ClearView: one forecast that drives ordering and staffing.

1Context

ClearView is QSS's restaurant management tool. Store and area managers use it to run several locations: sales, inventory, labour, reports and admin all live in one product.

This project is a design overhaul of the existing product. It focuses on the two big decisions managers make every week: what to order and who to roster.

2Problem

Both weekly calls depend on the same sales forecast, but in ClearView they were separate tasks worked out by hand. Two problems came up again and again.

3Research

I started by talking to the people who use ClearView every week.

• 3.1Manager interviews45-minute sessions, moving from warm-up questions to how they actually plan a week.
• 3.2Quotes and observations side by sideI record what managers say word for word, next to my own observations, so the findings stay close to their words.
• 3.3Two clear pain pointsRigid inventory control and hours that were hard to track. Both trace back to one forecast that never reached the tasks that need it.

4Audit

Next I mapped the first mockup to see what already existed and where the forecast got lost along the way.

The audit showed the problem wasn't missing features. The screens were there, but nothing connected the forecast to ordering and staffing, so I cut the work down to the six frames that tell that story.

5Define

From the research and audit I defined one idea: the Connected Forecast. One forecast flows through recipes into an inventory order and a labour schedule.

How might we help a manager turn one forecast into a confident order and a fair roster, without taking the decision out of their hands?

• 5.1AI as a collaboratorAI consolidates numbers and proposes changes. The manager reads the reasoning and decides.
• 5.2Traceable numbersEvery suggested figure shows where it came from, such as "Forecast × recipe".

6Key screens

The six screens follow one week of planning in order. Each one hands its numbers to the next, so a manager never re-enters a figure the system already knows.

1. Screen 1
   Dashboard

   The week at a glance. The long weekend is flagged up front, so the manager starts from what's coming, not from last week's reports.

2. Screen 2
   Sales forecast

   The week 27 forecast for Fri 4 to Sun 6 July, broken into extra servings. This is the single number everything else is built on.

3. Screen 3AI
   Recipes and servings

   Servings become ingredients through each recipe. The holiday mix is burger-heavy, so patties and buns go up and cheese barely moves.

4. Screen 4AI
   Inventory order

   A suggested order with quantities you can change line by line, each with its source and how much of the stock on hand it uses. This fixes the old, rigid inventory controls.

5. Screen 5AI
   Labour schedule

   The same forecast turns into extra hours per day at $115 of sales per labour hour, with suggested cover by name. Hours are visible instead of guessed.

6. Screen 6
   Review and approve

   Order and roster side by side with total cost and wage. Nothing goes to purchasing or the roster until the manager approves it.

The AI suggestion panel

This panel is the heart of the redesign. It went from a grey-box wireframe to a component used on Inventory, Recipes and Labour. Drag the line to compare.

Anatomy of the AI panel

1. Title and AI markSays what the panel explains, with an amber mark so AI content is never mistaken for system data.
2. Source line"Derived from week 27 forecast" comes before any number, so the manager knows what it's based on.
3. Plain-language reasoningTwo or three sentences on why, written the way a manager would explain it to a colleague.
4. One suggested numberThe headline figure in the display counter style, so it reads at a glance.
5. Accept or adjustA primary action and an equal way out. The manager always has the final call.
6. Table with a source columnEvery line shows where it came from, such as "Forecast × recipe", so any number can be traced.

7Try it

Change one thing and the rest follows. A forecast for a long weekend raises the ingredient order and the staffing hours together, and each suggestion shows where its numbers came from. Try it below: drag the forecast and watch both plans move.

A working model of the ClearView flow, rebuilt from the Figma screens with the same numbers. At 342 extra servings it matches the designed Inventory and Labour panels.

8Design system

The redesign uses ClearView's own type and colour styles, tightened so data reads first and AI content is always easy to spot.

9Reflection

The main lesson: a manager will trust a suggestion they can check. These three principles came out of the project.

• 9.1Show the source first.Every AI panel opens with its inputs (forecast, recipe, labour target), so managers can trust it or challenge it.
• 9.2Suggest, then ask.The plan stays a draft until the manager approves it, and any change sends it back to draft.
• 9.3Show consequences before commit.Stock pressure and staffing update together, so a manager sees the cost of a busier weekend before anything is ordered.

Before and after

Next: another round of manager interviews to test the six screens. Results will be added here.