10 September 2026
updated at: 27 September 2026
13 November 2026
Any business that has been through a period of rapid growth eventually runs into growing pains. Suddenly, approving a standard contract takes three weeks, hiring a new employee turns into a quest across five departments, and buying a new server gets stuck in an endless email thread. The company accumulates policies nobody reads and a dozen different IT systems that can't talk to each other. People work hard, but results — for internal or external customers — arrive painfully slowly.
At this point, leadership usually makes an impulsive call: we urgently need new software. Expensive tools get purchased, integrators start writing code, and the result is a heavyweight system that's even harder to work in than before.
The problem is that the business skipped a fundamental step — business process optimization. In this article, we'll walk through how to find broken workflows, fix them, and turn them into digital processes that make money instead of headaches.
Business process optimization is a systematic approach to analyzing, redesigning, and improving a company's existing workflows. Unlike one-off crisis fixes, it's a continuous cycle of finding efficiency gains. You take the "As-Is" process, identify where it's losing value, and design a "To-Be" model.
Optimized processes pay off in ways that are easy to measure and easy to defend to leadership:
In theory, any of them. In practice, architects group enterprise processes into three broad categories, each requiring a different approach:
Don't fix what isn't broken. Before launching an expensive transformation project, look for processes showing clear warning signs:
People have long since built frameworks for bringing order to chaos. Which one you choose depends on how deep the problem runs: does the process need a tune-up, or does it need to be scrapped and rebuilt?
Optimization is always a change-management project, and people generally don't like change. To minimize resistance and risk, follow a disciplined framework:
Step 1. Take inventory and pick a starting point. Don't try to optimize the whole company at once. Map your top-level processes, then choose one to start with — the most painful for the business, but still understandable and measurable. Onboarding a new employee is a great candidate.
Step 2. Map the As-Is process. Document how the process actually works today, without sugarcoating it. Who calls whom, what forms get filled out, where do things sit waiting for a response? For complex processes, Process Mining is invaluable here, since it surfaces the real approval loops — not the ones people assume exist.
Step 3. Find the problems and design the To-Be model. Analyze the As-Is model. Where is time being lost? Why does a contract need five approvers if only two of them are actually accountable for it? Cut unnecessary steps. Replace sequential approvals with parallel ones. Design the ideal target workflow.
Step 4. Choose an automation tool. A process that only exists on paper won't run itself. Select an IT solution — a BPM system or a low-code platform — capable of executing your new model and keeping people on the right track.
Step 5. Test it (pilot). Roll out the updated process in your IT system with a small focus group. Collect feedback — this stage is where roughly 80% of overlooked edge cases will surface.
Step 6. Scale and monitor. Move all participants onto the new process. Set up dashboards to track the new metrics and confirm the process doesn't slide back into chaos.
Drawing a perfect BPMN diagram on a whiteboard is only about 10% of the job. The real challenge is making that diagram run inside the company's actual IT landscape. Here's how the toolkit has evolved.
| Toolkit | Core Approach | Business Outcome |
|---|---|---|
| Level 1: Spreadsheets and email | Data gets passed around manually. Process logic — what happens next — lives only in people's heads. | Chaos and micromanagement. High risk of data loss. No way to track SLAs. |
| Level 2: Document management systems and task trackers | Digital task cards and statuses appear. | Basic tracking exists, but end-to-end logic breaks down between departments (a task gets manually re-entered from one system into Jira, for example). |
| Level 3: Classic BPM systems | Powerful engines (BPMS) enforce strict orchestration using BPMN notation. The system tightly controls the process. | Strong control, but implementation is slow and expensive. Any route change requires work from qualified developers. |
| Level 4: Low-code platforms and ESM | Business logic, forms, and interfaces are configured visually by business analysts — no code — on a shared enterprise data model. | The best of both worlds: fast implementation combined with enterprise scale and a single shared data layer across departments. |
By 2026, classic monolithic systems are giving way to low-code platforms built around Enterprise Service Management (ESM). Why does this matter so much for optimization?
Traditional development can't keep pace with the business. By the time developers finish coding your updated process, the requirements have often already changed. Platforms like SimpleOne solve this problem differently:
A business analyst can visually assemble a request form using drag-and-drop editors, configure a complex multi-level approval route, and set strict SLA rules — no code required.
The core advantage of the ESM approach: every service department — IT, HR, facilities, legal — works on a single shared data model. The process no longer breaks down at the handoff between departments or requires a dozen complex integrations. A single platform automatically routes tasks: an account-deactivation task to IT, a clearance form to facilities, and a final calculation to finance.
Optimizing for its own sake is a waste of budget. Results need to be quantified in terms leadership understands. Track the following metrics:
Here are a couple of typical processes where optimization delivers a fast return on investment.
Case study: Optimizing IT Support at Federal State Institution
The organization was dealing with a massive volume of requests and long first-line incident processing times.
Case study: Back-Office Transformation at Logistics Company
Even solid methodologies can lead to a failed project. Here's what to avoid:
Business process automation and the optimization that has to happen first aren't a one-off project — they're a continuous management cycle. Moving from chaotic email threads to managed digital services is essential for protecting margins in a tight labor market.
The key insight for 2026: how successful your optimization is depends directly on the IT foundation you choose. Move away from rigid, siloed systems toward flexible low-code and ESM platforms. Build a unified data ecosystem, automate routine work in software, and let people focus on what they do best — creative thinking, expert analysis, and strategic growth.
It covers mapping the current ("As-Is") process, identifying bottlenecks and waste, designing an improved ("To-Be") version, and selecting the right IT tool to run it. It also includes piloting the new process, training the people involved, and setting up metrics to monitor it after launch.
Watch for warning signs like chronic SLA breaches, requests bouncing between departments without resolution, a single person or team becoming a bottleneck, employees quietly working around official systems (shadow IT), and a high volume of manual, repetitive data entry.
Start with support processes — IT, HR, and administrative workflows — since they're usually the most standardized, generate the fastest ROI, and don't require touching revenue-critical systems. High-volume, repetitive processes like onboarding, approvals, and service requests are typically the best starting point.
Optimization comes first: it's about fixing the logic of a process — removing unnecessary steps, redundant approvals, and bottlenecks. Automation comes second and simply moves that (already improved) process into software. Automating a broken process just gets you a faster version of the same problem.
A classic BPM system enforces process execution through rigid orchestration, and any changes typically require developer involvement. A low-code platform lets business analysts configure forms, routes, and rules visually, with far less reliance on IT, while still running on a shared enterprise data model.
It depends on the process's complexity and the tool used. On a modern low-code/ESM platform, a well-scoped process — like the travel-request example above — can often go from design to a working pilot in a few weeks, compared to months on a classic BPM system.
Yes — this is the standard approach. Processes are typically redesigned and piloted with a small focus group first, running alongside the existing workflow, and then rolled out company-wide once the new version is validated. This avoids disrupting day-to-day operations during the transition.
Compare key metrics before and after: lead time, cost per transaction (including labor costs across the approval chain), the share of tasks completed automatically (STP rate), and SLA compliance. The difference in these numbers, multiplied by transaction volume, gives a concrete financial estimate of the optimization's impact.
