Successfully running a modern business has become inconceivable without an effective Business Intelligence strategy. Developing and implementing proper BI, on the other hand, is hardly done without optimized Data Governance. Data is the very fulcrum of a streamlined workflow, regardless of the industry your company belongs to.
Many business leaders have known that Data Governance can improve Business Intelligence.
It means that efficient data management is a prerequisite to achieving advanced BI levels.
According to a Forbes study conducted across numerous global organizations, businesses that deploy robust DG strategies and use them to enhance their BI efforts report breakthrough ROIs when investing in business intelligence.
However, developing a powerful Data Governance plan based on consistency, reliability, and flexibility is not exactly a walk in the park. It requires a multi-faceted approach to data storage, tracking and management, and needs to be tackled with proper attention to detail. It is true for both small businesses and enterprise-level environments. Otherwise, your DG is likely to have certain pitfalls that would render all other aspects ineffective.
Before we jump to the ways Data Governance can improve Business Intelligence, let’s take a look at what it actually is.
Data Governance involves various processes, policies, roles, standards, metrics, and infrastructures that help businesses achieve optimized and effective use of data. Proper information management enables companies to reach their goals and objectives on time while being cost-effective. DG encompasses operational processes and employee responsibilities that allow businesses to achieve high quality and security levels across an entire ecosystem of data and data flow an organization is handling.
Effective and tactical Data Governance strategy should ensure that all data management roles are clearly defined across all departments and should provide a clear overview of who takes what action and when, and for what purposes.
If your business has dynamic data flows daily, and your communication channels convey pertinent information regarding business analytics and security, creating a functional, consistent, and well-crafted DG strategy should be among your top priorities.
Data comes in various forms. For example, it can convey personal information that belongs to your clients. At the same time, it can also include raw performance metrics that your business can use to analyze and glean valuable insight into:
– how it can improve its operational processes,
– shorten time to market,
– recognize business drivers and boost ROI.
For instance, if you run a SaaS-based business. Your user base is enormous and diverse; one of your main drivers for having a powerful data governance strategy should be ensuring that client-based information is stored and processed securely. It flows through your company and communication channels.
Now let’s go over some of the essential best practice tips on using DG to enhance your Business Intelligence methods.
Every business owner knows that timing is everything. One can have a killer product and service, but if the strategy isn’t impeccably data-driven and timely, likely, their business won’t reach its full potential. Having an effective DG tactic in place can help you improve all aspects of your business workflow and all other operational processes, allowing you to improve data gathering, storing, and processing. This way, you can perform deep data analysis, and optimized ROI will undoubtedly ensue, followed by the enhanced discovery of new business opportunities.
This type of advanced business flow can hardly be achieved if each of your teams and departments isn’t getting the right data. The right raw data leads to smart insight, and intelligent insight then leads to improved Business Intelligence. However, suppose your raw data isn’t governed and managed the right way. In that case, the process of timely data analytics is severely hindered, which results in a ripple effect across all your processes and workflows.
According to an ever-relevant Forrester report titled “Best Practice Tips for Business Intelligence Success,” the main secret of surefire business success is the right correlation between data, analytics, processes, and tools, as well as providing these assets to decision-makers at the right time.
Data is the lifeblood of all operational processes. Data is an asset that needs to be managed so that it is highly accessible, easily usable and reusable, and highly secure. Developing effective data governance can help business owners streamline all operational processes and improve decision-making, so any potential efficiency gaps are easily mitigated. When properly implemented, it can reduce data inconsistencies to a minimum and remove the risk of human error from the equation.
According to Statista, the US alone saw over 1000 data breach cases with over 150 million records exposed to cybercriminals. Granted, this is lower than back in 2018 when 471 million records got exposed, and these attacks seem to be decreasing lately, but the overarching trend since 2005 is alarming.
We also need to address the insight provided by an Osterman Research study stating that companies typically move, store, and archive 75% of their critical data and intellectual property within their complex ecosystems of communication channels.
Minimizing the risk of cyberattacks should start with handling the data management and protection of your emails, as email platforms are the most widely used communication channels that permeate all modern companies. If utilized and implemented correctly, this type of mindset should trigger businesses to deploy top-tier email archiving methods and retention policies so any malware infiltration or data loss is obviated and network breaches are prevented.
Additionally, having a tight email retention policy in place allows you to determine DG for email-based data in terms of security, cost-effective retention, and retrieval of data, as well as ensure regulatory compliance.
In order to make proactive and revenue-driving decisions, businesses need to make sure that their data is of high quality. Subpar data quality results in false insights and can cause huge damages to your cost-effective resource usage. In order to always have quality data at your disposal, your DG plan needs to tackle a continual process of tracking, collecting, storing, updating, and creating data-driven insights that initiate growth and success.
Advanced BI cannot be performed without reliable data that fuels faster decision-making and powers innovation. The mere existence of raw data is not enough to drive productive Business Intelligence systems. You need a DG-powered BI and separate the wheat from the chaff in terms of data quality and deep analysis. Only then will you be able to grow and dominate your target market.
In order to determine the quality levels of your data, we recommend this insightful article by SmartBridge.
Data Governance and Business Intelligence go hand in hand. Only the highly accessible, accurate, well-organized, and properly managed data can help you get smart insights and boost your BI efforts.
Once you have a functional, efficient, and cost-effective BI strategy in place, we strongly recommend that your BI environment also has adequate monitoring methods so you can further improve upon your existing data management systems.
Author Bio: Damian is a business consultant and a freelance blogger from New York. He writes about the latest tech solutions and marketing insights. Follow him on Twitter for more articles.