How to Develop a Successful Business Intelligence (BI) Strategy
Business intelligence strategy implementation is an important step to consider. Let’s look at how BI development strengthens and optimizes your company.
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Every organization has goals and plans for how to reach them. To determine which actions to take and what approach to choose, they gather the needed data. Because we can't deny that the insights it provides are powerful tools for organizations on the road to success.
So, lots of companies started to implement BI strategy as they consider it an opportunity to increase profitability, optimize internal processes, discover new revenues, identify market trends, and detect business problems through effective decision making and data analysis.
Starting such an approach requires preparation. Let’s discover how to develop a business intelligence strategy.
What Is BI Strategy?
Before jumping straight to the strategy, let’s define the term. It appeared in the 1950s as a technology called decision support systems. Over the next decades, these systems turned into a comprehensive tool mainly due to the increase in the amount of data that companies can collect on their internal processes and their customers (the rise of the internet and computer usage accelerated this process).
Additionally, it became cheaper to store data in larger quantities. Companies received access to endless sets of data (internet usage records, social media activity, etc). BI aims to find patterns and trends among all this data.
Business Intelligence revenue in software is projected to reach US$23,258.94m this year.
Here are a few explanations that we consider relevant. To put it simply, BI is about delivering relevant information to the right people at the right moment to achieve better decisions in a faster way. To perform this, BI has methods to collect unstructured data and convert it into information to improve business decisions.
BI may include:
- Performance management
- Predictive modeling
- Data mining, etc.
BI exploits the data your business generates in all of its activities. Then it analyzes and visualizes this data to understand it and get valuable insights to make your business evolve by making better decisions. Basically, by collecting, structuring, and analyzing, BI converts raw data into meaningful information.
The reason companies invest in BI is data analysis. No matter how companies process their data, the insights from analytics reports affect all company’s processes. These two terms are often mixed up. BI uses past and present data to inform current decisions, while business analytics uses past data to explain current data and predict what will happen in the future. BI uses different analytics methods, including:
- Data mining (or discovery) includes automated analysis of large sets of data to find patterns.
- Text analytics combs through textual (unstructured) data (e-book or research paper) to find patterns. This can be used for linguistic analysis or sentiment analysis on social media or online customer feedback, etc.
- Business analytics draws connections between data and companies that use it to predict future trends, and reveal unknown inefficiencies in their systems.
Why Businesses Should Implement BI
Consider business intelligence if your company suffers from:
- Underperforming employees
- Loss of customers
- Wasted resources and time
- You produce tons of data but don’t know how to use it
The data-driven decisions can help your company by:
- Tracking performance
- Optimizing operations
- Foreseeing trends
- Planning approach to increase profit
- Analyzing customer behavior
- Analyzing competitors data
- Discovering problems and their solutions
Other benefits are broken down in the following sections.
Profitable Business Decisions
As we’ve already mentioned, BI helps to gain insights from your data to make smarter business decisions. For instance, graphics and charts in dashboards don’t give a visual representation of your business performance. Visualization makes it easier to read and understand data, to observe trends, and to see things that are going well and the parts that need improvement.
Business intelligence uses financial, operations data to generate accurate reports, visual representations (charts or graphs), or written information. In this way, every stakeholder (especially business owners) is every of every little change within the company.
BI analyzing an industry, markets, your competitors, your strengths and weaknesses, and define trends. Be the first one who knows the future trends and uses opportunities.
Every industry suffers from its own risks. It can be cyber threats, data leaks, etc. BI allows organizations to uncover, identify, and reduce them in the most efficient way. For instance, with BI fintech institutions create secure intelligence platforms, reduce fraud and cyber attacks what was possible in a harder and longer way.
If you run a business, you might think that implementing BI would come at a great cost and therefore be a luxury investment. But we can assure you that the gained insights will not only help to make smarter business decisions but also improve performance or reduce costs by spotting areas where money might be saved, so as a result increases your revenue. Moreover, there are BI tools that cost little or are even free of charge (e.g. Google Data Studio), so the budget question won’t be an issue.
Most of the business data is easily accessible. There's no need to code, perform data mining, or hire experts. The data can be exported from where it is stored (e.g. Excel) via the BI tool within a few minutes. Then you need to crunch the numbers and analyze and visualize the data to start taking advantage of BI.
Once the data is visualized through dashboards, there is no need to spend time trying to make sense of the data, as the idea is that these reports will control your business activity.
Business Intelligence Cycle
Its life cycle includes several important stages:
- Direction — determining the direction of development and goals
- Collection — gathering data and information from all relevant sources
- Processing — transforming raw data into a format, ready for analysis
- Analysis — interpreting the processed data
- Dissemination — communicating the newly-found insights to people
How to Build a BI Strategy
The business intelligence strategy is considered as some kind of a roadmap that aims to help businesses measure their performance and strengthen it with architecture and solutions. Here are a few steps to follow when building a business intelligence implementation plan.
Define Your Current State
To obtain the full potential of business intelligence and take your organization to the next level, you need to define simple questions:
- Where you are at this moment?
- What do you want to achieve?
- What’s possible to achieve?
An efficient business intelligence implementation strategy will enable your business to grow, so, as an owner, be ready to answer some questions:
- Machine learning — what, when, why it will happen?
- Predictive analytics — what may happen?
- Descriptive analytics — what happened? What's happening now?
Build a BI Roadmap
Strategy for business intelligence starts with a plan. There are many phases to implement BI at any organization, so the project roadmap should contain the why, what, who, when, and how the implementation is going to happen. No matter which project management approach you use (agile, waterfall, etc) it is a smart decision to communicate when milestones and tasks of the project are completed.
A roadmap is the outlook of the milestones and deliverables in chronological order. The point is that it helps every employee to stay on the same page, so be aware of what's been done and what's coming up, and enable them to adapt to changes.
Present BI to the Stakeholders
The other thing to do before implementing a business intelligence plan into your company is to set the terms and define the meaning of BI with all your stakeholders. As lots of employees are involved in the data processing, make sure that everyone is on the same page and has a mutual perception of what business intelligence development strategy is.
Set the KPIs and Requirements
At this stage, you need to define the problem and think of the business goal you are going to reach with the help of BI development strategy. Setting the plans helps you determine further parameters for BI, such as:
- What data sources will be used?
- What is the business analytics you want to keep an eye on?
- What metrics can improve your performance and strategy?
- What are KPIs and evaluation metrics that define tasks as accomplished?
Select the Tools
Selecting the tools for BI infrastructure usually depends on the industry, the size of the company, and your business needs. To understand what tool you need, it’s worth composing a requirement list for your business intelligence system and performing market research.
The BI market offers a number of tools that are available both as embedded versions and cloud-based (Software-as-a-Service) technologies. Some of the most used BI tools are Google Data Studio, PowerBI, Tabulae, Looker, Charito, Periscope Data, etc.
Create a Prototype
It is a short project to verify tech concepts by proposing numerous simplified features, validating assumptions, testing the product's functionality, and ensuring the concept is implementable or vice versa. Also, it helps to find the source data and where there can be some transformation to secure massive amounts of data while the end-users will get access to it.
Set the Team
Business intelligence strategy and roadmap can’t exist without people. The best way to create a team is to gather experts from different departments of your company who give specific insights, have a different vision, and make architectural, technical, and strategic decisions. Usually, there are five main roles:
- Head of BI — the person with business and technological skills, who generates insights and drives BI implementation.
- BI engineer — the person who designs, builds, implements, and sets BI systems (the most common technologies used are SQL, MySQL, AWS Redshift, HBase, BigSQL, Oracle, Apache Spark & Hadoop, SSIS, SSAS, Pentaho, Tableau, Power BI, etc.).
- Business analyst — the person who provides the rest of the team with expertise in data validation, processing, and visualization, and the person who transforms the analytics into actionable insights.
- Data Scientist — the person who uses analytics, statistics tools, and machine learning to pull out actionable value from big data.
If you don’t have an in-house expert team, there is always an option to hire a vendor who will offer solutions that best suits your business needs.
The Benefits of Outsourcing BI
- Cost and time savings
- Fresh, independent view from outside of the company
- Expertise and professionalism
- Focus on core processes while the BI team performs its job
- Accuracy and scalability
Doesn’t matter whether you are a small business or large enterprise, you will enjoy the benefits from implementing BI. Partner with a reliable vendor to manage the business data and take advantage of the valuable insights it brings.
So, BI is the practice of analyzing the data your company generates to produce actionable insights that drive business decision-making. It may sound simple in theory, but it required lots of computer processing power, coding knowledge, and advanced statistical skills.
Published at DZone with permission of Nazar Kvartalnyi. See the original article here.
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