Improving Business Intelligence Advancement – Business intelligence is a means of turning raw data into useful insights. It allows you to collect data from various sources, organize it and then enjoy the analytics. Do you need it? Probably yes, because it is the most balanced view of the business. But as you can imagine, starting such a complex task requires some preparation and we hope to help you with this. If you are implementing some BI procedures in your company, this article will help you get organized. Now, let’s talk about your business intelligence strategy.
A BI strategy will allow you to solve all your data problems and needs, create and maintain a unified system. What happens when you start implementing BI without a strategy? Basically, you focus too much on getting these graphs, but no one in the company understands why or how to use them. Here’s a handy illustration of life before and after a BI strategy.
Improving Business Intelligence Advancement
We previously posted a guide to implementing BI practices in your organization. Now, we’re going to detail one step of your implementation plan—documenting your BI strategy.
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Appearance. Why are you building a BI practice in your company and what do you want to achieve?
Tools and architecture. What dashboards and solutions do we want to build? For which areas? How will they affect these areas?
So, as you look at your company’s corporate strategy, you can imagine what BI initiatives you want to start. This view then helps you select the right people who will use the selected processes. You use software tools to support people and processes. And finally, you create an architectural plan for its development. Now, let’s talk about these steps in detail. And we start with a business that has a form of BI.
To know where you’re going, you need to build a foundation. Say, you know a few departments use analytics, but the data is largely siled—marketing people don’t have access to sales data, and customer support tracks user feedback for their own internal purposes—or the analytics aren’t there. everything – basically, seems to work, but it is not clear how effective it is.
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So, the first step is to talk to all the players in today’s BI processes: users and the IT team, department managers and stakeholders. As a result, you should have answers to the following questions:
Then, put together a SWOT analysis to organize what you’ve found. A SWOT analysis, one of the key strategy building tools, will help you uncover your key assets and challenges for the next phase.
Vision is a combination of purpose and direction. There is no invisible strategy. It manifests itself in the form of very important decisions about what information we will provide or who will be able to understand it.
Visions also have a very common purpose: to explain to people in your organization—those who have favorite tools and processes—why they need new ones, and how the changes will work.
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Our corporate vision for BI is to create and support a secure and accessible data infrastructure anywhere in the enterprise. Our corporate standard for a BI tool is ________. We use a BI Competence Center based on end-user satisfaction surveys and successful deployments. A significant segment of the end-user community demands access to real-time information. So we have provided such an infrastructure to accommodate them. We currently support ___% of ___ users. Our goal is to increase usage by ___% (date). We measure the cost of using BI against business value and ROI. Thus, our approach to success is transparent, measured, responsible and supportive.
One also said that the vision would help protect executives whose only goal is to provide staff with cheap tools and get back to “real work.”
Finally, the view is often accompanied by a BI maturity model – a scale that shows the maturity of your strategy. You can find several maturity model definitions on the web, including a very popular model from Gartner. According to them, there are five maturity levels for BI: naïve, opportunistic, standards, enterprise, and transformative. Using these models can help you identify your areas of progress and what your next goals might be.
Managing BI is about defining and implementing a BI infrastructure. (Not to be confused with data governance, which ensures the consistent use of data across an organization.) This includes three components:
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Identify BI management members, their roles and responsibilities, functions, goals, and relationships with the various structures of your company. Involve people at all levels, from executives to end users, to bring all perspectives to the table. So, it’s not really a group of BI experts, but rather a board of representatives from different areas of the company.
Large enterprises will benefit from an entire team of experts at the Business Intelligence Competence Center (BIC). Bix helps identify data needs, establish data management structures, monitor data quality, and support overall data integration processes. These are programmers, data scientists and analysts, experts in relational databases and reporting tools. If you have a pool of experts to collect stocks or resources, we recommend creating such a team.
The BI lifecycle is the framework that supports the BI effort or the architecture and tools used for it. Typically, the architecture looks like a pipeline that starts with data sources (your ERP, external sources, etc.) and then follows a data integration process, or ETL, where the data is transformed and loaded into a repository (data warehouses and data marts). The data is finally displayed on the dashboard and interactive tools. There are several architectural styles with different configurations of system elements.
Choosing BI tools. Depending on your level of confidence, you can get an end-to-end platform or create your own mix for each stage of the BI process. You can also find a great match based on price or what you want to install in the building. Use our guide to the best BI tools to help you with this task.
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Prepare the data integration process. Identify data sources and your BI tool can evaluate them. Ensure that data is of high quality and establish processes for data preparation. See Data Warehouse Architecture.
Provide information display. Based on end-user needs and KPIs, determine what types of reports and dashboards your system will display. Use our guide for some data visualization ideas, where we also list some handy tools and libraries.
Conduct user acceptance tests. User acceptance testing is an often overlooked but critical process where you ask end users to perform a series of tasks and gather information about the usability of the system. Then you prepare the test cases, choose the test time and select the necessary tools.
Training. End users need to be trained to understand the data basics and use the visualization platform. Before that, the non-BI experts of the management team must be trained to understand the stages of data transformation. Basically, recognize where the knowledge gap is and fill it as soon as possible.
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In addition to training, prepare to serve customers and solve their problems. Manage the feedback process and decide how to react quickly and cost-effectively. Having a customer support base is where you cover them from three stands:
Data education support is the provision of a knowledge base for users to find answers about incoming data: metadata, data purpose, metrics, data source, etc.
Tool support – If possible, choose a tool with end users, then set agreed time frames for responses, and let them know what channels or contacts they can use to get support.
Business support – end users not only understand the data, but know how to get value from it. Designate mentors in each chapter to help users learn how to deliver value through BI tools, what metrics and metrics to look for, and how to identify data trends.
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Here, the roadmap is a visual document of the various stages of implementation within the timeline. With this step, you have all the information you need to organize and approve the map, all you need to do is set timelines and deliverables for each task.
A roadmap may only include high-level tasks such as “Finding a BI vendor” or can be shortened to “Create a list of top ten matches,” but a high-level overview is sufficient for strategic maps. Below is an example of such a roadmap covering three quarters. It has deliverables and milestones, and tasks are divided into teams.
Our guide to building a road map should help you further, but we’ll reiterate a few key ideas here.
The logic of the strategy document is that it will be a reference point for the entire organization and will be used to present the strategy. What sections should this document include?
Business Analytics Process With Life Cycle Diagram
How will you measure up?
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