Fourth connector

Use your Fourth data for reporting, automation and AI.

Data Panda pulls your Fourth schedules, time clocks, payroll runs, employee records, inventory counts, recipes, menus and sales mix into the same warehouse as your point of sale, your finance system and your guest data. From one place we turn it into dashboards, automations and AI workflows that floor managers, area managers and the operations team use through the week, not only when group HQ asks for the labour-versus-revenue chart on Monday.

Fourth

About Fourth

Hospitality workforce and inventory management built for restaurants, pubs and hotels.

Fourth as it stands today was formed in July 2019 when Fourth (founded in 1999 in London around hospitality back-office software) and HotSchedules (founded in 1999 in Austin around restaurant scheduling) merged under common ownership of Marlin Equity Partners and Insight Partners. The combined company runs out of Austin, Texas, with major offices in London and Atlanta, and is led by CEO Scott Collison. Fourth reports more than 15,000 customers across over 100,000 sites worldwide, with around 2.5 million users on the platform.

The product covers the full hospitality back of house and front of house roster: HotSchedules for shift scheduling, time and attendance, manager logbook and team communication; HR, benefits administration and payroll services for hourly hospitality teams; and inventory management for purchasing, receiving, supplier invoices, recipes, menu engineering and dynamic production planning. On top sits Fourth Intelligence and Fourth iQ for forecasting and analytics. Pulled into a warehouse next to your POS, your finance system and your guest record, the Fourth data finally answers questions a Fourth report alone does not: which sites are running labour above the schedule the model recommended, which menu items lose margin once recipe cost is read at this week's invoice price, and which area managers are letting clock-in compliance drift before the wage bill confirms it.

What your Fourth data is for

What you get once Fourth is connected.

Labour and inventory reporting

Schedules, clock-ins, payroll, recipes and stock on one page across every site, brand and region.

Labour percentage and schedule-versus-actual hours per site, brand and region, against the model the planner used
Recipe cost movement against menu price per item and site, with the items where margin slipped past the threshold named
Stock-on-hand and variance against sales mix per site and week, with the supplier or item driving the variance called out

Process automation

Turn Fourth signals into the downstream work the rest of the stack expects, without an area manager chasing rows in HotSchedules.

Push approved Fourth payroll runs into the GL on the cost-centre key the finance system already uses
Open a recipe-review task the week ingredient inflation moves a menu item past its margin policy
Sync schedule changes into the operations dashboard the duty manager already reads on shift

AI workflows

Put schedules, clock-ins, recipes and sales mix behind AI that reads the full site-and-shift picture.

Demand and labour forecasting on POS sales, weather, local events and the published schedule, with the sites where the call diverged named
Variance explanation across stock counts, supplier invoices and sales mix, with the most likely driver per site flagged
Manager-shift summaries grounded in the actual clock-in record, the published schedule and the sales mix of the day

Custom apps on your data

Lightweight tools on Fourth data for area managers and operations leads who should not need a Fourth seat to read their own region.

Area-manager cockpit with labour percentage, schedule adherence and stock variance per site under their patch
GM scorecard with shift-cover, late clock-ins, recipe adherence and waste per period
Recipe-and-menu tracker with the items whose margin slipped per brand, site and last twelve weeks

Use cases

Use cases we deliver with Fourth data.

A list of concrete reports, automations and AI features we have built on Fourth data. Pick the one that matches your situation.

Labour percentage per siteLabour cost as a percentage of net sales per site, brand and week, with the sites past target named.

Schedule-versus-actual hoursHours scheduled in HotSchedules against hours clocked, per site, day-part and role.

Forecast accuracy per siteFourth labour and sales forecast against the actual outcome per site and week, with persistent over- or under-forecasters flagged.

Recipe cost-versus-menu marginCosted recipe against current menu price per item, with the items whose margin slipped past the threshold this period named.

Stock variance per siteCounted stock against theoretical-on-hand from sales mix and recipe usage, per site and category.

Supplier price driftInvoice price per ingredient against the costed recipe price, with the suppliers and items driving margin loss called out.

Clock-in complianceLate clock-ins, missed clock-outs and unauthorised overtime per site, manager and period.

Shift-cover and no-show rateShifts that opened, were swapped or stayed uncovered per site, day-part and role over the last quarter.

Sales-mix shift per siteMovement in product mix per day-part, site and brand, with the items pulling more or less revenue than the prior period named.

Waste and shrink per categoryRecorded waste, shrink and yield loss per category, site and period, with the categories repeatedly above policy named.

Area-manager scorecardComposite view per area manager combining labour percentage, schedule adherence and stock variance across the sites in their patch.

New-site rampLabour percentage, forecast accuracy and stock variance for sites in their first ninety days against the brand benchmark.

Real business questions

Answers you will finally get.

Are our sites running the schedule the labour model recommended, or are they drifting?

Hours scheduled in HotSchedules against hours clocked per site, day-part and role, joined to the recommended labour model and the actual sales the day produced. The area manager sees the four sites in the region where labour percentage drifted 1.4 points past target across the last six weeks, and the day-parts where the schedule itself was already over the model, instead of waiting for finance to call it out at period close.

Which menu items still earn the margin the recipe card promises?

Costed recipe against current invoice prices per ingredient and the live menu price per site. The brand team sees the items whose recipe cost crept up while the menu price did not, the sites where local supplier pricing eroded margin earlier than the rest, and the items that should be reworked or repositioned this menu cycle, instead of finding the margin slip in the quarterly P&L.

Is stock variance telling us something the next stock count will repeat?

Counted stock against theoretical-on-hand built from sales mix and recipe usage, per site, category and week. The operations director sees the categories where shrink keeps coming back at the same sites, and the suppliers whose deliveries match the invoice but not the count, before the next period's variance shows the same pattern again.

Value for everyone in the organisation

Where each function gets value.

For finance leaders

Fourth payroll runs and accrued wage cost lined up with the GL by cost centre and entity, period after period. Group finance stops chasing payroll exports per country, and the labour line in the next forecast is built on the schedule that is already published in HotSchedules, not on a flat percentage of last quarter.

For sales leaders

Sales-mix movement per day-part, site and brand against the menu changes and group bookings that went live. Brand and group sales see the new item that lifted attach rate at suburban sites but flattened at city centre, and the venues whose pipeline is already past the labour the schedule was built for, before the next campaign or booking push is written on a hunch.

For operations

Schedule adherence, clock-in compliance, stock variance and recipe margin on one page per site and area. The COO sees which area managers are letting the model drift, which sites carry both a labour overrun and a stock-variance pattern this period, and where the next site to open is already showing the rookie ramp shape from the last three openings.

Ideas

What you can automate with Fourth.

Fourth

Pair with Exact Online

Post Fourth payroll runs to the Exact Online GL per cost centre

Approved Fourth payroll runs land in the Exact Online general ledger on the cost-centre and entity keys finance already uses, period after period. Group finance stops pasting payroll exports into a journal template per country, and the wage line in the next forecast is built on the HotSchedules schedule that is published, not a flat percentage of last quarter. The variance review moves from arguing over export timing to working the sites where the labour-versus-sales line slipped past the model.

Fourth

Pair with Slack

Drive Fourth labour and stock-variance alerts from one Slack inbox

Schedule overruns, late clock-ins, missed deliveries and stock variances past their threshold land as a single morning summary in the area manager's Slack inbox, with a per-site channel post when labour percentage breaks target two days in a row. The duty manager sees an open shift on Friday morning instead of finding it at the start of service. Operations leads get the short list of sites where the labour and the stock signal both moved this week, instead of opening Fourth and HotSchedules in parallel to spot it.

Fourth

Pair with HiBob

Read Fourth pay and time on the HiBob employee record

Many hospitality groups run HiBob for the salaried HQ population and Fourth for the hourly site population. Each system holds half of the people picture; the warehouse holds both. Fourth time, scheduled hours, payroll cost and clock-in compliance land next to the HiBob worker, manager, site and tenure record, so the people-analytics view answers questions HiBob alone or Fourth alone cannot: which sites are running both an attrition spike and a labour overrun this quarter, which area managers carry a high-turnover patch alongside late clock-ins, and where the hourly-to-salaried ratio is drifting before the headcount plan is rewritten.

Fourth

Pair with HubSpot

Tie HubSpot guest CRM activity to Fourth labour and sales mix per site

HubSpot guest contacts, loyalty engagement and campaign response per site sit next to Fourth schedules, sales mix and labour percentage for the same week. The brand team sees the site where a loyalty campaign lifted attach rate but the schedule was not built for it, and the venues where the campaign landed on a day the labour model was already running tight. The next campaign brief reads off both sides instead of trusting that operations will absorb the lift.

Fourth

Pair with monday.com

Reflect Fourth recipe and menu actions into monday.com boards

Recipe changes, menu rollouts and supplier-switch tasks from Fourth reflect into the monday.com boards the brand and operations teams already work in, with status, owner and due-week kept in sync. Brand managers see which menu items are waiting on a costed recipe and which roll-out steps slipped past their site go-live date. The next menu cycle stops being a separate spreadsheet and becomes a read on the work the team is already running.

Fourth

Pair with Salesforce

Match Salesforce group-sales pipeline to Fourth site capacity

Group-event and corporate-bookings pipeline from Salesforce sits next to the Fourth schedule, labour model and inventory headroom of the venues those bookings would land in. Hotel and restaurant group sales see the venues where the next quarter's pipeline is already past the labour the schedule has been built for, and the sites where pipeline is thin precisely the weeks the kitchen has capacity. The forecast call moves from arguing over win-rate optimism to placing the next bookings where the venue is ready.

Your existing tools

Your data lands in a warehouse. Your BI tools read from it.

You keep the reporting tool you already have. We connect it to the warehouse where your Fourth data lives.

Power BI Microsoft

Fabric Microsoft

Snowflake Data warehouse

BigQuery Google

Tableau Visualisation

Excel Sheets & pivots

Three steps

From Fourth to answers in three steps.

Connect securely

OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.

Land in your warehouse

Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.

Reporting, automation, AI

We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.

Two ways to work with us

Pick the track that fits how you work.

Track 01

Self-serve

We set up the foundation. Your team builds on top.

Fourth connector configured and running
Warehouse set up in your cloud account
Clean access for your Power BI, Fabric or Tableau team
Documentation on what's in the data model
Sync monitoring so you're warned before reports break

Best fit Teams that already have a BI analyst or data engineer and want to own the build.

Track 02

Done for you

We build the whole thing, end to end.

Everything in Self-serve
Dashboards built to the questions your team actually asks
Automations between your systems
AI workflows scoped to real tasks your team runs
Custom apps where a dashboard does not cut it
Ongoing delivery at a pace that fits your team

Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.

Before you book

Frequently asked questions.

Who owns the data?

You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.

How fresh is the data?

Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.

Do I need a warehouse already?

No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.

Which Fourth tables land in the warehouse?

The connector pulls employees and managers, sites and brands, schedules and shifts from HotSchedules, time and attendance with clock-in and clock-out events, payroll runs and pay components, inventory items and suppliers, purchase orders and supplier invoices, recipes with their ingredient hierarchy, menus with item pricing, and sales mix joined back to the recipe and menu records. Authentication runs through a Fourth API token scoped to your account.

Does this cover both Fourth and HotSchedules data?

Yes. Since the 2019 merger Fourth and HotSchedules sit on the same vendor surface, but the underlying data still splits along the historical product lines: HotSchedules holds shift scheduling, time and attendance, manager logbook and team communication; Fourth holds HR, payroll, inventory, recipes, menus and the analytics layer. The connector reaches both and lands them on shared site and employee keys in the warehouse, so a labour-versus-sales view does not need a manager to keep two tabs open.

How are payroll, pay rates and other sensitive Fourth fields handled?

Payroll runs, individual pay rates and tax-related fields can be kept in restricted schemas that only finance, payroll and HR roles reach, while schedule adherence, labour percentage and stock variance power the dashboards the rest of the business uses. Access is enforced in the warehouse, not in each dashboard, so a new operations report cannot accidentally surface a pay rate it should not see.

GDPR-compliant

Data stays in the EU

You own the warehouse

A first deliverable live in four to six weeks.

We review your Fourth setup and the systems around it. Together we pick the first thing worth building.

Book a call See our other connectors