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Praval Technologies

Case study

Store operations and employee service on ServiceNow

A mid-size US retail chain gave 4,200 store staff one place to raise IT, HR and facilities issues, with self-service answers and automated routing replacing phone calls and chased emails.

Median resolution time
↓58%Median resolution time3.2 days → 1.3 days
Register and system downtime
↓31%Register and system downtime
Requests self-served
34%Requests self-servedResolved without a ticket
Staff satisfaction (CSAT)
+22 ptsStaff satisfaction (CSAT)61% → 83% satisfied

A broken register, and nobody to call

A Minneapolis-based retail chain runs 60 stores with roughly 4,200 store associates. When a register froze, a new hire's login didn't work, or a freezer alarm went off, staff had no reliable channel, so they improvised. The engagement ran around five months, phased, for the Head of Retail Operations and IT.

Three numbers, no answers. IT, HR and facilities each had their own phone line and inbox. Staff guessed which to call, and often guessed wrong.

Nothing was tracked. Requests lived in voicemails, texts to a district manager, and emails. No ticket, no owner, no visibility.

Selling time lost to chasing. Store managers spent hours a week following up on issues instead of running the floor.

The same questions, endlessly. Password resets, shift-swap rules and PPE orders made up much of the volume, all answerable without a human.

Downtime on the floor, hours off the schedule

Unresolved issues don't stay in the back office: a dead register or a locked-out associate costs trading hours and morale.

  • 3.2 days median time to resolve a store request end to end.
  • 6 hrs per store manager, per week, spent chasing open issues.
  • 41% of requests misrouted at least once before reaching the right team.

Roughly 8,600 requests a month, concentrated in weekend trading peaks, precisely when head-office support desks were thinnest. Requests per hour, by day and daypart:

Open–11a11a–2p2p–6p6p–close
Mon18262212
Tue16242011
Wed17252112
Thu19282414
Fri24363321
Sat31524829
Sun22383419

"A register goes down on a Saturday and my closing manager is calling three numbers and leaving voicemails. That's not a support process; that's hoping someone picks up."

— Head of Retail Operations, Minneapolis-based retail chain

What store staff actually needed

We shadowed shifts across store formats and analysed six months of request history. The pattern: most volume was repetitive, most delay came from routing, and anything requiring a desktop login wouldn't be used on the floor.

  • One front door for IT, HR and facilities: no guessing.
  • Mobile-first: usable from the floor in under a minute.
  • Answer common questions without creating a ticket at all.
  • Route automatically to the right team, first time.
  • Prioritise by trading impact: a dead register outranks a stapler.
  • Give managers visibility of every open issue in their store.

One front door, and a request that routes itself

A ServiceNow employee-service portal built for the shop floor: staff describe the problem in plain language on a shared store device or their phone, and the platform either answers it outright or sends it to the right queue with the right priority.

How a request now travels:

  1. Raise it: on the mobile portal or a store device, in plain language.
  2. Answer first: a knowledge article or guided fix is offered instantly.
  3. Classify and route: category, store, priority and team assigned automatically across IT and access (registers, logins, scanners), facilities (refrigeration, HVAC, lighting), HR (shifts, pay queries, onboarding), or store systems (price files, peripherals, network).
  4. Resolve and confirm: SLA tracked; the requester is notified and asked to rate it.

Built for the floor. A mobile-first portal designed for a two-minute break, not a back-office desktop.

Answers before tickets. A curated knowledge base resolves the repeat questions without involving a queue.

Routing that just works. Category, store and trading impact decide the queue and priority, no triage desk in between.

Visibility by store. Managers and district leads see open issues, ageing and SLA breaches for their own stores.

Piloted in ten stores, then rolled out

A deliberately small pilot proved the routing rules before any store lost its old phone number. Then the rollout moved in waves, region by region.

  1. Shadow and analyse: shift observation across store formats, plus six months of request history categorised and timed.
  2. Design the catalogue: build the request catalogue and knowledge base around the words staff actually use, not internal team names.
  3. Pilot in ten stores: run alongside existing channels; tune routing rules and priorities against real traffic.
  4. Automate and integrate: connect IT, HR and facilities queues, add SLA tracking, and automate the highest-volume fixes.
  5. Roll out and retire: region-by-region rollout with floor training, then retire the old phone lines and shared inboxes.

A third of requests never become tickets, and most of what remains routes straight to the right team without human triage:

Of 8,600 requests a monthVolumeShare
Self-served (knowledge and guided fixes)2,90034%
Auto-routed (no triage desk)4,80056%
Manual triage (exceptions only)90010%

Priority is set by trading impact, so a dead register is chased harder than a stationery order, and the numbers now reflect that. SLA attainment by priority, over the trailing quarter after rollout:

PriorityTargetAttainment
P1 · Trading stopped4 hours96%
P2 · Degraded1 day91%
P3 · Routine3 days84%

The old queue accumulated a long tail of forgotten issues. Automated routing and SLA alerts cleared it and kept it clear:

Open tickets by ageBeforeAfter
Under 1 day210540
1–3 days330225
4–7 days29080
Over 7 days25025
Total open1,080870, far younger

Staff back on the floor, issues off the manager's desk

Store teams now raise an issue in under a minute and get an answer or an owner immediately. A third of requests resolve themselves, managers stop chasing, and retail ops can finally see which stores and systems generate the most pain, which is turning into the next round of fixes.

Result
Median resolution3.2 days → 1.3 days
System downtime↓ 31%
Self-served34%
Staff CSAT+22 pts

Built on ServiceNow.