# Monday.com for Lab Inventory and Experiment Tracking: A Template Guide By the end of this guide you will have two working monday.com boards, one for reagent and consumable inventory and one for experiments, connected so that a running experiment points back to the exact reagent lots it consumed. You will be able to build expiry alerts with formula columns, calculate how much of a kit you have used, assign ownership of every stock item, and export your structure if the lab changes tools later. You need three things before you start: a monday.com account (the free tier is enough for a small lab to test the setup), a spreadsheet or paper list of your current reagents and their lot numbers, and about two hours of uninterrupted setup time. You do not need any programming background. Every formula in this guide is copied directly into a formula column and produces a visible result in seconds. ## Why use monday.com for laboratory management Research runs on two kinds of records. The first is physical: what is in the freezer, how old it is, and who used it. The second is procedural: what was done, when, by whom, and with which materials. When either record lives in one person's notebook or a shared spreadsheet with no version history, the lab pays for it in repeated orders, failed repeats, and slow audits. The problem is common enough that it shows up in education research. In interviews with senior nursing students about their undergraduate research projects, participants named data collection, time management, and research planning as the major challenges of the process, and they identified structured mentorship and stronger institutional support as what they needed most [1]. A lab that gives every student a clear, visible structure for planning and tracking removes a large share of that friction on day one. Documentation drift is also measurable in clinical and laboratory settings. An audit of immunoglobulin A nephropathy care in Western Chongqing found that preoperative examination completion was documented for only 1.37% of enrolled patients, and documented medication use among eligible patients reached only 38.89%, despite standardized pathology staining rates of 100% [2]. The pattern is instructive. Steps that were baked into a fixed workflow got done and recorded. Steps that depended on informal tracking did not. A good monday.com template bakes your workflow in the same way. There is also a structural argument. Reviews of distributed agricultural research infrastructure describe the field moving from isolated sensing toward geographically distributed, long-term, data-driven closed-loop management [3]. Multi-site labs, core facilities, and collaborations with field stations face the same shift. A tool that centralizes inventory state and experiment state in one place, visible to everyone at once, is the coordination layer that kind of distributed work requires. To be clear about scope: monday.com is a general-purpose work management platform, not a [laboratory information management system](/knowledge/bioinformatics/lims-explained-lab-information-management-systems) (LIMS) or an electronic [lab notebook](/knowledge/molecular-biology/lab-notebook) (ELN). It excels at the coordination layer, meaning who owns what, what is running now, and what is running out. This guide shows you how to build that layer well and where the boundaries are. ## What you need before you start Gather these four inputs. Setup goes twice as fast with them in hand. 1. A complete inventory list. One row per item with its current location, lot number, expiry date if it has one, and approximate remaining quantity. An old order spreadsheet works as a starting point. 2. A naming convention. Decide the format for experiment IDs before you create a single row. A workable format is YEAR-INITIALS-SEQUENCE, for example 2026-ZK-014. Decide it once and write it down. 3. A list of people and their roles. Principal investigator, lab manager, postdocs, students, visiting researchers. You will assign edit access differently for each. 4. Your consumption units. Decide whether antibody stocks are counted in microliters or aliquots, whether kits are counted in reactions or boxes, and stick to it. Mixed units are the most common cause of broken quantity math later. ## Walkthrough 1: Building the lab inventory board ### Step 1. Create the board From your monday.com workspace, click **Add item** in the left sidebar, choose **New Board**, and name it "Lab Inventory". Start from a blank board rather than a prebuilt template, because prebuilt templates carry columns you will spend time deleting. Create four groups inside the board by clicking the group header and choosing **Rename group**: - Group 1: Antibodies and proteins - Group 2: Chemicals and buffers - Group 3: Kits and consumables - Group 4: Enzymes and [molecular biology](/blog/careers/molecular-biology) reagents Groups map naturally to storage logic. If your freezers are the primary mental model, group by freezer instead. Either works. Pick one and do not mix both, because items can only live in one group. ### Step 2. Add the core columns Click the plus icon at the right edge of the table to add columns. Set up this set: | Column | Type | Purpose | |--|--|--| | Item | Text (default) | Reagent name, for example "Taq polymerase, 500 U" | | Lot Number | Text | Manufacturer lot exactly as printed on the vial | | Location | Status or Text | Freezer, rack, and box position | | Initial Quantity | Numbers | Amount on arrival, in your chosen unit | | Current Quantity | Numbers | Amount remaining, updated after each use | | Unit | Status | µL, mg, reactions, boxes | | Expiry Date | Date | Manufacturer expiry, or blank for stable items | | Reorder Threshold | Numbers | Minimum quantity before you reorder | | Days to Expiry | Formula | Calculated, see Step 3 | | Usage | Formula | Calculated percent consumed | | Owner | People | Person responsible for the stock | | Data Sheet | File | Manufacturer certificate of analysis or datasheet | Set the **Unit** column with fixed labels and allow only those labels. This prevents the same item from being logged in microliters by one person and milliliters by another. ### Step 3. Add the formula columns Click the plus icon, choose **Formula**, and paste this into the formula editor: ``` DAYS({Expiry Date}, TODAY()) ``` Click **Save**. Every row with an expiry date now shows a number. A reagent expiring in 47 days shows `47`. A reagent that expired last week shows a negative number such as `-6`, which is your fastest visual check that something needs to be discarded. Add a second formula column named **Usage**: ``` ROUND(({Initial Quantity} - {Current Quantity}) / {Initial Quantity} * 100, 0) ``` Expected output for a kit that started at 96 reactions and has 24 left: ``` 75 ``` That reads as 75% consumed. The `ROUND(x, 0)` function rounds to zero decimal places, so you get whole numbers rather than long decimals in every row. Add a third formula column named **Reorder Flag**: ``` IF({Current Quantity} <= {Reorder Threshold}, "ORDER NOW", "OK") ``` A row where Current Quantity is 12 and Reorder Threshold is 20 shows `ORDER NOW`. A row where Current Quantity is 55 and Reorder Threshold is 20 shows `OK`. This single column becomes the basis of your weekly restock routine: sort or filter the board by Reorder Flag and order everything flagged. ### Step 4. Set up the expiry automation Formula columns cannot trigger automations, because monday.com treats them as calculated displays rather than changeable fields. This is a known and permanent limitation, so plan around it rather than against it. The standard workaround is a date-based automation on the raw Expiry Date column. Open **Automate** at the top of the board, search for "date", and select the automation of the form: ``` When {Expiry Date} arrives 30 days before, notify {Owner} ``` Then add a second one at 7 days before. Your reagent owner now receives two notifications before anything expires, and the formula column still shows the exact day count for anyone browsing the board. ### Step 5. Set permissions Click the board menu (three dots next to the board name), choose **Board permissions**, and restrict who can edit. A sensible pattern for a lab is full edit rights for the lab manager and permanent staff, edit rights limited to their own items for students, and view-only for visitors. Some permission options, such as restricting edits to specific columns, depend on your plan tier, so check what your account offers under board permissions before promising a design to your team. ## Walkthrough 2: Building the experiment tracking board ### Step 1. Create the board and columns Create a second board named "Experiment Tracker". Add these columns: | Column | Type | Purpose | |--|--|--| | Experiment ID | Text | Your naming convention, for example 2026-ZK-014 | | Project | Status | Which grant or aim this belongs to | | Status | Status | Planned, In Progress, Analysis, Complete | | Person | People | Who is running it | | Timeline | Timeline | Planned start and end dates | | Protocol | Link | URL to the protocol document | | Samples | Connect boards | Link to a samples board, described below | | Reagents Used | Connect boards | Link to inventory items | | Results | File | Raw data files and figure drafts | The **Timeline** column gives you a Gantt view of everything running in the lab at once, which is the single biggest visibility gain over a spreadsheet. ### Step 2. Use subitems for replicates and steps Hover over an item row, click the chevron that appears, and choose **Add subitem**. For an experiment with three technical replicates and five processing steps, create subitems like this: - 2026-ZK-014 (main item) - Replicate A - Replicate B - Replicate C - RNA extraction - cDNA synthesis - RT-qPCR run Each subitem can carry its own status and due date. A student can see at a glance that the extraction is done, the qPCR is pending, and two of three replicates are collected. This structure directly addresses the planning and time-management pain points that trainees report in research-skills studies [1], because the plan is visible rather than carried in someone's head. ### Step 3. Register structured projects when relevant If your lab runs systematic reviews or formal protocol-driven studies, add the structural fields directly to this board. Systematic review protocols are commonly registered with defined frameworks such as PICOS (population, intervention, comparator, outcomes, study design) and reported against PRISMA guidance [4]. Published systematic reviews in the life sciences similarly extract predefined fields such as demographic, genetic, clinical, and laboratory data from every included record [5]. Add one text column per framework field, for example a "PICOS population" column, and your review project becomes auditable inside the same tracker as your wet-lab work. ## Linking inventory to experiments ![Worked calculation of the Usage formula for a 96-reaction kit reduced to 72 reactions, giving 25 percent consumed.](/article-images/illustrations/monday-com-for-laboratory-management-usage-formula.webp) This is the step that turns two boards into one system. monday.com's **Connect boards** column creates live links between items on different boards. 1. On the Experiment Tracker, add a column of type **Connect boards** and point it at the Lab Inventory board. Name it "Reagents Used". 2. On any experiment item, click the connect cell and select the inventory items you consumed, for example the Taq polymerase lot and the specific kit. 3. Add a **Mirror** column next to it and mirror the Lot Number from the connected inventory item. The lot number now appears on the experiment record without being retyped. The payoff is reproducibility. When a result looks strange six months later, you open the experiment item and see exactly which lot of enzyme it used. Reviews of biosensor and diagnostic methods make the same point from the literature side: reported performance cannot be compared without recording the matrix, units, enrichment steps, and assay conditions, and reagent stability plus validated conditions remain major barriers to reproduction [6]. Your mirror columns are the practical version of that principle for your own lab. For consumption tracking, keep the math simple and manual. When an experiment consumes a quarter of a 96-reaction kit, open the inventory item, change Current Quantity from 96 to 72, and the Usage formula recalculates: ``` ROUND((96 - 72) / 96 * 100, 0) ``` ``` 25 ``` Updating the number takes five seconds and keeps every downstream calculation correct. Structured staging of work also helps here. A published clinical pharmacist program for hepatitis C treatment defined six explicit points of care, from therapy selection through follow-up and laboratory monitoring at 12 weeks, and quantified enrollments at each stage [7]. Translate that format to your tracker: define the fixed stages of your standard assay as subitems, and every run of that assay inherits the same checklist. Fixed stages get recorded. Informal steps get forgotten. ## A research software comparison: where monday.com fits When people search for the best software for researchers, they usually mean one of four categories. Knowing which problem each category solves keeps you from forcing a tool to do a job it was not built for. | Category | Built for | Strength | Weakness for labs | |--|--|--|--| | Spreadsheets | Any tabular data | Universal, zero learning curve | No permissions, no audit trail, no automation, one person "owns" the file | | monday.com and similar work platforms | Team coordination, tasks, inventory state | Automation, connected boards, ownership, dashboards | Not designed for structured experimental data capture or instrument integration | | Electronic lab notebooks (ELNs) | Protocols, observations, rich experimental data | Designed for experiment documentation and search | Typically weaker at general task and stock coordination | | LIMS | Regulated sample chains of custody | Sample tracking with compliance controls | Heavy setup, often overkill for a small academic lab | The honest conclusion of this research software comparison is that monday.com is the coordination layer, not the record of primary experimental data. Use it to answer who owns what, what is running now, what is running low, and which lot went into which experiment. Keep your primary quantitative data, instrument outputs, and full experimental detail in an ELN or analysis environment, and link to them from the Protocol and Results columns. Labs that try to make a work platform do the ELN's job end up with truncated records in both places. ## Designing boards your team will actually use A template only works if people enter data into it. Human factors research offers concrete guidance. A teaching experiment on wayfinding design at Sapienza University of Rome combined human-centred design with explicit task analysis to identify critical decision points before proposing any solution, with the explicit goal of reducing cognitive load for users with diverse needs [8]. Apply the same method to your boards: 1. List every person who will touch the board and what they need from it. A student needs to log usage in five seconds. The lab manager needs a restock list. The principal investigator needs a project overview. 2. Walk each person's most frequent task end to end and count the clicks. If logging a used aliquot takes more than three interactions, simplify the columns. 3. Remove any column that nobody has filled in after a month. Empty columns train people to ignore the board. Quality management literature reinforces the point. A scoping review of quality managers in healthcare describes their role as developing, leading, maintaining, and championing Quality Management Systems that set out organizational quality requirements and goals [9]. Someone in your lab must own the tracking system the same way. Without a named owner, boards accumulate stale entries, and stale entries destroy trust in the whole system faster than any technical flaw. ## Template summary The core monday.com for laboratory management template described in this guide reduces to the following structure. Copy it exactly, then adapt. | Board | Group | Key columns | Key formula or automation | |--|--|--|--| | Lab Inventory | Antibodies, chemicals, kits, enzymes | Lot Number, Location, Initial and Current Quantity, Expiry Date, Reorder Threshold, Owner, Data Sheet | `DAYS({Expiry Date}, TODAY())`, `IF({Current Quantity} <= {Reorder Threshold}, "ORDER NOW", "OK")`, notify automation at 30 and 7 days before expiry | | Experiment Tracker | One group per project or aim | Experiment ID, Status, Timeline, Protocol link, Reagents Used (connect boards), mirrored Lot Number, Results files | Subitems per replicate and per fixed stage | | Optional Samples board | One group per storage unit | Sample ID, Location, Collection Date, linked experiments | Connect boards link back to Experiment Tracker | ## Common Mistakes and Limitations ![Four warning signs for monday.com lab boards: mixed names, mixed units, expecting formula automations, and stale entries.](/article-images/illustrations/monday-com-for-laboratory-management-board-mistakes.webp) **Skipping the naming convention.** If two people log the same antibody as "anti-GAPDH" and "GAPDH Ab" on different rows, your quantity math is wrong from that day forward. Decide the canonical name for every item and forbid variants. **Mixing units in one column.** A Current Quantity column containing "50", "0.5", and "2 boxes" cannot drive a reorder formula. One unit per item, encoded in the Unit column. **Expecting formula columns to trigger automations.** They do not. All automations must hang off status, date, or people columns. This is why the expiry alert uses the raw date column and a fixed 30-day offset rather than the calculated day count. **Entering the full experimental record into monday.com.** The tracker is not an ELN. Concentrations, instrument parameters, and raw traces belong in your notebook or analysis environment, linked from the Protocol and Results columns. Copying them into a project management tool creates two conflicting versions of the truth. **Ignoring access tiers.** A shared admin login defeats the ownership model entirely. Every person gets their own account, even the rotating undergraduate. **Letting the board go stale.** A weekly five-minute review by the board owner, checking that Current Quantity values and experiment statuses match reality, is the difference between a trusted system and an abandoned one. Assign that review to a named person, in the spirit of the quality management role described in the healthcare literature [9]. **Overbuilding on day one.** Resist dashboards, dependencies, and time tracking until the two core boards have survived a month of real use. Complexity added before adoption is complexity that never gets used. Individual experimental and clinical decisions always require the relevant specialist, whether that is a PI for study design or a veterinarian or physician for animal and patient care. A tracking tool supports those decisions, it does not replace them. ## Frequently Asked Questions ### Is monday.com suitable as an electronic lab notebook? No. monday.com is a work management platform, not an ELN. It handles task coordination, inventory state, and linked records well, but it lacks the structured experimental data capture, protocol versioning, and witness-signing features that dedicated ELNs provide. Use it as the coordination layer and keep primary experimental records in an ELN or notebook. ### Can monday.com send expiry alerts for reagents? Yes. Set an automation on the Expiry Date column of the form "When a date arrives 30 days before, notify someone." Add a second alert at 7 days before. Note that the alert must be built on the date column itself, because formula columns cannot trigger automations. ### How much does monday.com cost for a small lab? Pricing is per seat and tiered, and it changes over time, so check the vendor's pricing page for current figures rather than relying on secondhand numbers. A free tier exists and is sufficient to build and test both boards in this guide before anyone commits budget. ### Can students and visiting researchers get limited access? Yes. monday.com supports view-only members and guest access, and board-level permissions can restrict who can edit what. The practical pattern is full edit rights for permanent staff, view or limited edit rights for trainees, and view-only for visitors. Some finer permission controls depend on your subscription tier. ### How does monday.com compare with Excel for lab inventory? Excel is faster to start and universally known, but it has no per-user permissions, no audit trail, no automations, and no live links between records. monday.com adds ownership, notifications, connected boards, and history, at the cost of adopting a new tool. Labs past two or three people almost always benefit from the structure. ### Can I track freezer contents and sample locations? Yes, in two ways. Simple setups use one inventory group per freezer and encode rack and box position in a Location column. Larger collections justify a separate Samples board with a connect boards column linking each sample back to the experiments that used it. ### What happens to our data if we stop using monday.com? Boards export to Excel files from the board menu, so your records remain portable. Connected-board relationships and automation history do not survive export as relationships, so if you plan to leave, export early and often, and keep your naming conventions tool-independent. ### Do formula columns update in real time? Yes. A formula column recalculates the moment any referenced column changes, so editing Current Quantity from 96 to 72 instantly updates the Usage percentage. The recalculated value is display-only, which again means it cannot itself fire an automation. ## Sources 1. [Nursing students' experiences of undergraduate research projects: a qualitative descriptive study.](https://pubmed.ncbi.nlm.nih.gov/42986058/) 2. [Current status and optimization strategies for immunoglobulin a nephropathy management in the Western Region of Chongqing, China: A cross-sectional study.](https://pubmed.ncbi.nlm.nih.gov/43012756/) 3. [Space-Air-Ground Integrated Networks for Smart Agriculture and Smart Breeding: A Review of SDN/NFV-Enabled Intelligent Resource Management.](https://pubmed.ncbi.nlm.nih.gov/42884378/) 4. [The impact of late-life depression on cognitive performance in older adults with mild cognitive impairment: a systematic review protocol.](https://pubmed.ncbi.nlm.nih.gov/43010078/) 5. [Diacylglycerol O-Acyltransferase 1 Deficiency in Children: A Systematic Review.](https://pubmed.ncbi.nlm.nih.gov/43010663/) 6. [Microfluidic Biosensors for the Detection of Foodborne Pathogens: A Comprehensive Review.](https://pubmed.ncbi.nlm.nih.gov/43010997/) 7. [Streamlining Hepatitis C Treatment: Implementation of a Clinical Pharmacist-Driven Medication Management Program.](https://pubmed.ncbi.nlm.nih.gov/43010163/) 8. [Cognitive Ergonomics and Universal Design for Museum Wayfinding: A Teaching Experiment Based on Human-Centred Design and Project-Based Learning.](https://pubmed.ncbi.nlm.nih.gov/42960780/) 9. [The Role of Quality Managers in Healthcare: A Scoping Review.](https://pubmed.ncbi.nlm.nih.gov/43012364/)