We have an expression in data analytics: “data rich, information poor”. This expression is a reflection of the many companies that implement data collecting software applications, but fail to actually extract useful information from them.
Data rich, information poor commonly plagues businesses, rendering their investments in and efforts to collect data completely futile. Data-driven management services can significantly reduce the potential for wasted investment in data collection services.
8 Crucial Components to Boost a Data-Driven Enterprise:
- Data governance. Key performance indicators (KPIs) rely on data quality, which is easy to monitor and sustain when running data-driven initiatives with experienced, knowledgeable governors. Data governance assesses all the roles and responsibilities of systems involved. Make sure that the team you use to oversee your data collection and analytics has a thorough understanding of all IT systems involved and all goals associated with the information at hand. Governance should be left in the hands of company leaders and executives.
- Metadata management. Metadata incorporates structural elements of data information, including formulas, definitions, and other pertinent details. Metadata management organizes these aspects of data into concise, digestible presentations in the form of dashboards, tables or reports.
- Data acquisition. In order to comprehensively evaluate data, companies must implement the right data acquisition tools. The tools might range based on goals, so speak with your advisor or consulting firm to understand which tools are best for you data raking.
- Business Intelligence. Business intelligence (BI) is the most widely used data management practice. BI hosts a slew of tactics to keep data systems intact and delivering useful insights. Tactics include predictive modeling, conduct and ad-hoc queries and breaking data down into information subsets. BI is the useful summation of all data collection, analytics, and organization. BI extractions are used in every branch of a company, and should always be communicated to the appropriate decision-makers, leaders, and managers.
- Data architecture. Extraction, integration, and analysis are the three tiers of information collection and digestion that all companies must follow. Each layer should follow the guidelines and direction and goals specific to the company. Remember, in order for data to be actionable, it must be oriented toward an end goal of the company.
- Governance. Incorporating data analytics is a first priority for growing your business, but it’s only one element in a range of many essential business components. Ensure that all facets of your company are in order: clinical, stakeholders, IT, funding and data implementation. Data management will help oversee all these elements and run all systems involved more efficiently.
- Master data management. Master data management (MDM) focuses on integrating and maintaining all the systems involved in data governance. Master data fuels all decisions and growth models of a company, so keep the master goals set, organized and updated is crucial to success.
- Technical architecture. As data systems grow and collectible information expands, it is increasingly vital to have the right technical architecture in place. Properly configured servers keep information streamlined, organized and up to date.
Building a data-driven organization is one of smartest transitions you can make in your small to mid-sized business. Basing your strategy on data will ensure that your performance matches goals and realistic, quantifiable consumer information.
To grow your understanding running a data-driven and based business, reach out to our experts at Quantum FBI. We can help you understand underlying reasons for mediocre performance and identify ways for you to reach your financial and brand objectives.