency purchases at premium rates.
Consumption variance
Finding. Two wards of identical bed count consumed surgical gloves at a 2.3× difference.
Action. Audit the higher ward: found glove boxes stored open at a shared trolley.
Consumption normalised within a month — recurring monthly saving on a single line.
Demand forecasting
Finding. Dialysis consumable use tracked 8% above plan every month for a quarter.
Action. Reset par levels and move to a fortnightly replenishment cycle for that unit.
Cover restored to 21 days without increasing total inventory value.
Price variance
Finding. The same IV cannula was billed at three different rates across four sites in one quarter.
Action. Consolidate onto the contracted rate and flag off-contract purchases at approval.
Per-unit cost aligned to the lowest contracted rate across every site.
Case-mix shift
Finding. Orthopaedic implant and POP consumption grew steadily while general surgery stayed flat.
Action. Expand ortho OPD slots and rebalance the theatre schedule and stock mix.
Capacity followed real demand instead of last year’s budget split.
Goal-led improvement
Finding. Target: cut emergency purchases. 18% of order value was placed as urgent top-ups.
Action. Insights flagged the twelve items behind most urgent orders and raised their par levels.
Urgent orders fell to single digits as a share of value the following quarter.
Set your focus goals — reduce stockouts, cut emergency purchases, lower cost per bed-day, tighten expiry write-offs — and the recommendations reorder themselves around what you are trying to move.
How It Works
No new system to run. Insights reads what your ordering already generates.
01
Connect
Your Serturner order history is on by default; add GRN, indent or HIS/LIS exports if you want department-level detail.
02
Clean
Items are mapped to a single catalogue, so the same product ordered five ways still counts once.
03
Analyse
Burn rate, cover, variance and fill rate are recomputed nightly against your own baseline.
04
Act
Every view ends in a recommendation you can approve, share or convert into an order.
Your data stays yours
Access is limited to your own organisation and the users you nominate. Nothing is sold or shared.
Role-based access
Stores, pharmacy, finance and leadership each see the views relevant to them.
Export anything
Every view exports to CSV or PDF for board packs, audits and rate-contract reviews.
Already a Serturner customer?
Your purchase history is already there — sign in and it populates on first login.
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From Serturner Groundwork
Guides and case studies on procurement data, stock cover and cost control.
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