Business Intelligence Advancement Tasks – Business intelligence is the process of transforming raw data into actionable insights. It allows you to collect data from different sources, organize it and then enjoy the analytics. Do you need it? Probably yes, it’s the most balanced view of the business you can get. But as you can imagine, starting such a complex endeavor requires some preparation, and we’ll help you with that. If you have already introduced some BI practices in your organization, this article will help you get organized as well. Now, let’s talk about your business intelligence strategy.
A BI strategy will allow you to address all your data problems and needs, create and maintain an integrated system. What happens if you start implementing BI without a strategy? Basically, you focus a lot on getting those maps, but no one in the company has an understanding of why and how to use them. Here’s a simple explanation of life before and after a BI strategy.
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Previously, we posted a guide to implementing a BI practice in your organization. Now, let’s take a closer look at one phase of your implementation plan – documenting the BI strategy.
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Vision Why are you developing BI training in your organization and what do you want to achieve?
Tools and Architecture. Which dashboards and solutions do we want to build? For which areas? And how will they affect those areas?
So, when you look at your company’s corporate strategy, you envision what BI initiatives you want to launch. That vision helps select the right people who will use and maintain the chosen processes. You use software tools to support people and processes. Finally, you establish an architectural blueprint for its development. Now, let’s go through those steps in detail. We’ll start with businesses that already have some form of BI.
To know where you are going, you need to set a baseline. You know many industries use analytics, but the data is often siled — marketers don’t have access to sales information, and customer support tracks user feedback for their own internal purposes, or there’s no analytics at all. All – basically, it seems to work but how effectively is not clear.
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Therefore, the first thing to do is to talk to all the players of the current BI processes: users and the IT team, department managers and stakeholders. As a result, you should have answers to the following questions:
Then, compile a SWOT analysis to organize your findings. One of the key strategy development tools, SWOT analysis can help you uncover your key assets and issues for the next phase.
A vision is a combination of purpose and direction. There is no strategy without vision. This manifests itself in the form of many important decisions, such as what data we receive or access to intelligence.
A vision also has a more mundane purpose: explaining to people in your organization — who already have their favorite tools and processes — why they need new ones, and how the transition will happen.
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Our corporate vision for BI is to build and support an infrastructure with secure and authorized access to data held anywhere in the enterprise. Our corporate standard for a BI tool is ________. We hire and scale our BI competency center based on end-user satisfaction surveys and successful deployments. A significant segment of our end-user community requires real-time data access. Therefore, we have provided such infrastructural facilities to accommodate them. We currently support ___ users representing ___% of our user population. (Date) Our goal is to increase usage by ___%. We weigh the potential costs of increased BI usage against the business value and ROI we receive. Therefore, we have a clear vision that makes our success measurable, accountable and defensible.
Biere also notes that a vision articulated in this way can help prevent executives whose only goal is to provide employees with cheap tools and return to “real work.”
Finally, the view is often accompanied by a BI maturity model – a measure that tells you how mature your strategy is. A few of the most popular models from Gartner can be found online explaining maturity models. According to them, BI has five maturity levels: Ignorant, Opportunistic, Standards, Enterprise, Transformational. Using these models helps you identify your areas of improvement and what your next goals might be.
BI Governance means defining and implementing BI infrastructure. (Not to be confused with data governance, which ensures consistent use of data in an organization.) It includes three components:
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Define BI governance members, their roles and responsibilities, functions, goals, and relationships to various structures within your organization. Include people at all levels, from administrators to end users, and bring all their perspectives to the table. So, it’s not really a group of BI experts, but rather a group of representatives from different organizational areas.
However, larger organizations will benefit from an all-expert team at the Business Intelligence Competence Center (BICC). BICCs help identify data needs, establish data governance structures, and oversee data quality and general data integration processes. These are programmers, data scientists and analysts, experts in relational databases and reporting tools. If you have some experts or resources to hire them, we recommend establishing such a committee.
A BI lifecycle is a framework that supports BI efforts, or the architecture and tools used for it. In general, the architecture looks like a pipeline that starts with the data sources (your ERP, external sources, etc.), then follows the data integration process, or ETL, where the data is transformed and loaded into the repository (data warehouse and data marts). The data is finally displayed in dashboards and interactive tools. There are certain architectural styles with different configurations of system elements.
Choosing BI tools Depending on your level of confidence, you can either get an end-to-end platform for each step of the BI process or build your own mix. You can find the perfect match price-wise or depending on whether you want to use on-premises or in the cloud. Use our guide to the best BI tools to help you with this task.
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Drawing up the data integration process. Define data sources and make sure your BI tool can evaluate them. Ensure data is of high quality and set processes for data preparation. Consider the architecture of the data warehouse.
Ensuring data presentation. Establish what types of reports and dashboards your system will display based on end-user requirements and KPIs. Use our guide for some data visualization ideas, where we list some handy tools and libraries.
Conduct user acceptance tests. User acceptance testing is an often overlooked but important process where you ask end users to perform certain tasks and collect output information about the system’s usability and performance. Then you prepare the test cases, choose the test time and select the required tools.
Conducting training. End users must be trained to understand the data bases and use the visualization platform. Before that, non-BI skilled members of the governance team must be trained to understand the phases of data transformation. Basically, find out where the knowledge gap is and make sure to fill it as soon as possible.
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Apart from training, prepare to serve users and solve their problems. Set up a feedback process and determine how to react as quickly and cost-effectively as possible. Having a user support structure means you cover them from three status points:
Data Education Support – Providing a knowledge base that allows users to find answers about incoming data: metadata, data purpose, metrics, data sources, and more.
Tool support – If possible, work with end users to choose the tool, establish agreed-upon timeframes for problem response, and communicate which channels or contacts they can use to get support.
Business Support – Ensure end users not only understand the data, but also how to derive value from it. Appoint mentors in each department to help users learn how to deliver value with BI tools, what metrics and dimensions to look for, and how to identify data trends.
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Here, a roadmap is a visual document of deliverables at various stages to be executed within a timeframe. With this step, you already have all the data you need to organize and plan on the map, you just need to set time frames and deliverables for each task.
A roadmap may only cover high-level tasks like “Find a BI vendor” or be shortened to “Create a list of top ten matches,” but for strategy mapping, a high-level overview is sufficient. Below is an example of such a three-quarter length road map. It consists of deliverables and milestones and tasks are divided by teams.
Our guide to creating a roadmap will help you further, but we’ll repeat some key ideas here.
The logic behind a strategy document is that it serves as a reference point for the entire organization and is used for strategic presentation. What sections should go into this document?
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How do you measure?
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