Scheduling - Application Overview
Objective. Teach the customer value of Scheduling: whether a schedule can cover demand while respecting rules, costs and employee constraints - and make concrete the sales 'shortage window, then planning/optimization/publication as distinct steps' demo and the CSM validation of forecast version, rules, skills and time zone plus publication ownership.
Scheduling turns a staffing requirement into a feasible, published schedule that covers demand while honouring rules, cost and employee constraints. This module teaches reps to show a coverage shortage and then separate planning, optimization and publication as distinct steps, and teaches CSMs to validate the forecast version and rules behind a schedule and to teach publication and change ownership safely - without trusting a clean-looking draft built on a stale forecast.
See it in the demo
The customer problem
Having the right total headcount (from Capacity Planning) does not mean the right people are on at the right times. Translating a requirement into actual shifts is where operations get stuck: coverage gaps at peak, idle overlaps in the trough, rule and labour-law violations, unfair or unstable rosters that drive attrition, and overtime spent papering over poor shift design. Most teams still build this by hand in a spreadsheet and discover the gaps only when the day goes wrong.
The business impact is service misses and avoidable labour cost at the interval level, plus compliance and fairness risk. A manually built roster that looks full can still miss the 2pm peak and violate a rest rule nobody checked. And because the schedule is edited and republished constantly, change without ownership creates confusion - employees do not know which version is live. The customer needs coverage they can trust, built within their rules, and a clean publication process.
How Time Champ addresses it
Scheduling builds feasible schedules against demand and constraints. The demo areas include Planner, coverage, optimization, scenarios, shift designer, requests, overtime and VTO, open shifts, meetings, employee portal, publication, audit, analytics and configuration.
The value is in three distinct steps the demo keeps separate. Planning lays shifts against the requirement and shows coverage by interval. Optimization improves that draft against rules, cost and constraints (reducing shortage and overtime while respecting skills and labour rules). Publication makes a version live, with an audit trail and an employee portal for acknowledgment, requests and open shifts / VTO. Keeping these steps distinct is itself the teaching point: a draft is not a published schedule, and optimization operates on whatever forecast the draft was built from.
Confirm with product which labour rules, integrations and publication controls apply for a customer; the demo shows the model on seeded data.
The value and how to measure it
The value is coverage you can trust, built within the customer's rules, published cleanly: fewer interval-level service misses, less overtime from poor shift design, fewer rule violations, and employees who know which schedule is live and can transact requests through a portal.
Measure with the grounding's candidate measures: coverage by interval (not just daily totals - the peak is where service breaks); rule exceptions (violations the schedule still carries, which should trend to zero before publication); acknowledgment (do employees confirm their published shifts); publication timeliness (is the schedule published with enough notice, a fairness and attrition driver); and schedule stability (how much it churns after publication - excessive change signals a weak forecast or process). The honest value is a feasible, rule-respecting, acknowledged schedule - not a claim of zero overtime.
Sales task made concrete
Your task is to show a shortage window, then explain planning, optimization and publication as distinct steps. Concretely:
- Open the Schedule planner (https://schedules.demo.timechamp.io/#/planner) from the overview (https://schedules.demo.timechamp.io/#/home) and show coverage with a visible shortage window - an interval where required exceeds scheduled.
- Step 1 - planning: show the draft laid against the requirement and name the gap.
- Step 2 - optimization (https://schedules.demo.timechamp.io/#/optimize): run it and show the shortage and overtime fall while rules and skills are respected. Be explicit: 'Optimization reshapes the draft against rules and cost - it does not change the forecast underneath it.'
- Step 3 - publication: show that a version becomes live with an audit trail and portal acknowledgment. 'A draft is not a live schedule until it is published.'
Discovery to pair: 'How do you build rosters today, and when do you discover coverage gaps?' 'How do you know a schedule respects your labour rules before it goes out?' 'How do employees know which version is live, and how do they request changes?'
CSM task made concrete
Your task is to validate forecast version, rules, skills and time zone, review coverage and violations, and teach publication and change ownership in a safe sandbox. A routine:
- Forecast version: confirm which capacity/forecast version the schedule is built on. This is the number-one adoption trap (see interpretation check) - a draft on an old forecast looks valid while failing current demand.
- Rules and skills: validate labour rules, rest/overtime constraints and skill requirements are configured to the customer's policy.
- Time zone: confirm time zones for multi-site teams, or coverage windows will be misread.
- Coverage and violations: review coverage by interval and clear rule exceptions before publication.
- Publication and change ownership: teach, in a sandbox, who may publish, how changes are made, and how employees acknowledge - so change is owned, not chaotic. Ownership and a clean publication discipline are the adoption deliverable, not the first optimised draft.
Objections and honest limits
'The draft looks fully covered, so we are done.' This is the core interpretation check: a draft built on an old forecast may look valid while failing the current coverage requirement. Always confirm the schedule is built on the live forecast version before trusting a green coverage view.
'Optimization will fix everything automatically.' Optimization reshapes the draft against rules and cost; it cannot fix a wrong forecast or missing rules. Garbage demand in, confident-but-wrong schedule out. It is a step, not magic.
'We already schedule in a spreadsheet / another WFM tool.' Spreadsheets do not check rules, optimise coverage, or give an audited publication and employee portal. Against an incumbent WFM, qualify its actual optimisation and publication capabilities before positioning.
Honest limit: feasibility depends on correct rules, skills and the current forecast. Supported labour rules, integrations and publication controls for a customer must be confirmed with product.
Interpretation check
A draft on an old forecast may look valid while failing the current coverage requirement. A green coverage view only means the draft matches the forecast it was built on - always confirm it is built on the live forecast version before trusting it.
In the field
A contact-centre or RCM operation building rosters against a Capacity Planning requirement (e.g. OVO-style contact centre): Scheduling turns the requirement into interval-level coverage within labour rules and publishes a single acknowledged version - ending the spreadsheet rosters that hide peak gaps and rule violations until the day goes wrong.
Practical task
Using the demo, run the three steps on one shortage window: capture coverage before and after optimization (noting rules respected), then publish and show the audit/acknowledgment. Write the four items you would validate with a customer before trusting any schedule (forecast version, rules/skills, time zone, cleared violations) and state who should own publication.
Self-check
A manager shows a fully-covered draft and wants to publish. What do you check first?
Which forecast version the draft is built on. A draft on a stale forecast can look fully covered while failing current demand. Confirm it is the live forecast before trusting the coverage view.
Why does the demo keep planning, optimization and publication as distinct steps?
Because conflating them creates the biggest misreads: a draft is not a live schedule, and optimization reshapes the draft against rules/cost but does not change the forecast underneath. Separating them is the teaching point.
A customer expects optimization to 'fix everything.' What is the honest framing?
Optimization improves a draft against rules and cost; it cannot repair a wrong forecast or missing rules. Correct inputs first, then optimise - it is a step, not magic.
What is the CSM's real adoption deliverable for Scheduling, beyond a good draft?
Publication and change ownership: who may publish, how changes are made and acknowledged, built on the correct forecast and rules - so the live schedule is trusted and change is owned, not chaotic.
Verified vs demo. The planner, coverage-by-interval, optimization, publication/audit and employee portal are demo-shown on seeded data; supported labour rules, integrations, time-zone handling and publication controls for a customer must be confirmed with product.