6 Practical Microsoft Copilot Use Cases

Finance, Procurement, Marketing and Sales

Many organisations now have Microsoft Copilot available which helps inside Excel but many teams still use spreadsheets the same way they did five or ten years ago.

They copy reports out of a system, then spend hours filtering columns, rebuilding formulas, cleaning messy rows and formatting charts for meetings. The result is not just wasted time but also potentially avoidable mistakes, because the more manual steps you add, the more chances there are to sort the wrong column, reference the wrong range or apply the wrong logic.

We have added six structured use cases to the Koshima Resources section of our website (details at the end of this blog)

Each one is based on a workflow that we have come across often and each one includes a clear objective, a starting prompt and a workflow that you can adapt to your own work.

If your business is looking at effective AI training then check out our task-tailored training courses with 30 days learner support at www.koshima.ai.

Microsoft Copilot Use Cases

Reducing Weekly Sales Review Time Using Copilot in Excel

Role: Regional Sales Leadership
Challenge: Weekly performance reviews require repeated filtering and sorting of exported CRM reports. Each new question during meetings means more clicks, more menus, and delays in discussion. Manual filtering creates slow meetings, repeated work, and risk of incorrect sorting.

Outcome: Copilot lets leaders describe the view they need in normal English. Copilot then applies the filters, sorting, and highlighting.

Result:

• 60 to 75% reduction in weekly review time
• Faster answers during meetings
• Fewer manual filtering errors
• Faster follow up actions to protect revenue

 Workflow available in koshima.ai/role-based-use-cases

Identifying Overdue Risk Patterns in Accounts Receivable

Role: Finance. Accounts Receivable
Challenge: Overdue invoice reviews often require pivot tables, SUMIF calculations and repeated filtering by customer and days overdue. This makes trend spotting slow and manual. A pivot table is an Excel tool that groups and summarises large tables, for example totals by customer or by month. A SUMIF formula adds numbers that match a condition, for example “sum all invoices where the customer is X” or “sum all balances over 60 days”. Risk patterns can be missed. Escalation is delayed.

Outcome: Copilot can group and summarise overdue exposure from clear instructions, flag outliers, and summarise balances so the team can focus on action.

Result:

• 60 to 70% reduction in weekly review time
• Earlier identification of high risk accounts
• Improved cash flow visibility
• Faster escalation and collection action

 Workflow available in koshima.ai/Role-Based-Use-Cases

Standardising Supplier Data in Procurement

Role: Procurement and Supplier Management
Challenge: Supplier quotations and ERP (enterprise resource planning system) that many organisations use to manage purchasing, finance, inventory, and operations data, exports arrive in inconsistent formats. Phone numbers, currencies, and supplier names often need manual correction before benchmarking. Data cleaning often takes an hour per dataset.

Outcome: Copilot can generate text and formatting formulas from clear instructions, then apply consistent standards across all rows.

Result:

• 40 to 80% reduction in data cleaning time
• More reliable supplier comparisons
• Reduced risk of selection errors
• Faster preparation for negotiation and approval cycles

 Workflow available in koshima.ai/Role-Based-Use-Cases

Adding Calculated Performance Metrics in Marketing

Role: Marketing Performance Management
Challenge: Metrics like cost per lead, conversion rate, and performance classification require manual formulas and nested IF logic across every export. A nested IF formula is an Excel formula where one IF condition sits inside another, often to handle multiple thresholds such as “if above X do this, if between Y and X do that, otherwise do something else”. Formula rebuild happens repeatedly. Small errors distort results.

Outcome: Copilot can build structured formulas from clear instructions and apply them across the dataset, including threshold logic.

Result:

• 60 to 75% reduction in formula build time
• Faster campaign comparison
• Reduced formula errors
• More time available for campaign improvement and budget decisions

 Workflow available in koshima.ai/Role-Based-Use-Cases

Writing Complex Commission Formulas in Finance Operations

Role: Finance Operations
Challenge: Commission and bonus structures involve layered IF logic, thresholds, and multipliers. Small syntax errors delay payroll checks and create rework. Syntax errors are formula mistakes like missing brackets, incorrect commas, or referencing the wrong cell range, which can cause Excel to return an error or calculate the wrong result. Manual bracket checking is time consuming.

Outcome: Copilot can generate the full commission formula logic from clear rules written in normal language, so the team can focus on checking the logic rather than building it.

Result:

• 50 to 70% reduction in formula build time
• Fewer syntax errors and less payroll rework
• Faster updates when commission rules change
• Lower audit and compliance exposure

Workflow available in koshima.ai/Role-Based-Use-Cases

Creating Executive Ready Charts Using Copilot in Excel

Role: Marketing and Sales Leadership
Challenge: Leaders manually select ranges, choose chart types and format visuals before executive meetings. Chart rebuild slows preparation and slows discussion in meetings. Wrong chart selection can misrepresent trends.

Outcome: Copilot can create charts from normal language instructions and support live refinements during a meeting, so the focus stays on the decision, not on formatting.

Result:

• 50 to 70% reduction in chart preparation time
• Better chart selection for trend and comparison data
• Less manual formatting
• More time discussing what the numbers mean

Workflow available in koshima.ai/Role-Based-Use-Cases

Your approach to learning

If your teams already have Copilot access, the key question is this:

 “Are they learning what the tool can do in theory or are they redesigning the way their reports, checks and updates are actually completed each week so the work becomes faster and more consistent?”

When a team rebuilds high frequency work properly using Copilot, it is common to see time savings between 20 and 75%, but the result depends on whether people are shown how to apply Copilot inside their tasks, with clear objectives and clear steps, rather than being shown features and left to experiment.

Koshima.ai training is customised and task-tailored.

We survey your team, identity the high friction tasks, build these as copilot workflows and teach your team step by step. They experience their tasks with Copilot as the learn. Explore out training courses at www.koshima.ai/training.

For selected programmes we provide 30 days of support so your team can contact us and we will help them through their tasks. See more at www.koshima.ai/AI-Productivity-Programme

You can explore the step by step workflows, starting prompts and structured objectives in the Resources section at www.koshima.ai/resources.

If you want to apply these use cases to your organisation’s datasets, thresholds and reporting, we can map the details with you so the workflow fits your team and reduces rework rather than adding another tool to learn.