7
min read
Most companies begin automation by buying new software. That is exactly why so many automation projects fail to pay off.
If your team copies data between a CRM, Excel, and chat apps every week, the problem is no longer the people. The problem is the process. Managers waste time searching for updates, executives ask every morning where each order stands, and the business depends on the fact that “only Olha knows how this report is built.”
Automation can change that. But only when the business starts not with “Which system should we buy?” but with a different question: where are we losing the most time, money, and control every day?
At Yarandin, we see the same pattern again and again: businesses usually ask us to automate the process people complain about most loudly, not the one that creates the greatest losses.
McKinsey also describes digital transformation not as a one-off technology implementation, but as a systematic redesign of the business to create value.
Business Automation in Simple Terms
Business automation means using a system to handle repetitive actions, move information between tools, and trigger the next step without constant reminders or manual copying.
It can be as simple as automatically creating a task after a new request, or as complex as an internal platform that connects sales, operations, documents, payments, and analytics.
✅ A good outcome: less manual work, faster decisions, clear statuses, and less dependence on individual employees.
❌ A bad outcome: the company buys a new CRM, but the team still manages half the process in spreadsheets and chats.
Atlassian defines workflow automation as completing tasks and sequences of actions with minimal human involvement. One condition is essential: the business must clearly understand what should happen after each event.
Why Automation Often Fails to Deliver the Expected Results
Automating the Loudest Problem
A manual report may annoy a manager, but slow lead processing or order errors may cost the business far more.
Buying a System Before Analyzing the Process
A company chooses a popular product and begins adapting its operations to fit the software. The result is workarounds, duplicated data, and even more manual work.
Automating Chaos
If four managers approve contracts in four different ways, the system cannot know which process is the correct one.
Failing to Calculate the Real Losses
Saying “this takes too much time” tells you nothing about return on investment. You need to know how many people are involved, how often errors occur, and how much each delay costs.
Ignoring Integrations
Sometimes a business does not need another platform. It simply needs its CRM, accounting system, email, payment tools, and spreadsheets to exchange data automatically.
A real-world example. One of our clients wanted to automate contract approvals. During the analysis, we discovered that different managers followed four separate approval scenarios, while the final decision depended on informal agreements. We first standardized the process together and defined clear roles. Only then did automation genuinely reduce reminders and delays.
A Short Checklist: Is the Process Ready for Automation?
Instead of twelve separate questions, six checks are enough. If the answer to most of them is yes, the process is already a strong candidate for automation.
✅ The process happens frequently — A five-minute task performed hundreds of times a week is usually more important than a five-hour operation performed once a year.
✅ It consumes a noticeable amount of team time — Five managers spending 30 minutes a day equals more than 50 hours every month.
✅ The rules are clear — It is obvious what starts the process, who owns the next step, and under which conditions approval is required.
✅ Errors or delays cost money — The process affects response time, payments, order fulfilment, customer retention, or reputation.
✅ The data is accessible and reliable enough — There is no critical volume of duplicates, inconsistent formats, or conflicting sources.
✅ There is a process owner and a success metric — Someone is responsible for rules, exceptions, and changes, and the business knows what should improve after launch.
Stop signal: if the team cannot describe the process step by step in the same way, it is too early to start development. First remove unnecessary steps, align the rules, and assign responsibility.
What to Automate Now — and What to Postpone
Process | ✅ Ready to automate | ❌ Better to postpone | |
Repetitive manual tasks | Performed frequently and according to consistent rules | Occur rarely or follow different logic each time | |
Reports | Data is structured and there is a single source of truth | Figures conflict or are collected inconsistently | |
Lead processing | Clear rules exist for routing and prioritization | The sales process has not yet been defined | |
Approvals | Roles, limits, and approval paths are clear | Decisions are made differently every time | |
Complex, unstable processes | One stable stage is automated first | A large, rigid system is planned immediately | |
Processes with poor data | After the data is cleaned and standardized | Before data preparation and ownership are established |
Which Solution Do You Need: Off-the-Shelf Software, Integration, Custom Software, or AI?
Off-the-Shelf Software
Best when the process is standard and does not require unique business logic. This is usually the fastest and least expensive way to start.
Examples: task management, a basic CRM, email marketing, help desk software, and standard accounting tools.
Integration of Existing Systems
Best when individual tools work well, but employees still move data between them manually.
Examples: automatically sending orders from the CRM to the accounting system, synchronizing payments, or creating reports from several data sources.
Custom Software
Makes sense when the process is specific to the business, involves complex roles, connects several systems, or creates a competitive advantage.
Examples: an internal operations dashboard, a customer portal, or a specialized order management system.
AI Automation
Works well with text, documents, classification, search, and draft preparation. However, outputs must be reviewed, and the system must know when to escalate a decision to a person.
Examples: processing customer requests, extracting data from documents, searching a knowledge base, and preparing draft responses.
How to Quickly Estimate Whether Automation Will Pay Off
You do not need a complex financial model for an initial estimate. Four numbers are enough:
· how many hours the team spends on the process each month;
· what that time costs;
· how many errors and delays occur;
· what share of the work can realistically be handled by a system.
For example, if a team spends 20 hours a week moving data between a CRM and spreadsheets, that is not “minor administrative work.” It is more than 80 hours every month that could be returned to sales, customer service, or operational control.
But the value is not limited to time savings. After the right automation is introduced, managers no longer need to collect statuses manually, customers receive faster responses, and the business stops depending on one person who keeps the entire process in their head.
The Yarandin Model: Four Questions Before You Start
At Yarandin, we begin automation not with a technology demo, but with four questions:
1. What Costs the Most?
Where is the business losing the most time, money, customers, or control?
2. What Repeats?
Which actions does the team perform regularly and according to similar logic?
3. What Must Scale?
Which process will become a bottleneck if the number of customers or orders doubles?
4. What Can Be Tested Quickly?
Which hypothesis can be tested with a small solution before making a major investment?
This model protects a business from two extremes: buying a large product the team will not use, or tolerating a manual process for years because a full transformation feels too difficult.
A Minimum Launch Plan
1. Understand the Process
Talk to the people who perform the work every day and identify unnecessary steps, duplication, and points where information gets lost.
2. Choose One Priority
Do not start with “automate everything.” Start with the process where the effect can be seen and measured.
3. Test the Solution on a Small Scale
Create a prototype or automate one stage to uncover exceptions and see how the team responds.
4. Scale After Validation
Only after the value is confirmed should you build the full solution and add integrations, analytics, security, and support.
Conclusion
Good automation does not start with a CRM, AI, or ERP system. It starts with an honest answer to one question: where is the business losing the most resources?
Sometimes the answer is an off-the-shelf tool. Sometimes it is an integration between existing systems. In other cases, the business needs custom software or an AI module. Technology is not the goal here; it is a way to remove a specific business constraint.
Choosing the right first process does more than save hours. It removes daily reminders, makes statuses transparent, reduces errors, and allows the company to grow without expanding the team at the same rate.
If your team has already accumulated too many spreadsheets, manual data transfers, and processes that depend on individual employees, Yarandin can help audit your operations, identify the best starting point, and build a solution around the real logic of your business — without automating for the sake of automation.
