7 Key Steps of Business Intelligence (BI) Implementation Process

Why Does Your Company Need Business Intelligence Implementation?

When it comes to the concept of business intelligence, we should picture not just the mere technology but a set of tools, software, and practices used for the collection and presentation of the company's data.

Business intelligence helps companies move from 'guessing' to 'understanding' the real cause of a particular problem. Here's a simple example:

The importance of business intelligence becomes evident if we look at the fact that today's global datasphere is growing exponentially and will reach 175 ZB by 2025 (175 x 10²¹ bytes) — compared to 45 ZB generated in 2019. According to statistics, 2 QB (2 x 10¹⁸) of data are generated across all industries every day.

Data needs to be organized somehow, and it's no secret that legacy systems and outdated infrastructures are no longer able to aggregate such large chunks of incoming information. On the contrary, BI systems can help structure end-to-end workflow — from data collection to preparation to interpretation and storage.

To put this all into perspective, the implementation of business intelligence can be beneficial for:

All these aspects that come with business intelligence systems are extremely important for the fast-paced environments businesses are faced with today. That brings us to the next question of how to implement business intelligence.

1. Analyze the current state of the company's data

Before implementing a BI strategy or integrating corresponding tools, it's necessary to understand in which state your data is, currently. This process includes examining all the existing sources of data, and evaluating how data is stored, managed and shared.

Keep in mind that not all sources can be valuable for BI — some may provide incomplete data, some duplicate information, overlap stats, etc. So, select those that are clear and carry the most value in terms of information relevance and retrieval.

2. Gather a team of subject matter experts

Obviously, the BI integration process would be impossible to carry out without a dedicated team. Your team has to consist of data-driven experts that have expertise in different domains — finance, IT, marketing, HR, etc. These can come from your various intercompany departments.

A mix of members with different backgrounds ensures that the BI team will be able to introduce changes to all the necessary areas of your company and not overfocus on a single component.

When it comes to the team members' roles, in particular, your group of BI evangelists may consist of: Data Quality Analyst, Data Mining Expert, Lead Developer, Infrastructure Architect, Data Administrator, Project Manager, and Business Representative.

3. Create a strategy and a business intelligence implementation plan

Once you have assembled a BI team, it's time to develop your strategy. Here, your main task will be to understand how data will be processed within your company. To correctly define the scope of business intelligence implementation, you need to answer three basic questions:

Getting answers to those questions beforehand will help to lay out a clear road map for successful BI implementation.

4. Identify important KPIs

At this stage, you need to understand what you want to measure. Identifying key performance indicators will help you ensure your BI strategy stays on the right track throughout the whole business intelligence implementation process.

The choice of metrics solely depends on your goals, but we advise you to break them into sections based on the objectives (or departments) they relate to. For example:

If you are just starting to work with business intelligence, we recommend concentrating on the most important KPIs first in order not to overcomplicate the data gathering and analysis processes.

5. Educate Staff & Stakeholders

For many people, it is quite difficult to break established habits, and business intelligence adoption is no exception here. If your employees have never had experience working with the BI before, chances are they will resist adopting new tools.

To make sure that your staff understands the necessity of change, hold training sessions and make them a part of the implementation strategy. Help employees see the bigger picture and value behind the new software; explain how new tools will improve their work and what the reasons are for introducing such changes. Data analytics has to become a part of a company's culture.

Oftentimes, all business owners have to do to minimize the effect of this phenomenon is simply communicate with their employees to get their input (before actually implementing BI tools). When people — whose work will be affected by the changes — know their considerations are taken into account, and that their concerns are addressed in advance, it is much easier for them to start using new technologies.

6. Choose a software and setup BI infrastructure

The integration of actual BI tools will be a major part of the whole process. At this stage, you will need to choose your BI software. Luckily, there are a lot of ready-made solutions on the market from SAP, IBM, Oracle, and Tableau. Your developers, in turn, will need to configure data storage and data environment components.

For data storage, you can go with either of two repositories: a data lake or data warehouse. A data lake assumes storing raw blocks of data, the purpose of which is yet to be defined. A data warehouse, on the other hand, is a repository that stores structured and filtered data. The latter is considered a better choice for BI architecture.

For the data environment, you can choose between three options: On-premise — where the BI system is located on your internal physical servers; Cloud — where the BI system is stored in a public/private cloud; and Hybrid — where some components are stored internally, and some are deployed in the cloud.

If you don't have enough expertise in the Big Data domain, you can always onboard a ready-made development team who has the relevant know-how and is experienced enough in developing custom business intelligence systems tailored to your needs.

7. Roll out pilot project and adjust system based on the results

After all the components of a system are tuned to work together, it’s time to test them. Start with the smaller chunks of data and expand later on as you adjust system requirements. The testing process of a BI system normally covers all main reporting functions and consists of several phases:

Once all of these tests are done, you should run your customizable system to get results across your KPIs. This is an ongoing process so, after introducing changes to the areas of your audit, run the system again to see the changes in key performance indicators. After that, you can scale — adding more data and more detailed KPIs.

Implementing BI with WTT Solutions

All great strategies and innovations come from data-driven decisions, and BI is a way to ensure companies have solid ground to base their actions on. Business intelligence solutions give organizations access to real-time analytics and spare them the need to turn to third-party companies to do that for them.

The popularity of business intelligence is spreading at high speed, and will continue to do so as more and more data becomes generated worldwide.

If you are interested in developing a custom business intelligence application, or want to get a deeper sense of what's going on and what should be done with your company data, contact us through the feedback form in the upper right corner of this page. Make sure you subscribe to our newsletter so you don’t miss any new blogs and industry insights!