Business Intelligence based on Power BI

Start making management decisions that directly impact profits

The only source of truth:

Finance, commerce, and operations finally work with the same numbers. Disputes in meetings and time spent trying to figure out whose data is correct disappear.

Management reporting without delays:

What previously took an analyst 2-3 days of work is now generated automatically. The manager receives up-to-date information exactly when it is needed.

Transparent Marginality:

Financial analytics show profitability by product, customer, and sales channel. Product and pricing decisions are based on real numbers.

Real-time deviation control:

A lag from the plan becomes visible at the moment it occurs and when it can still be influenced. Not at the end of the month, when the situation has already developed.

Current P&L without analyst requests:

Management sees the financial picture at any time. Different departments no longer receive different versions of the same metrics.

Automation instead of manual work:

Data is updated without human intervention. The risk of error due to the wrong formula or the wrong file is structurally removed, and does not depend on the attentiveness of a particular employee.

Signs

5 signs that your business needs a full-fledged Business Intelligence system

Management reporting is present in almost every company that has experienced the first stage of growth. But the presence of reports and the ability to quickly make decisions based on them are completely different things. The greatest danger is that the gap between them becomes noticeable not immediately, but when the cost of a late or wrong decision is already quite tangible.

"Reports are generated manually in Excel"

Фінансисти та аналітики витрачають десятки годин на місяць на зведення таблиць. Замість того щоб інтерпретувати цифри і формулювати рекомендації, вони збирають дані.

"Data from different systems does not match"

The finance department shows one number, the sales department shows another. Data consolidation becomes a point of contention, and every meeting starts with figuring out whose numbers are correct.

"Marginality by product and customer is opaque"

There is a turnover. But understanding which products or customers actually generate profit and which ones absorb it is difficult, and sometimes even impossible, without a separate analytical project.

"Promotional activities have no financial value."

Discounts are given, promotions are held, turnover increases. But the real impact on profit remains unknown until the end of the quarter, and the marketing budget is effectively allocated blindly.

"Management receives reports late"

Data for the past week arrives on Tuesday, by which time the situation has changed, but we have to act on the basis of what is available.

Real cases of our clients

Stonelight – production

Shareholders and top management have control over key indicators in real time, regardless of who prepares the report and when. Two-level reporting: shareholders see the status in a “traffic light” format, top management – detailed analytics with the possibility of in-depth analysis. Everything is available from a mobile phone.

Helen Marlen Group – luxury retail

The numbers between stores and the central office no longer differ. A single methodology for calculating indicators, agreed with top management, and a role-based model in Power BI: each level of management sees only the data relevant to it.

Planeta Kino – a chain of cinemas

The analytics infrastructure covers the full funnel: from the first customer touch to the cash register, including cross-selling and LTV. Four areas of analytics, a centralized data warehouse and ML models for hypothesis testing.

WHERE BI WORKS

What tasks does Business Intelligence solve?

Financial analytics

The central unit for most customers. The one where the cost of an error or delay is the highest.

P&L by product, channel, and division. CFO sees where profit is generated and where it is consumed. No manual summarization of ten tables.
Marginal and profitability analysis. Detailing by SKU, client, region – where decisions about assortment and pricing are actually made. It becomes clear which positions, areas or contracts are dragging the business down.
Plan-to-fact analysis and deviation control. Deviations from the budget are visible immediately, not at the end of the month. There is an opportunity to react while there is still time.
Cash flow forecasting. Liquidity is planned based on current dynamics. Fewer surprises, fewer emergency decisions, more control over money.

Sales

Business analytics shows not the picture that managers want to show, but the one that the data confirms.

Sales analysis by channel, customer, and region. It’s clear where revenue actually comes from and where there are hidden growth points.
Evaluation of the effectiveness of promotions and discounts. Each campaign receives a financial assessment, the team sees which campaigns bring in money and which ones only create the illusion of activity.
Determining the most profitable products. The portfolio is reviewed based on the actual profitability of each position. It becomes clear what needs to be pushed into sales, what needs to be revised in price, and what needs to be removed from the focus of attention.
Monitoring the implementation of sales plans. The lag from the plan becomes visible at a time when it can still be corrected. Not only the fact of the slump is visible, but also the source of the problem: check, volume, structure, region, manager, channel.

Stocks and operations

Warehouse and finance live separately in most companies, and operational analytics shows how much what is on the shelves and what is missing is costing the business.

Inventory control. Slowing down in turnover is captured before it turns into frozen capital.
Out-of-stock and overstock analysis. Lost sales due to lack of goods and surpluses that put pressure on liquidity – everything is visible in one place.
Data-driven procurement planning. Orders are formed based on real sales dynamics.
Synchronize operational and financial metrics. Consolidating data between warehouse, purchasing, and finance eliminates the gap that is usually only apparent at inventory.

Diagnosis of the current situation

First, we always analyze which management decisions are currently being made slowly or inaccurately, what data is in the systems and in what state, where conflicts arise between departments. Duration 1-2 weeks. At the end, the client receives a map of the current state of analytics and a list of priority tasks for the BI system.

Data integration and consolidation

Building an analytical model

Power BI dashboard development

System training and transfer

CFOs and financial directors

CEOs and business owners

Head of Finance and financial managers

Commercial directors

CMOs and marketers

Frequently asked questions about Business Intelligence and Power BI implementation

How long does implementation take?

The first analytics work block typically takes 6-10 weeks from the start of diagnostics to dashboard launch. Full implementation with all blocks (finance, sales, operations) takes an average of 3-5 months depending on the number of data sources, the state of current systems, and client priorities. The phased approach allows you to see initial results before the entire project is completed.

Do existing ERP and CRM systems need to be changed?

The BI system is built on top of the existing infrastructure: it connects to ERP, CRM, and accounting systems and retrieves data from them through integration. There is no need to replace or abandon current systems. On the contrary, they become the sources for a unified analytical environment.

Who from our team needs to be involved?

At minimum, one relevant representative from the client side: a financial director or head of the respective department to validate business logic. Participation is required at specific points: during requirements alignment sessions and results verification. IT resources are only needed to provide system access.

Can we start with one area, for example, only finance?

A modular approach is standard practice. We begin with the module where there is the greatest management pain point or the highest value from quick results. Financial analytics, sales analysis, or the operational module—any of them can be launched first, and then the system can be scaled up.

What happens after launch? Do you provide support?

After system handover, we can provide support: technical, analytical, and consulting. When business logic changes or new tasks arise, the system is updated within the SLA framework.

Is the solution suitable for our industry and specifics?

The analytical model is developed according to the specific client's business logic. The approach works regardless of industry: retail, distribution, manufacturing, agriculture, services. There are no ready-made templates for everyone; everything is built around the company's real management tasks.

Start with diagnostics: find out where your business is losing decision speed and profit

At a free meeting, we analyze the current state of analytics: what data is available, where it comes from, where contradictions arise, what management tasks remain unanswered. At the end, you will receive a structure of the future BI system with implementation priorities and specific recommendations, regardless of whether there will be further cooperation.