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Priced from the ERP, approved against the margin floor, signed before the week turns

Quotes built, discounts approved and signed within the day

Prices, conditions and stock come from the ERP, the discount rule decides or names an approver in Microsoft Teams, and the quote leaves as a signed document the same day.

DepartmentalMicrosoft TeamsHuman in the loopDeterministic automation
1,350quotes a month leave this illustrative building-materials manufacturer, and 300 of them wait on a discount that nobody records as a decision.

Executive summary

Challenge

Your margin floor is enforced by a thumbs-up in a chat and audited three weeks later.

What changes

The quote starts where the deal already lives: a seller opens the opportunity in the CRM.

Business value

Quotes leave the same day, because the lookups, the arithmetic, the document and the filing no longer wait for a free hour.

Systems involved

SAP ECC or SAP S/4HANA, read only in this workflow; Salesforce or Microsoft Dynamics 365 Sales; SharePoint quote library

Business problem

Quoting

A quote is assembled from four sources that do not talk to each other: prices and customer conditions in SAP, stock and lead times in the warehouse system, the discount policy in a PDF circulated two years ago, and the seller's memory of what worked with this contractor last time. Excel is where the four meet, which is why the errors repeat: a price from the wrong period, a discount stacked on a condition that already contained it, a lead time that was a guess.

Discount approval is the part that looks free and is not. It happens in a chat, on a phone, occasionally in a corridor, and none of it is a record. The manager who says yes rarely has the margin in front of them, because working it out would mean opening SAP for a deal they have thirty seconds for. Finance sees the consequence months later, when the product-group margin is thinner than planned and nobody can point at the decisions that made it so.

Then the document. Every quote is a copy of an older one, so terms drift and a payment clause from a special case spreads through a region. Acceptance returns as a scanned signature or a sentence in an email, which the order desk retypes into SAP. The process survives because each part is somebody's working routine, and because finance owns the floors but not the moment one is breached.

How it works today

This is what we find in most B2B manufacturers before the quote flow is automated.

  1. PersonThe seller asks inside sales for the customer's conditions, or looks them up in SAP when the day allows
  2. PersonStock and lead times are checked in a warehouse channel and typed into a spreadsheet copied from an older quote
  3. WaitingA discount above the seller's authority waits for a manager who is travelling, half a day to two days
  4. Risk of errorThe approval arrives as a chat message or a call, so nothing records the margin the approver saw
  5. WaitingThe quote is emailed from the seller's own mailbox, and acceptance returns as a scanned signature or a "go ahead" email
  6. PersonThe order desk retypes the accepted lines into SAP from the PDF
  7. Risk of errorThe sub-floor margin surfaces at month-end, after the pallets have shipped
PersonWaitingRisk of error

Why the current process costs more than it appears

The budget shows headcount, not what it is spent on.

  • Quoting hours are the visible cost and the smaller one. The expensive part is a discount granted without the margin in view, three hundred times a month, each one defensible alone and none decided against a number.
  • Slow quotes lose deals to whoever answered first, and nothing records a loss caused by elapsed time. The pipeline shows it as lost on price, the only reason field anyone selects.
  • Terms copied from an older quote become disputes later: an invoice argument, a credit note and a call from the contractor's buyer, none of it charged back to the quote that caused it. Stock promised on a guess becomes a backorder in the same way.
  • Pricing knowledge sits with the longest-serving inside-sales specialists, so when one leaves, quote quality drops in a way that shows up as margin rather than as a resignation.

Cost of inaction

Twelve months of quote assembly at today's pace≈ €248,160
The discount chase beside it, over the same twelve months≈ €64,800
Both, carried for the eighteen months until the next price-list revision≈ €469,440

Two things grow on their own here. Quote volume rises with every distributor signed and product line added, each carrying the same manual minutes, so the first row is a floor rather than a forecast. Input-cost volatility shortens the life of a price list at the same time, so more quotes are built on a version already replaced.

The quieter risk is that nothing about the discounts changes. Three hundred approvals a month continue without a margin in view, and the total given away rises because volume rose, not because anyone decided it should. The audit finding repeats each year, and the answer each year is that approvals do happen, in a chat that has since scrolled.

Illustrative scenario

A plausible organisation with realistic proportions. The figures are there to be recalculated on your data; they are not a client result.

Organisation

A building-materials manufacturer of insulation, roofing membranes and accessories, 1,100 employees, selling through distributors and directly to large contractors in Poland, Czechia and the Baltics. Salesforce is the CRM, SAP ECC holds prices, conditions, stock and lead times, and Microsoft 365 is the collaboration platform.

Volume

1,350 quotes a month from 28 field sellers and nine inside-sales specialists; roughly 300 carry a discount request above the seller's own authority.

Current process

Quotes are built in Excel from prices looked up by hand, sent as PDFs from individual mailboxes, approved informally when a discount is needed, and retyped into SAP once the customer accepts.

Bottleneck

About 38 minutes of assembly per quote before anyone thinks about the customer, 25 minutes of chasing and review on each discount approval, and one to two days elapsed on the quotes that matter most.

Solution

A robot prices the quote from SAP conditions, stock and lead times, the rules decide what the seller may grant alone, exceptions reach the named approver in the Microsoft Teams Approvals app with the margin impact on the card, and the document comes from one approved Microsoft Word template, filed in SharePoint and sent for signature.

Potential outcome

In the modelled case the quote leaves the same day, every discount below the floor carries an approver and a margin figure, and accepted lines reach order entry as structured data. The figures are a model on stated assumptions, not a client measurement.

Proposed solution

The quote starts where the deal already lives: a seller opens the opportunity in the CRM, or fills a short form in Microsoft Teams for enquiries that never become opportunities, naming customer, products, quantities and requested delivery. A UiPath robot reads that customer's conditions, prices, stock and lead times from SAP through the BAPI and OData connectors, prices every line and calculates the margin against the product-group floor finance owns.

The discount rules decide next, and this is the part that changes the economics. Rules written from the client's own policy establish what a seller may grant without asking, what the regional manager may approve and what reaches the commercial director. Anything above the seller's authority becomes an approval in the Microsoft Teams Approvals app carrying the margin impact in euros, the floor, the customer's discount history and the quote itself, so the manager decides against a number rather than a screenshot, under their own Microsoft Entra ID identity and with the event audited in Microsoft Purview.

The robot then fills the approved Microsoft Word template, renders the PDF, files both in a SharePoint library with customer, opportunity, margin and approver as metadata, and attaches the document to the opportunity. The quote goes for signature through SharePoint eSignature, the signed copy returns with its audit trail, and accepted lines reach order entry as data. Power BI shows cycle time, approval turnaround, discount depth and win rate by band. No AI is involved, deliberately: pricing has to be reproducible for a controller.

Native capabilities used

Microsoft Teams Approvals app with templates and Microsoft Purview audit; SharePoint eSignature returning the signed copy to the library; SharePoint libraries with metadata, permissions and retention; UiPath Orchestrator triggers, queues, credential store and audit

What we build

The pricing and margin calculation against the floor, the discount rules and thresholds, the routing and the approval card, the Microsoft Word template and its generation, SharePoint filing, CRM write-back, the hand-off to order entry and the Power BI report

Custom integration

SAP prices, conditions, stock and lead times through the UiPath SAP BAPI and OData connectors, with screen automation only where no interface exposes a condition type; the CRM opportunity, attachment and status through the Salesforce or Microsoft Dynamics 365 CRM connector

How the automated process works

  1. SystemThe request is picked up from the CRM opportunity or the Teams form, and a robot reads conditions, prices, stock and lead times from SAP and prices every line
  2. AutomationMargin is calculated per line and per quote against the product-group floor, and the discount rules are evaluated
  3. PersonRequests above the seller's authority reach the regional manager or commercial director in the Teams Approvals app, margin and floor on the card
  4. AutomationApproved and in-authority quotes are generated from the Microsoft Word template, rendered to PDF and filed in SharePoint
  5. AutomationThe document is attached to the CRM opportunity and sent to the customer for signature through SharePoint eSignature
  6. SystemThe signed copy returns to the library, the opportunity is updated, and accepted lines reach order entry as structured data
  7. AutomationCycle time, approval turnaround, discount depth and win rate by band are refreshed in Power BI
SystemAutomationPerson

Human-in-the-loop model

Automation handles

  • Reading prices, conditions, stock and lead times, pricing every line, and calculating margin against the floor
  • Routing each exception to the approver the policy names, with the numbers attached
  • Document generation, filing, CRM attachment and the signature request
  • The hand-off of accepted lines to order entry and the reporting

People decide

  • What to offer this customer and how to position it, the part of quoting that earns the margin
  • Every discount beyond the seller's authority, now against a figure rather than a screenshot
  • Pricing policy itself: the floors, the thresholds and who may approve what
  • Anything the rules cannot price, such as a new product without a condition record

Before and after

BeforeAfter
Assembly time per quote38 minminutes, spent on positioning
Elapsed time from request to quote sent1 to 2 dayssame day
Approvals with the margin visible to the approverrarelyevery one
Evidence behind a discount decisiona chat messageapprover, figure, timestamp, audit event
Accepted quote reaching order entryretyped from a PDFstructured lines

Systems and integrations

Everything below runs on licences and systems you already hold, or would need anyway.

Inputs

  • CRM opportunity
  • short quote form in Microsoft Teams
  • SAP list prices, customer conditions, stock and lead times

Automation layer

  • UiPath Orchestrator
  • UiPath Robots
  • UiPath Integration Service
  • the pricing, margin and discount rule set

Target systems

  • SAP ECC or SAP S/4HANA, read only in this workflow
  • Salesforce or Microsoft Dynamics 365 Sales
  • SharePoint quote library
  • Power BI

Human touchpoints: Microsoft Teams Approvals for discounts; a Teams card for pricing exceptions; SharePoint eSignature for the customer's signature

CRM opportunityUiPath OrchestratorUiPath RobotsSAP ECCMicrosoft Teams Approvals for discounts

Technologies used

UiPath Robots + Orchestrator

price the quote, apply the rules, generate and file the document, with queues, retries and audit

A
UiPath Integration Service (SAP BAPI and OData connectors)

prices, conditions, stock and lead times read over interfaces, not screens

A
UiPath Integration Service (Salesforce and Microsoft Dynamics 365 CRM connectors)

the request from the opportunity, the document attached back, the status updated

A
Microsoft Teams (Approvals app)

discount decisions above the seller's authority, margin on the card, audit event in Microsoft Purview

A
Microsoft Word

the one approved quote template the robot fills, rendered to PDF

A
Microsoft SharePoint

quote library with customer, opportunity, margin and approver as metadata

A
SharePoint eSignature

the quote sent for signature and the signed copy returned with its trail

A
Power BI

cycle time, approval turnaround, discount depth, win rate by band

A
Averified product capability (vendor documentation)

Illustrative economic model

A model, not a promise.

Illustrative model
742 quote-equivalents a month (1,350 × 0.55 automatable) × 38 minutes≈ 470 h / month
470 h × €44 fully loaded cost of quoting work≈ €20,680 / month
× 12 months≈ €248,160 / year
Annual quoting capacity released (illustrative)≈ €248,160

Two costs sit in this process and the calculator prices only the first. Assembly runs at 38 minutes across price lookups, the stock check, the document, the PDF, sending and filing; 0.55 of that is mechanical work a robot can take, so the 1,350 quotes a month enter as 742 quote-equivalents while the seller keeps positioning and the customer conversation. €44 is a fully loaded blended hourly cost for inside-sales and seller quoting time in Central Europe. The second cost, 300 approvals a month at 25 minutes of chasing and review, 0.6 of it avoidable, at €72 an hour of manager time, is about €5,400 a month and is carried into the next section instead. Nothing here was measured at a client.

Run the numbers on your data

hours released per month
of annual capacity released

An illustrative estimate from your own inputs. It models released capacity; it is not a promise of savings.

Business benefits

  • Quotes leave the same day, because the lookups, the arithmetic, the document and the filing no longer wait for a free hour
  • Margin is protected before the order rather than explained after it: nothing goes out below the floor without a named approver and a figure
  • Every quote carries the same terms, because there is one template and sales operations owns it rather than whoever sent the last quote
  • Order entry receives structured lines instead of a PDF, which removes a class of errors from delivery and invoicing, while approval turnaround per manager and win rate by discount band become reportable

The management view

  • Every open quote has an age, an owner and an approval status, so the pipeline review stops depending on memory
  • Discount decisions become records with approver, margin and reason attached, available to an auditor without a mailbox search
  • Pricing policy changes are made once in the rule set and apply to every seller the next morning, and the process stops being a set of personal routines

Board-level KPIs

quote cycle time from request to sentapproval turnaround per managershare of quotes priced without exceptionsub-floor quotes issuedwin rate by discount band

Security and governance

Security is designed with the process, not after it.

  • The robot reads SAP through a service user restricted to price, condition, stock and customer master reads and posts nothing, so a pricing error cannot become an order
  • Discount approvals happen only in the Teams Approvals app under the approver's own Microsoft Entra ID identity, which keeps the seller, the approver and the document generator separate
  • Approval events and signature requests are written to the Microsoft Purview audit log, so the evidence exists without anyone maintaining it
  • Quote documents inherit the library's permissions and a retention label, signed copies keep the eSignature trail, and pricing rules and floors are versioned artefacts changed only by finance and sales operations; customer data stays inside the Microsoft 365 EU Data Boundary and the EU region of UiPath Automation Cloud, with service credentials in a managed store

Why now

01

Input-cost volatility has moved discount discipline from a sales-operations topic to a board one, and price lists are revised more often, so more quotes are assembled from a superseded version

02

SharePoint eSignature now sends a quote for signature and returns the signed copy to the same library without a separate document platform, and the SAP BAPI and OData connectors read conditions and stock over interfaces, which removes most of the custom development this used to need

03

Leaving it alone costs a modelled €20,680 a month in quoting hours and €5,400 in approval chasing, before any margin given away below the floor

Relevant executive roles

Sales Director

Quotes leave the same day, approvals stop being the reason a deal waits, and win rate by discount band becomes something to manage rather than argue about

CFO

Every discount below the floor carries a named approver and the figure they saw, so margin is protected before the order instead of reconstructed after it

COO

Accepted quotes reach order entry as structured lines, which removes a recurring source of delivery and invoicing errors

Common questions and objections

We are implementing a configure-price-quote tool, so this is redundant.

It is a different layer. That tool handles configuration and pricing logic; this workflow supplies the ERP data it prices from, the approval discipline in Teams, the document, the signature and the hand-off to order entry.

Our sellers need flexibility on discounts.

They keep it. The rules define who may approve what, not what may be offered, and an approval that arrives with the margin on the card is answered in minutes instead of chased for a day.

Customer-specific pricing here is too complicated to automate.

The complication already lives in SAP conditions, and the robot reads what SAP computes rather than reimplementing it. Cases outside the rules go to a pricing specialist with the calculation finished.

When this is not the right solution

  • Quotes are engineered configurations needing design work before anything can be priced; a configuration tool belongs first, and this flow sits behind it
  • Volumes are low and every price is negotiated individually with no price master to read from, so the rules have nothing to enforce
  • The discount policy does not exist in writing. Rules cannot enforce a policy nobody has agreed, and writing one is a management task

A question for the next management meeting

If the commercial director had to state the margin given away in last month's discount approvals, where would that number come from and how long would it take?

Implementation approach

The first week looks the same at every client: we look at the data.

We deliver

  • Twenty to thirty recent quotes and their approval trail, repriced under your own policy to show rule coverage and margin at stake
  • The target flow designed with sales operations and finance: who approves what, at which threshold
  • The pricing and discount rule set, versioned and owned by finance rather than buried in code, with the SAP and CRM integration, quote generation from a rebuilt Microsoft Word template, SharePoint filing and e‑signature dispatch
  • The Teams approval experience, the Power BI report and a pilot in one region before rollout with hypercare

We need from you

  • SAP read access for a service user covering prices, conditions, stock and customer master data
  • The CRM sandbox and a technical account for it
  • The current quote template, the terms in use and the discount policy in writing
  • A sales-operations owner for the template and the rules, and a finance owner for the floors

Stages

Discovery

Quotes and approvals repriced under the written policy, to size rule coverage and exceptions

Design

Target flow, rules, thresholds, template structure, security model

Build

SAP and CRM integration, document generation, Teams approvals, filing and signature

Validation

Historical quotes repriced by the robot and compared line by line with what was sent

Go-live

One region and product group under supervision, then rollout with the old route retired per region

Optimisation

Rule tuning against the exception log, then extension to further product groups and countries

Departmental. Effort is driven by how much pricing lives in SAP conditions rather than in habit, how many thresholds the policy really has, and the state of the quote template.