What ABC VED analysis answers that min-max cannot
ABC VED analysis is a two-axis classification of pharmacy inventory: ABC ranks items by annual consumption value, and VED ranks them by clinical criticality. The reason to run both is that they disagree, and the disagreement is the useful part. An expensive item that nobody dies without and a cheap item that a patient dies without require opposite control policies, and no single-axis rule can express that.
A blanket min-max policy applied across the item master treats a ₹4 paracetamol tablet and a ₹40,000 vial of an antivenom with the same logic: set a minimum, set a maximum, reorder when you hit the minimum. That produces overstocking of expensive slow movers, understocking of cheap critical items nobody thinks about, and buyer attention distributed evenly across a catalogue where the value is anything but evenly distributed.
The output of the analysis is not a report. It is a set of differentiated policies — who approves the purchase, how often stock is counted, how much buffer is held, how far ahead it is ordered — assigned by class and applied automatically. Hospitals that produce the classification and then continue managing everything identically have done the analysis and skipped the point.
Running the ABC calculation, concretely
ABC analysis is arithmetic on twelve months of consumption. For each item, take the quantity actually issued over the period and multiply it by the current unit purchase cost to get the annual consumption value. Use issues rather than purchases, because purchases reflect ordering behaviour and stock building rather than what the hospital consumed. Use a rolling twelve months rather than a financial year, so seasonal items are represented consistently.
Sort the items by annual consumption value in descending order, then compute a running cumulative total and express it as a percentage of the total consumption value across all items. Apply the conventional cut points: the items accounting for roughly the first 70% of cumulative value are class A, the items covering the next 20% are class B, and the remainder — the long tail making up the last 10% of value — are class C. The thresholds are a convention, not a law; adjust them if your distribution has a natural break elsewhere.
A worked illustration makes the shape clear. Suppose a hospital stocks 1,400 pharmacy line items with a total annual consumption value of ₹6 crore. Class A is then the set of items whose cumulative value reaches ₹4.2 crore — in a typical hospital distribution this will be a small fraction of the item count, often on the order of a hundred-odd items. Class B covers the next ₹1.2 crore, and class C is everything left, which is usually the large majority of line items accounting for the last ₹60 lakh. The figures here are illustrative arithmetic on an assumed total, not a benchmark; run your own numbers, because the item counts falling into each band vary considerably by hospital type and case mix.

The ABC calculation, step by step
- Extract twelve months of issue quantity per item code
- Multiply issue quantity by current unit purchase cost to get annual consumption value
- Sort all items by that value, descending
- Compute the running cumulative value and its percentage of the total
- Cut at roughly 70% and 90% cumulative to separate A, B, and C
- Review the boundary items manually before locking the classification
Assigning VED criticality
VED classification cannot be computed, because criticality is a clinical judgement about consequence of absence, not a property of the data. Vital items are those whose unavailability risks death or serious harm and for which there is no ready substitute — emergency drugs, antidotes, anti-snake venom, oxygen, resuscitation medicines, and agents specific to the services this hospital actually runs. Essential items are those whose absence causes significant deterioration in care or forces an inferior alternative. Desirable items are those whose absence causes inconvenience.
The classification must be hospital-specific. An item that is vital in a hospital with a cardiac catheterisation lab is desirable in one without. A paediatric formulation is vital where there is a neonatal unit and irrelevant where there is not. Copying a VED list from another hospital or a textbook produces a classification that is wrong in precisely the places where it matters most.
Assign V, E, and D through a clinical group — the Pharmacy and Therapeutics Committee is the natural home — with input from intensive care, emergency, anaesthesia, and the major specialties. Expect the exercise to take a couple of sessions the first time and much less on review. Ask a specific question for each candidate: if this item is unavailable for twenty-four hours, what happens to the patient who needs it? That framing produces far more consistent answers than asking people to rate importance.
The combined matrix and what each cell means
Crossing the two axes produces nine cells: AV, AE, AD, BV, BE, BD, CV, CE, and CD. A common convention groups them into three control categories. Category I comprises everything vital regardless of value — AV, BV, CV — plus the high-value essential and desirable items AE and AD. Category II covers BE, CE, and BD. Category III is CD alone: low value, low criticality, the long tail.
Two cells deserve specific attention because they are where single-axis thinking fails. AD items are expensive and clinically dispensable — high-cost items that are convenient rather than necessary — and they are the best available target for cost reduction, since reducing stock there carries little clinical risk. CV items are cheap and vital, and they are the classic stock-out: nobody watches a ₹15 item, and its absence during an emergency causes real harm.
The matrix is also a purchasing-authority map. Category I items justify senior approval, contract-based sourcing, and named accountability for availability. Category III items should be delegated as far down as the hospital is comfortable, ordered in bulk on long cycles, and reviewed rarely. Spending a buyer's attention equally across all nine cells is the specific waste the classification exists to eliminate.

“Our worst stock-out in three years was an item costing under twenty rupees. It had never once appeared on a purchase review because it never appeared on a value report.”
Differentiated reorder and review policies
The policies should differ along four dimensions: buffer stock, review frequency, ordering quantity, and approval authority. Category I items carry generous safety stock relative to lead time, are reviewed continuously with system alerts on any approach to the reorder point, are ordered in smaller and more frequent quantities to limit capital and expiry exposure on the expensive ones, and have a named owner responsible for availability.
Category II items sit on a periodic review — weekly or fortnightly — with moderate buffer and standard reorder logic. Category III items go on a long review cycle, monthly or quarterly, ordered in economic bulk quantities with generous buffer because the capital tied up is trivial and the transaction cost of frequent ordering is not.
Reorder level itself should be computed rather than assumed: average daily consumption multiplied by supplier lead time in days, plus a safety stock that reflects both demand variability and criticality. The criticality term is what makes this different from a textbook formula — a vital item warrants a buffer that a purely statistical service-level calculation would call excessive, because the cost of a stock-out is not a lost sale. HealUDoc can hold ABC and VED codes as item attributes and drive reorder alerts and approval routing from the combined class, so the policy applies automatically rather than depending on the buyer remembering which items are vital.
Policy by control category
- Category I: continuous review, high buffer, senior approval, named availability owner
- Category II: periodic review, moderate buffer, standard reorder logic
- Category III: long-cycle review, bulk ordering, delegated approval
- Class A within any category: smaller order quantities to limit capital and expiry risk
- CV items: reorder alerts regardless of value, and a physical count on a short cycle
Where blanket min-max rules fail, specifically
The most expensive failure is a uniform months-of-cover rule applied across the master. Holding two months of everything means holding two months of the ₹40,000 vial that is used four times a year, which is capital sitting on a shelf accumulating expiry risk. The same rule leaves the cheap vital item with two months of a consumption figure that understates emergency demand, because emergency use is spiky and averages hide spikes.
The second failure is reorder points frozen at their configuration values. Consumption changes when a new consultant joins, a service line opens, a protocol changes, or a seasonal pattern shifts, and a min-max set eighteen months ago encodes a hospital that no longer exists. Recompute from actual consumption on a schedule rather than editing values reactively after a stock-out.
The third is treating lead time as a constant. An item with an unreliable supplier needs a buffer reflecting the variability of the lead time, not its average, and vital items from single-source suppliers need either a qualified alternative or a deliberately larger buffer. Track actual received-versus-ordered lead times per supplier and feed the variability into the safety stock for critical items — this is the single highest-yield refinement most hospitals have not made.
Keeping the classification current
ABC classification should be recomputed at least twice a year, and quarterly where the case mix is changing. Items migrate between classes as consumption and prices shift, and the migrations are informative in themselves — an item moving from C to A usually means a new consultant, a new protocol, or a price increase, and all three are worth knowing about. HealUDoc dashboards can produce the consumption-value ranking directly from issue history, which reduces the recomputation to a review of the migration list rather than a spreadsheet exercise.
VED classification changes far less often and should be revisited annually, or immediately when a service line opens or closes. A new dialysis unit, cath lab, or neonatal intensive care unit changes what is vital in a way that no consumption-based recomputation will detect.
A useful adjunct is to layer a movement analysis over the classification: fast, slow, and non-moving items by issue frequency rather than value. The intersection that repays attention is a class A item that is also slow-moving — expensive stock turning over rarely — and a non-moving item that is classified vital, which is either correct emergency preparedness or an item nobody has needed since the protocol changed. Both are questions worth a buyer's afternoon.



