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    What is Business Intelligence Governance & How to Achieve it?

    What is Business Intelligence Governance & How to Achieve it?

    Businesses are going at breakneck speeds to keep up in this highly competitive market. They are doing anything that they could possibly do to get the edge over their competition. A lot of data and great Business Intelligence strategies are what can help your business truly get a competitive advantage. But even with great data, implementing business intelligence in the most efficient & effective way is crucial. And that is where BI governance comes into play. But what is business intelligence governance?

    Business intelligence governance is a collection of all the strategies and processes such as staffing and tools used (hardware and software) that ensure the investment in Business Intelligence is generating true value. It also ensures that the implemented BI system has the necessary security, data privacy, content management & engagement, and access controls. Now that we know what BI governance is, let’s find out how you can achieve business intelligence governance in this blog.

    How effective is BI Governance?

    Effective BI governance is at the foundation of every successful BI strategy. Usually, the BI team creates and deploys the report for the organization. Here BI governance is important and is effective only when it properly balances out all the engagements, content management, and access control as well. It is most important to maintain the report most efficiently and safely.

    Being one of the leading business intelligence consulting services providers, we understand that BI governance should extend well beyond security and basic data governance. It is the best approach that focuses on BI resource optimization while also building trust with the users. So we’ve listed a few points that will make your business intelligence governance more effective.

    • Content should be secure and it should not be hidden from the business user while reporting the same in the BI platform.
    • Data quality is more important as users have to trust BI reporting.
    • BI tools are very effective and prominently used for day-to-day decision-making.
    • It should be a user-dependent workflow
    • Reports and dashboards should be constantly updated wherever it is posted.
    • Self-Service BI should be achieved as business users will be able to access and explore the data in the BI environment.
    • Teamwork should be there to maximize the business value.

    Achieving Business Intelligence Governance

    • Access Control or Audit Control
    • Maximize User Engagement
    • Displaying Essential Metadata
    • Optimizing License Management
    • Business Intelligence Governance Committee
    • BI Governance Framework

    Access Control or Audit Control

    Access control or Audit control is maintaining the balance between Discoverability and Data security to achieve maximum collaboration. Without proper discoverability, users will not be able to see all the datasets and reports in the dashboard. So users who might need it might not even know that such data exists and might end up wasting their time creating another similar report.

    But discoverability should be done in a way that sensitive data doesn’t fall into unauthorized hands. So you have to make sure that the appropriate content is discoverable but not accessible to all users. By keeping sensitive data on a need-to-know basis, discoverability can be achieved without compromising data security. Here are a few tips to achieve this.

    • Create different roles based on the level of access needed.
    • Limit the administrative abilities of regular users by limiting their access to create, edit, and delete data.
    • Create user groups to easily map different users based on their roles.
    • Create a Centralized Catalog of all the reports to improve discoverability.

    Maximize User Engagement

    The entire point of Business Intelligence is to identify the most important data from the clutter to make the right decisions. But having a cluttered dashboard that users don’t engage with is of no use. So business intelligence governance has to be implemented to observe how users engage with different data assets to identify opportunities for improvement. By doing so you will be able to maximize the value a business can attain by investing in Business intelligence.

    • Make sure to track the usage pattern of important data assets.
    • Look into data assets that have low engagement & identify the cause.
    • Review existing dashboards and remove data assets that you retrospectively don’t find to be effectively improving the business process.
    • Identify high user engagement data assets and look if they can be included in other dashboards that might benefit.

    Since an organization will have different business units that require different reports, the centralized catalog of reports will also help in increasing user engagement.

    Displaying Essential Metadata

    Visual representation of data without proper context can make it very hard to understand the dashboard or report. So without the proper use of metadata, the entire point of using visual representations will go to waste. Explaining this with the help of an example would be much easier.

    Displaying Essential Metadata in Business Intelligence Governance

    If you look at the image, It is clear that the lack of metadata makes it almost impossible to comprehend anything from the visuals. That is why displaying metadata is an important aspect of Business Intelligence Governance. But at the same time, excessive metadata should also not be used as it might create additional confusion. Though there are different types of metadata, the 3 primary categories when it comes to an organization are Descriptive, Administrative, and Structural metadata.

    Descriptive Metadata

    It is the information about the resource such as titles, dates, and other keywords that will describe the asset and help with easy identification & understanding.

    Administrative Metadata

    It is information that specifies the technical source of the digital assets such as license, rights, and file type.

    Structural Metadata

    It specifies how the digital asset is organized. This includes data such as pages, tables of contents, chapters, and indexes.

    Optimizing License Management

    Most of the BI tools such as Power BI, Tableau, and SAP licensing costs depend on the number of users at different levels. So you will be able to cut costs by managing the license of the users based on their usage; making it an essential part of Business Intelligence governance. The following points will help you optimize License management.

    • Implementing an auto-provisioning technology to grant access to users who do not have a BI Tool license.
    • Check and deallocate the license which is unused by the users.
    • Identify the under-utilizing license user and downgrade those.

    Business Intelligence Governance Committee

    When the number of reports is high, it is likely that we might face discrepancies between them. One report might suggest that the sales were great, whereas a different report might say that sales have gone down. How will you be able to solve such differences? That is why you’ll need to assemble a business intelligence governance committee keeping the following points in mind.

    • The BI Governance Committee should have members from all the departments in the organization. (From the Senior management level to the end user.)
    • Each team should bring their perspectives and priorities to predict which project is going to peak and to identify projects that need more concentration.
    • Make sure to identify redundancies and think of ways to combine efforts to get better results.
    • The BI governance committee should ensure that the organization stays aligned with the business goals.
    • It should include people from IT to be the Subject Matter Experts that will help us make the right decisions.

    BI Governance Framework

    Using the right framework is very important when it comes to Business Intelligence Governance as it involves the entire BI lifecycle. It will be instrumental in implementing an end-to-end process to create a BI report which supports the end-users and business users. So let’s now explore all the aspects that make a BI Governance Framework.

    Tool Selection

    Selecting the right tool is at the core of the BI process as it directly influences the success of a project. Make sure the tool you choose supports the type of data you’ll be handling. But it is important to keep in mind that creating various reports isn’t the only purpose of the tool. The user must be able to interact with the report with ease as the tool acts as the end user’s interface. Since an over-complicated tool can cause issues for end users, make sure the tool has data presentation tooltips, drill-down actions, accessible functionality OLAP, etc.

    Data Integration

    Once you have chosen the right tool, the next step of the Business Intelligence Governance framework would be to analyze the quality of the data and its relevance. If everything is of the expected quality and in the format that fits your BI tool, you can go ahead with data integration. But if you have opted to use a tool that doesn’t support the data format you have, you might need to invest in a data acquisition project.

    Analytics

    Once the data has been integrated into the tool of your choice, the natural next step would be to present the data to the users. There are primarily three main stages involved in analyzing the data, and they are Data Mining, Data Cleaning, and Descriptive Statistics. Once the analysis is done, we need to work on the data modeling process that will help us present the data in an accessible form (or) workable form to the users.

    User Acceptance

    The next step in the BI Governance framework would be to analyze if the data we’ve presented is effective or not. So checking the User Acceptance of the completed BI product will help us understand if the users are engaged with all the processes, steps, and challenges involved with the implementation. The end users are the best people who can test out the product as they will be able to effectively review if the data and tool functionalities deliver the expected results.

    End-User Support

    End-user support is the help desk that helps a user when they encounter a problem with the BI product or any functionalities in the tools. In addition to that, this team will receive feedback from the end-user or business user to keep the user and the IT partners on the same page. This will improve the overall BI process and empower the BI community as well.

    Conclusion

    We hope you found our blog to be informative and now have a clear understanding of why Business Intelligence Governance is important and how to achieve it as well. Constructing a well-organized framework for BI governance is one of the key factors that will help improve organizational performance. Being one of the leading Business Intelligence companies, we understand this fact very well and use it as a base upon which we build the other discussed factors.

    The Importance of Actionable Business Intelligence & Its Challenges

    The Importance of Actionable Business Intelligence & Its Challenges

    The fundamental reason for employing business intelligence is to make data-driven decisions that will create a positive impact on your business. So having large amounts of processed data that you cannot use to make any decisions is of no use. Likewise, having the vital data you need to make those important decisions buried in a cluttered dashboard or report is also of no use. Actionable business intelligence goes beyond business intelligence by helping us create a roadmap using the data at hand. There might be a hundred different data points in a report, and actionable business intelligence will help us focus on the ones that matter to your need. So in this blog, we will be looking at how you can develop actionable business intelligence and the various challenges that you might encounter.

    What is Actionable Business Intelligence?

    If you are unsure of what actionable business intelligence is, and how it differs from business intelligence, let’s clear it up for you. Regular Business Intelligence only opens up the opportunities to obtain value, whereas actionable business intelligence is what can truly drive your business in the right direction by creating value from those opportunities. To put it in simple terms, actionable business intelligence is the information that you can use to make important business decisions and also help in implementing them.

    Benefits of Employing Actionable Business Intelligence

    • Attain Competitive Advantage
    • Make Better Decisions
    • Identify focus points to increase profit
    • Track performance
    • Identify customer interests
    • Predict market trends
    • Discover bottlenecks & issues

    Actionable Business Intelligence Examples

    Competitor’s Price Range

    You can make all the analyses you want internally to find out how much a product or service can be offered by you. But it is equally important to know where you stand amidst your competition when it comes to pricing.

    Targeted Demographic

    Knowing who will eventually use your product or service is an integral part of making it successful as you will know how to cater to their needs. Instead of just having a generic idea of who your target audiences are, knowing their demographics can help you identify attributes such as age group, location, and so on.

    Resource Utilization

    Understanding the workload of your employees to assess if they are over or underutilized is a crucial aspect of any business. So keeping track of the number of projects an employee is working on will be a great idea.

    Arriving at Actionable Business Intelligence

    So the regular business intelligence process has to be followed here as well. Once we are at the reporting stage, the additions we have mentioned can make your business intelligence actionable. We will also explore what these additional steps are using the above-mentioned examples.

    Regular Business Intelligence vs Actionable Business Intelligence

    Alerting System

    Your dashboard might have a space monitoring the competitor’s price range every day. But what if your competitor runs a special offer or is providing additional discounts? The price change should be bought to your attention as you cannot be following every data point on the dashboard. So either a push app notification or an alert beside the data will be instrumental in achieving this goal.

    Recommendation Engine

    Let’s assume your product is targeted toward the youth community. This is where the target audience’s demographics come into play as using such data the BI system will be able to identify if your product sparks interest amidst a new demographic of people as well. So based on the data, the recommendation engine should be able to recommend an update to your advertising strategy. Another very simple example would be the recommendations that we see as consumers on platforms like Netflix<, Amazon, and so on.

    You can either achieve this by employing the heuristic approach that relies on human observation and knowledge to get such recommendations. If not you could use a statistical approach that relies on machine learning to use all the data at hand to make these recommendations.

    Effective Automation

    Using only a selective few data points from the numerous data that are available to make your decisions can also be seen as underutilization. But it is extremely difficult to pull data from different data streams (both internal & external) and then feed them into another system to get the insights. In most cases, it is not humanly possible to keep tabs on such large amounts of data. Even if the number of data is less, it does take a lot of time to perform such operations. That is why it is important to automate such actions and even cross-validate them in the dashboard to see how accurate it is as well.

    Challenges of Arriving at Actionable Business Intelligence

    Obtaining actionable business intelligence insights is not easy as we would have to overcome numerous challenges during the process. But given the scope that we have seen earlier, it would definitely be worth the effort if we overcome these challenges. Being an experienced Business Intelligence service providers, we have listed out the most common challenges one might encounter, and have elaborated on how we can overcome them as well. Most of the challenges we see here would apply when it comes to regular business intelligence as well.

    • Data preparation from different data sources
    • Having Structured and Reliable Data
    • Measuring the Correct KPIs
    • A well-defined BI strategy
    • Self-serviceable Solutions

    Data preparation from Different Data Sources

    This might not seem like a very big concern when you are operating at a very low scale. But the scale of any Business Intelligence is prone to increase over time. So processing all the information from the different sources will become a definite challenge. In addition to that, you will also need to access all the data past the various security and permissions levels. So if there are no proper standards followed for processing the internal information across different departments and divisions within the organization.

    But you can overcome these issues by using an effective data warehouse that can function as a hub for all your business intelligence data. Make sure to use the various BI tools such as Microsoft Power BI , Hubspot and so on that are available in the market today to integrate the data effectively. The lack of such integration will create data silos and prevent your data from ever transforming into actionable business intelligence.

    Having Structured & Reliable Data

    It goes without saying that the data you are using to make the important business decisions should be concrete. Having poor data quality is the same as building something with a weak foundation, it will definitely crumble. In addition to that, unstructured data will result in a lot of time wastage as you would have to spend hours cleaning the data and modeling it. If having the right data is important, so is having it at the right time.

    Measuring the Correct KPIs

    Since there is such an abundance of available data, it is very easy for us to lose our way by focusing on the wrong KPIs (Key Performance Indicators). Apart from the large quantity of data, the process behind the data processing should also be simple enough as a convoluted business intelligence process makes it hard to focus on the correct KPIs. Few businesses also limit themselves by measuring just the financial KPIs even though they are truly not enough. So KPIs such as the rate of progression and level of performance should also be of prime importance. Utilizing an effective KPI dashboard will enable organizations to assess their performance against both internal and external benchmarks.

    A well-defined BI strategy

    The one simple solution to avoid most of the problems you face will be to have a well-defined Business Intelligence strategy that is tailored to your needs. Proceeding without a proper plan is equivalent to flying blind and it will not do you or your business any good. With the amount of data and dynamic BI reporting tools available at your disposal, you will be able to take your BI process to the next level. So build a strategy that takes the existing process into account, validate your solution with a Proof of Concept, and choose the best tools for your needs. By doing so, your data will flow in the right direction without any hindrances and ultimately become a value generator.

    Self-serviceable Solutions

    The entire objective of having visually rich BI dashboards is to ensure that these highly potential solutions are self-serviceable in nature. Having a complicated process that demands specialized end-user training compromises all the possible benefits.

    • Identify which solutions are essential for making the decisions and keep them at the forefront.
    • Make sure the solutions don’t require technical expertise.
    • Ensure these solutions are accessible on portable devices.
    • Make sure the employees are equipped to handle the dashboards effectively.
    • Keep the Installation & Deployment process simple.
    • Ensure that everyone who has to adapt to the technology move on from the traditional methods they are accustomed to.

    Conclusion

    Hopefully, you now have a clear understanding of what actional business intelligence is, and how it is different from conventional business intelligence. Our vision as a Business Intelligence Company is to always ensure our insights are actionable. We ensure that the true potential and value of business intelligence are realized by making them actionable. We will be publishing more informative content and recommend you to subscribe to our newsletter to stay updated.