Email, Excel and Phone Calls: What Does It Really Cost to Sell B2B This Way?

Many B2B companies have digitized their product catalogs, marketing activities and part of the customer relationship. But when it comes to turning a commercial request into an actual order, the process often becomes surprisingly manual again.

One customer sends an Excel file.

Another forwards a PDF.

Someone writes directly to the sales representative.

Others prefer to call.

An order received by email is opened, read, interpreted, checked and eventually entered manually into the ERP.

Everything works.

And that is exactly the problem.

Processes like these can continue working for years without appearing truly inefficient. Their cost does not show up as a single line item in the P&L. Instead, it is distributed across employee time, errors, checks, corrections, delays and commercial opportunities that are never captured.

That is why, when discussing B2B sales digitalization, the most useful question is not simply:

“How many orders do we receive online?”

A better question is:

“How much human work is still required to turn a customer request into an order correctly recorded in our systems?”

That is where a significant part of the real cost of traditional B2B commerce can be found.

The problem is not email or Excel

Email and Excel are remarkably effective tools.

They are universal, flexible and familiar.

The problem begins when they become the infrastructure through which a company manages processes that should be structured.

A buyer may find it very convenient to prepare an order in Excel because that is already part of their daily workflow.

For the supplier, however, that file may mean that someone has to open it, identify the customer, validate product codes, check quantities, apply commercial conditions, verify availability and manually enter all the information into the ERP.

The same information is created once by the customer and then reconstructed by the supplier.

The process is digital only on the surface.

The file is digital.

The workflow is not.

This distinction is important because it explains why B2B order automation can have a much greater impact than simply eliminating data entry.

How much does manual B2B order entry really cost?

There is no universal cost for manually entering an order.

It depends on catalog complexity, number of lines, commercial rules, industry and level of system integration.

But the basic calculation is surprisingly simple.

Imagine a company receiving 1,000 orders per month.

If each order requires only 10 minutes of manual work, that already represents:

10,000 minutes per month, or approximately 167 hours of work.

More than one full person-month every month.

And this only includes order entry.

It does not yet include the time required to:

• clarify incorrect product codes;
• check unavailable items;
• correct quantities;
• validate commercial conditions;
• request confirmations;
• modify orders already entered;
• manage duplicate entries;
• answer questions about order status.

The real cost of the process therefore rises quickly.

The point is not to establish one universal benchmark. It is to make visible a cost that usually remains hidden.

Any company can estimate it using four variables:

number of orders × average handling time × hourly cost × frequency.

Many organizations only realize at that point how much human capacity is being consumed by activities that do not directly generate new business.

Data entry is only the most visible cost

Focusing only on administrative cost would still be too narrow.

Manual processes generate at least five different categories of cost.

1. Operational time

This is the easiest cost to identify.

Every order has to be read, interpreted, checked and entered.

As the number of customers and order volumes increase, the number of people required to manage them tends to increase as well.

This creates a scalability problem.

A company that doubles its commercial volume may also need to increase its operational structure proportionally.

Technology should enable the opposite.

It should allow transaction volume to grow faster than the cost required to manage it.

2. Errors

Whenever information is transferred manually from one system to another, the possibility of error increases.

A mistyped product code.

An incorrect quantity.

An outdated price.

A wrong shipping address.

A commercial note that is not recorded.

Even when the mistake is detected before shipment, someone still has to spend time correcting it.

When it reaches the customer, the cost can spread across warehouse operations, logistics, administration, customer service and sales.

A data-entry mistake that takes seconds to make can create hours of downstream work.

3. Order processing lead time

Another cost is less visible but often even more important.

An order received at 10 a.m. may remain in a sales representative's inbox until the afternoon.

It may then be forwarded to administration.

Then entered.

Then checked.

The difference between the moment the customer decides to buy and the moment the order actually reaches the system can become significant.

That delay has practical consequences.

Available stock may change.

A shipment may move to the next day.

Customer service may still be unable to see the order.

Warehouse planning receives the information later.

Automation therefore does more than reduce staff time.

It reduces the information lead time of the entire organization.

4. Unstructured information

A huge part of the B2B commercial relationship still lives inside inboxes, phone calls, personal files and messages.

The information may be useful, but it is difficult to use at scale.

If a customer sends a request through a digital platform, the data can immediately be associated with their profile.

If the same request is sent by email to an individual salesperson, that information may remain trapped in their inbox.

The company progressively loses the ability to build a complete picture of customer behavior.

How often do they order?

Which products do they request?

At what frequency?

Which products do they substitute?

Which orders do they change?

How long is the gap between one purchase and the next?

These signals become essential for analytics, forecasting and artificial intelligence.

Manual processes therefore do not cost only in terms of productivity.

They also reduce the quality of the company's data asset.

5. Lost commercial opportunities

This is probably the least visible cost.

A salesperson who spends time entering orders has less time to sell.

A team member who constantly looks up prices, checks availability and answers repetitive operational questions has less time to understand what the customer may buy next.

This is where the cost of inefficiency changes nature.

It is no longer only about how much the company spends.

It is about how much potential revenue is not generated because people are busy performing administrative work.

The phone is efficient for the customer, but much less so for the system

Phone calls still play an important role in B2B relationships.

And they will continue to do so.

They are immediate.

They help resolve complex issues quickly.

They preserve the human relationship.

The problem begins when the phone becomes a data-entry channel.

A customer calls and says:

“I need another ten packs of the product I ordered last time, plus twenty of the new one.”

The salesperson understands perfectly.

The software does not.

The information must once again be converted into structured data.

Every unstructured channel therefore creates another human step before the process can continue.

The goal of digitalization should not be to eliminate the phone.

It should be to eliminate the need to manually translate every conversation into data that enterprise systems can use.

Forcing every customer to use a portal does not always solve the problem

The traditional answer to these inefficiencies has been:

“From now on, all orders must be entered through the portal.”

From the supplier's point of view, this makes perfect sense.

From the customer's perspective, not necessarily.

A professional buyer may work with dozens or even hundreds of suppliers.

If every supplier asks them to use a different platform, the digital advantage quickly disappears.

That is one reason why many buyers continue to rely on Excel and email.

Not because they resist digitalization.

Because these tools may still be the most efficient option from their point of view.

True innovation therefore has to solve both sides of the equation.

Allow customers to use the channel that feels most natural to them while preventing the supplier from having to process that channel manually.

This is exactly where artificial intelligence is changing the model.

AI Text-to-Order: automate without forcing customers to change behavior

Consider the same order received by email.

In the traditional process:

email → salesperson → verification → data entry → ERP.

In an AI-supported process:

email → AI → order recognition → validation → ERP.

The customer can continue sending a message.

The system can automatically identify:

• customer;
• product codes;
• product descriptions;
• quantities;
•  units of measure;
• addresses;
• notes;
• potential anomalies.

It can then compare the request with the catalog, inventory and commercial conditions.

If everything is consistent, the order can continue automatically.

If a problem is detected, it can be escalated to a human operator.

This combination is particularly powerful because it allows companies to automate processes that, until recently, seemed impossible to automate without radically changing customer habits.

Not everything needs to be fully automated

Automation does not necessarily mean removing human involvement altogether.

In many B2B processes, the best approach is a human-in-the-loop model.

The system automates what is certain.

It asks for confirmation when confidence is insufficient.

It escalates exceptions.

A standard order from a regular customer may be processed almost entirely automatically.

An unusual request involving unidentified products or non-standard commercial conditions can instead be routed to a person.

The difference is fundamental.

In the traditional model, a person manages every order.

In the automated model, a person manages the exceptions.

That is how an organization becomes truly scalable.

Excel can become an interface instead of a problem

The same principle applies to Excel.

Instead of trying to eliminate it, a modern B2B commerce platform can treat it as one of several possible order-entry channels.

The buyer can use a template.

Or upload a structured file.

The system interprets rows, product codes and quantities and automatically checks them against the catalog.

Excel moves from being a problem to being an interface.

The same logic can progressively be applied to other formats as well.

The central idea is simple:

The customer should not always have to adapt to the software. The software should increasingly be able to understand the customer.

From digital order to connected order

Order automation also creates a benefit that goes beyond the individual transaction.

Once the process becomes digital, the order can automatically connect to other systems.

The CRM knows the customer has purchased.

The ERP receives the order immediately.

The warehouse sees the new demand.

Logistics can begin planning.

Commercial dashboards update automatically.

Marketing systems can adapt subsequent communications.

Forecasting algorithms receive a new signal.

The value therefore does not come only from reducing data entry.

It comes from the fact that information entered once can be used across the entire organization.

This is the transition from a simple digital order to a connected order.

When orders become data, sales change too

There is another, even more interesting consequence.

Once all orders become structured and connected to the customer profile, companies can start building intelligence on top of them.

A system can identify that a customer usually orders every thirty days and has not done so this month.

It can detect that two product categories are frequently purchased together.

It can identify a progressive decline in volume.

It can suggest replenishment.

It can highlight potentially complementary products.

The digitalization of the ordering process therefore becomes the foundation for:

recommendation, forecasting, churn prediction and sales automation.

Data that was previously hidden inside an email becomes a commercial signal.

B2B order automation: where should companies start?

There is no need to transform everything at once.

An effective journey can begin with a simple assessment.

How many orders do we receive each month?

Which channels do they come from?

How many are entered manually?

How much time does an average order require?

What are the most common errors?

Which customers still use email or Excel?

Which orders are standard and which ones genuinely require human expertise?

These questions quickly identify high-volume, low-complexity activities.

They are usually the best candidates for automation.

The second step is to integrate the order-entry layer with the ERP, product catalog and customer master data.

The third is to use automation and AI to progressively reduce the amount of manual work required.

The goal should not be:

“Automate 100% of orders.”

It should be:

“Make sure people intervene only when their intervention actually creates value.”

The real KPI is not how many orders arrive online

For years, one of the most common metrics in B2B digital projects has been the percentage of orders received through eCommerce.

It is a useful metric.

But it can also be misleading.

An order may arrive online and still require manual work afterwards.

Conversely, an order may arrive by email and be automatically interpreted and processed.

A more interesting KPI is therefore:

Straight-Through Order Processing Rate

In other words, the percentage of orders that can move through the entire process without human intervention.

This can be combined with:

• average processing time;
• operating cost per order;
• error rate;
• exception rate;
• order-to-ERP time;
• percentage of automated orders;
• volume managed per employee.

These metrics provide a much clearer picture of how digital the process actually is.

The biggest cost is continuing to scale in the same way

Email, Excel and phone calls are not necessarily the problem.

The real problem is building business growth on the assumption that more volume requires more people to handle it.

If every new customer generates more emails, more data entry, more phone calls and more checks, the business scales linearly.

More revenue means more administrative work.

A digital platform should change this relationship.

Transaction volume should be able to grow without requiring a proportional increase in operational headcount.

That is the real promise of B2B order automation.

Not simply doing the same things faster.

But creating a model in which the company can grow without multiplying complexity.

From manual commerce to programmable commerce

The transformation taking place in B2B goes even further.

Once catalogs, customers, prices, inventory and orders become structured, connected and queryable, they are no longer usable only by people.

They can also be used by intelligent systems.

An AI agent can identify a replenishment need.

Another can check availability.

A system can automatically prepare a purchase request.

A procurement agent can directly query a supplier's catalog.

B2B commerce starts to become programmable.

This is an important shift because automation moves from the individual task to the entire commercial process.

Email, Excel and phone calls will probably continue to exist.

But they do not necessarily need to continue generating manual work.

That is the real evolution.

The future is not about eliminating the channels customers prefer. It is about building infrastructure intelligent enough to understand, integrate and automatically turn them into business.

Frequently Asked Questions about B2B Order Automation

What is B2B order automation?

B2B order automation is the use of software, integrations and artificial intelligence to reduce the manual work required to receive, validate, enter and process business customer orders. It may involve eCommerce portals, ERP systems, email, Excel, APIs and AI text-to-order technologies.

Why are orders received by email inefficient?

Email is not necessarily inefficient for the customer, but the information it contains is often unstructured. This means the supplier has to read, interpret and manually re-enter the data into enterprise systems. Automation can convert email content directly into structured, usable order data.

Can orders received through Excel be automated?

Yes. A B2B platform can allow customers to upload Excel files and automatically convert rows, product codes and quantities into digital orders while validating catalog data, commercial conditions and inventory availability.

What is AI Text-to-Order?

AI Text-to-Order uses artificial intelligence to interpret order requests expressed in natural language or contained in documents and convert them into structured data. For example, it can be used to automatically process purchase orders received by email.

Which KPIs should be used to measure B2B order automation?

Useful metrics include the percentage of orders processed without human intervention, average processing time, cost per order, error rate, exception rate, time from order receipt to ERP registration and number of orders handled per employee.

Does order automation replace sales teams?

The goal is not to replace sales teams but to reduce repetitive administrative work. This allows sales and customer service teams to spend more time on customer relationships, exception management and the development of new commercial opportunities.