How to Analyse Business Processes Before Digitalisation

What is business process analysis before digitalisation and why does it decide the outcome?

Business process analysis before digitalisation is a practical diagnosis of how a company actually works: who does what, in what order, in which systems, with which approvals, and where waiting, errors or duplication arise. It decides the outcome because without it you often end up digitalising the chaos instead of removing it.

This is not about drawing diagrams for a presentation. The goal is an accurate picture of how information, documents, requests and decisions actually move between sales, operations, accounting, service and management. Only then can you responsibly determine what is worth automating, what needs simplifying first, and where a change to the process beats buying another tool.

Looking at how ready companies are more broadly, the topic is backed by data. In 2023, 58 % of small and medium-sized enterprises in the EU reached at least a basic level of digital intensity, while the EU's target for 2030 is more than 90 %, according to Eurostat. The pressure to digitalise is growing, but the gap between deploying technology and genuinely improving processes remains wide.

A good analysis should answer at least these five questions:

• Where the process begins and where it actually ends
• What inputs it needs, who enters them and at what quality
• Where decisions, approvals and waiting happen
• Which steps repeat, are done manually or carry a higher risk of error
• What impact the process has on revenue, cash flow, the customer or the team's capacity

The output should not be merely understanding, but a decision. After the analysis you need to know which processes to tackle first, which KPIs to track after the change, and whether a CRM, a workflow, an integration, an AI automation or custom software will suit better.

Which processes should a company analyse first?

Analyse first the processes that combine high volume, a significant impact on money or the customer, frequent errors and several handovers between people or departments. You do not have to take the whole company apart at once. The best results come from one process that causes trouble daily and has a clear process owner.

In practice it pays to rank the candidates by a simple score. Give each process 1 to 5 points in these areas:

• Frequency: how many times a month the process runs
• Financial impact: its effect on revenue, margin, collections or costs
• Impact on the customer: whether it slows down a response, delivery, service or communication
• Manual work: how much retyping, e-mailing, spreadsheet work and checking it requires
• Error rate: how often it produces a complaint, a correction or an argument
• Complexity of handover: how many roles, approvals and systems are involved
• Dependence on a person: whether one experienced colleague holds the process together

In most companies these process lines recur among the first candidates:

1. Lead to order – from enquiry to closed order
2. Order to cash – from order to delivery and invoicing
3. Purchase to pay – from a purchase request to settling the liability
4. Request to service – from a customer request to resolving the service or support case
5. Internal approvals – contracts, invoices, leave, budgets, expenses

If you cannot choose, a practical rule is to start where a large volume of repeated steps meets high value. Typically that means processing enquiries, approving documents, keeping customer records, the invoicing flow, or the link between sales and delivery. That is where it becomes clear fastest whether digitalisation will produce a measurable effect.

How do you map a process so you capture reality and not just the written policy?

Do not map the process from internal policies, but from the real work. A reliable analysis therefore combines interviews, observation, document samples, system exports and a check of the exceptions. That is the only way to capture what people actually do, not merely what the documentation says they should.

The most practical procedure has five steps:

1. Define the boundaries of the process. Name the trigger and the end clearly. For example: an enquiry arrived through the form and the process ends with a quote issued; or an incoming invoice arrived by e-mail and the process ends with a payment ready.
2. Capture the roles and the handovers. It is not enough to know that sales or the back office handles the process. You need to see exactly who enters the data, who checks it, who approves it and who fixes the errors.
3. List the systems and the places data lives. CRM, ERP, e-mail, Excel, chat, a form, a shared drive, paper, a mobile. Name everything that touches the process.
4. Map the normal course and the exceptions. The ordinary case is only half the truth. Digitalisation is often derailed by credit notes, missing data, manual interventions, individual pricing, incomplete attachments or special approvals.
5. Add time and volume. For every step, note not only who does what but also how long it takes, how often it happens and what slows the process down.

For the output, a simple swimlane-style map is usually enough, with each row belonging to one role or department. What matters is that the process map makes clear:

• the entry into the process
• the decision points
• the manual and automatic steps
• the approvals
• the systems used
• the waiting between steps
• the places where data is retyped or filled in

It is very useful to work with 10 to 20 real cases from recent weeks. That moves the discussion away from impressions and onto specific orders, invoices, requests, leads or service tickets.

Which metrics need measuring before the first automation?

Before the first automation you need to know the starting point. Without a baseline you cannot tell whether the process got faster or cheaper after the change, or merely moved the problems elsewhere. The minimum is to measure total lead time, hands-on working time, waiting, the error rate, the number of systems involved and the number of approval steps.

The most practical set of metrics looks like this:

Metric	What it measures	Why it matters
Total lead time	time from entry to completion	shows how long a customer or colleague actually waits
Touch time	the net time somebody spends working on a case	separates work from waiting
Waiting time	idle periods between steps	reveals approval and communication delays
Errors and rework	the number of corrections, returns and additions	shows where the process creates unnecessary work
Number of handovers	how many times a case changes owner	the more handovers, the higher the risk of losing context
Number of systems	how many tools have to be opened	a good signal of an integration problem
Cost per case	an estimate of labour and overheads	the basis for priority and ROI
SLAs or deadlines	the share of cases completed on time	important for sales, service and the back office alike

You do not need a complex model for a first ROI calculation. For each process it is enough to work out:

• the average monthly volume of cases
• the average manual time per case
• the number of corrections or extra interventions
• the value of the time of the team running the process

If a process handles 800 cases a month and you save 6 minutes per case, you are no longer talking about an impression but about dozens of hours a month. That is how an analysis turns into a business decisionrather than a technology debate.

Where do bottlenecks and invisible costs most often hide?

Bottlenecks rarely sit in one big problem. More often it is a series of small delays: manual retyping, unclear ownership, approvals without a rule, filling in missing data, and exceptions handled outside the system. It is exactly these details that create the invisible costsa company goes a long time without counting.

These patterns show up in analysis again and again:

• Duplicate data entry. Data appears first in a form or an e-mail, then in Excel, later in the CRM, the ERP or the invoicing tool.
• Approvals without decision rules. People do not know who should approve an exception, a discount, an invoice or a change of brief, so everything gets pushed around by e-mail.
• Exceptions outside the process. The ordinary case is described, but anything non-standard is handled by phone or a private message.
• Incomplete inputs. A missing attachment, job number, deadline, price, contact person or link to the previous step.
• Files in attachments. The current version of a contract, quote or document lives in five mailboxes at once.
• An unclear process owner. Everybody does their part, but nobody manages the outcome from beginning to end.
• Systems that are not integrated. The data exists, it just does not flow between the tools automatically.

Hidden cost is not created at the level of a single click alone. It also arises because:

• sales responds to enquiries more slowly
• invoicing goes out later and cash flow worsens
• the team spends capacity on corrections instead of growth
• management decides from incomplete or delayed data
• the customer has to send the same information repeatedly

That is why, during the analysis, it is not enough to ask only where you could deploy a tool. The more precise question is: where is value being lost in the process today, and if you remove that point, what improves at the same time for the customer, the team and the company?

Which approaches to digitalisation come into play after the analysis?

After the analysis, do not choose technology by trend but by the type of problem. A sales process needs one solution, document approvals another, retyping data another, and a core process that differentiates the company from its competitors another again. A good analysis therefore addresses the right approach, not merely a software purchase.

Broader data also shows that companies already use several layers of digitalisation. In 2025, 53 % of EU enterprises used specialised ERP, CRM or BI software, while in Slovakia the figure was 34 %, according to Eurostat. What matters is not having some tool, but connecting it correctly to how the work actually runs.

The situation after the analysis	The suitable approach	The typical result
The problem is in sales, follow-up, customer care or service cases	CRM	unified records, fewer lost leads, a clear pipeline and communication history
The problem is in documents, forms and approvals	workflow and document digitalisation	fewer e-mails, a traceable status, shorter waiting
The problem is manual retyping between systems	integrations and automation scenarios	less duplicate entry and a lower error rate
The problem is reading, sorting or extracting data from documents and messages	AI automation	faster processing of inputs and less routine work
The problem is a unique company process, its rules, or a combination of several roles and systems	custom software	a precise fit to the process, the data and the permissions

If the core of the problem is a sales or service flow, it usually makes sense to start with a CRM designed around the processrather than another spreadsheet. If the process rests on repeatedly reading documents, e-mails or requests, or on triggering routine steps according to rules, then AI solutions for business processesare a strong candidate.

Timing AI correctly matters too. In 2025, 20 % of EU enterprises with at least 10 employees used artificial intelligence technologies, a share that grew compared with 2024, according to Eurostat. That does not mean AI should be the first step, however. It brings the greatest benefit where you already know the process, the data inputs, the exceptions and the expected result.

What does the output of a good analysis and the development brief look like?

A well-executed analysis does not end with a pretty process map. It has to turn into a decision document and a brief the team can use to design the architecture, estimate the scope and deliver the solution in stages. Otherwise the findings get lost and you return to debates based on gut feel.

The minimum usable output consists of:

• An AS-IS process map: how the process works today, including roles, systems, approvals and exceptions
• A list of pain points with their impact: not only that a problem exists, but what it costs in time, money, errors or customer experience
• TO-BE principles: how the process should work after the change, what gets removed, what gets unified and what gets automated
• Decision rules: who approves what, where the process branches, which conditions trigger the next step
• Data requirements: which fields, relationships, validations and data sources the solution needs
• Integration points: which systems the solution should connect to and in which direction the data should flow
• A prioritised backlog: what is the MVP, what belongs in the second phase and what is merely nice to have
• KPIs after launch: which numbers will be tracked once it goes live

An output like this is genuinely usable for software development that follows the reality of the process. From it a development team can prepare the solution design, the stages, the integration plan and a realistic scope for the first version.

Discipline about priorities matters too. If the analysis uncovers ten problems, that does not mean ten modules in the first phase. The strongest projects usually begin with one process, one group of users and one measurable goal. Only then does the architecture expand further.

What should you do next?

If you want to digitalise sensibly, do not start by choosing a tool. Start with one process, one owner and one measurable goal. The best entry point tends to be a short diagnosis showing the current state, the priorities, the suitable type of solution and a realistic scope for the first implementation.

The practical procedure looks like this:

1. Choose the process with the highest impact. Not the whole company, but one process line.
2. Name the process owner. There has to be a person who can decide and validate reality.
3. Gather real cases. Ideally 10 to 20 recent orders, enquiries, invoices, requests or service tickets.
4. Map the AS-IS state. Roles, systems, waiting, errors, approvals, exceptions.
5. Measure the baseline. Time, error rate, number of interventions, volume, handovers.
6. Design the TO-BE goal and the MVP. What gets removed, what gets unified, what gets automated straight away and what only later.
7. Choose the form of the solution. A CRM, a workflow, integrations, automation over a specific process or custom software.

This is exactly where a partner who builds the technology around the process rather than alongside it earns its place. At BeCode we connect analysis, architecture and implementation so the result is not just a new application but a measurably better-functioning company. If you can already see processes breaking down over e-mails, spreadsheets, manual retyping and unclear approvals, the natural next step is contacting the BeCode team, who can turn the reality of your processes into a concrete plan.

Frequently asked questions

How long does business process analysis before digitalisation take?

One clearly bounded process line can usually be analysed in 2 to 4 weeks, provided the people, the data and real cases are available. If the process runs through several departments or has many exceptions, it takes longer. Accuracy matters more than speed, so that you do not build a solution on a false assumption.

Do we have to analyse the whole company at once?

No — in most cases it is better to start with one high-impact process that has a clear owner. That gives you a measurable result faster, validates the approach and lets you extend digitalisation afterwards. A pilot on one process tends to be more practical than a large analysis without priorities.

How do we recognise that a process is suitable for AI automation?

A good candidate for AI has recurring inputs, a clear expected output and rules or historical data that are legible enough. Typically that means sorting messages, extracting data from documents, drafting replies or triggering routine steps. If the process is still unclear, fix the workflow itself first.

What do we get at the end of the analysis if we do not want to build a new system straight away?

Even without immediate implementation the analysis has high value, because you gain a map of the current state, a list of bottlenecks, priorities, KPIs, a design for the future process and a recommendation on the suitable type of solution. That is the basis for an informed decision, a budget and introducing changes gradually without a hasty software purchase.