As businesses worldwide witness drastic acceleration in digitization, organizations are swamped with massive data streams, pushing them to become more data-driven than ever before. Undoubtedly, data is emerging as a critical business asset, but its value depends on intelligently harnessing it to generate actionable insights to assist strategic decision-making. Data and analytics capabilities have developed at lightning speed in recent years and increasingly fuel the adoption of data-driven strategies. A recent survey of industry-leading firms by Statista brings out interesting facts about the adoption state of big data and analytics in the year 2020 compared to 2019.
The survey results reinforced the pivotal role of data in reshaping corporate decisions, reimagining the competitive landscape, driving innovation, and building data-driven organizations. The survey revealed that 37.8 percent of respondents were able to create a data-driven organization in 2020.
What is a Data-driven Organization? Why has it Become a Business Imperative?
A data-driven organization fosters the culture of leveraging data and business intelligence to make all corporate decisions. Its goal is to design a structure where everyone in the organization approaches each decision by exploring and analyzing relevant data. It strives to make data-driven intelligence a natural component of the organizational workflow. Data-driven organizations encourage all stakeholders to base their daily business activities on data and insights instead of mere gut instinct. Besides, data-driven organizations are highly resistant to changes in the economy, technology, or competitive landscape and are operationally more predictable. Data helps organizations perform better by proactively highlighting the areas of improvement and providing insights to strengthen current and future decision-making. With continuous improvement and accurate forecasting, organizations enhance innovation, attain a competitive advantage, and become more profitable.
Let’s take a quick look at common characteristics of successful data-driven organizations.
the concrete foundation for an effective analytics strategy. Continuously improving data quality through constant data validation, hygiene checks, and quality control is crucial for leveraging data to enable scientific decision-making. Implementing an automated data management system replaces manual data logging, management, and maintenance processes and eliminates data errors and duplication. Smart data management tools also allow seamless data integration and data governance to monitor and secure sophisticated data and information.
Implement Cohesive Data Analytics Platform for Better Decision Making
An intelligent data analytics software is necessary to simplify the big data analysis, execute heavy lifting of data science and complex calculations to enable scientific decision-making. Business leaders need a constant flow of data insights to innovate, develop new business models, product offerings, and revenue streams, plan operations, and maintain a competitive edge. Modern data analytics software with embedded advanced analytics capabilities such as predictive analytics and data-driven recommendations give more power in the hands of the decision-makers. Smart data analytics solutions help visualize data in easy-to-understand formats, such as charts and graphics, and customized reports and dashboards give a bird’s eye view of mammoth data at the click of a button. Therefore, such solutions are essential to eliminate complexity and help in focusing on critical information. Besides, business users can use these solutions to configure metric-driven notifications or customized alerts for proactive response management and process improvement.
Embark on Your Data-driven Journey with Experts
The writing is on the wall; organizations that will leverage data for improved decision-making will emerge as winners in today’s digital world characterized by uncertainties. Modern businesses using advanced analytics solutions to monitor, analyze, and respond to changing conditions faster than the competitors will certainly gain a competitive advantage.
Businesses are increasingly turning to partner with data and analytics specialists, such as Mothersonsumi INfotech and Designs Ltd. (MIND), a digital transformation company, to develop an analytics-driven culture and accelerate scientific decision-making. The team of specialists at MIND works closely with businesses to transform them into a data-driven organization by enabling them to manage their data better, execute complex analysis and get smarter insights about different business aspects. Consult the experts today to maximize your data’s value and make analytics an integral part of your business decision-making.
- Centralized and Organized Data: Well-structured data from internal and external sources is aggregated centrally to serve as a single source of truth.
- Easy Data Accessibility: All the employees across departments have access to the necessary data and insights to improve their day-to-day decisions.
- Standard Policies to Govern Data Quality Set of policies & procedures help establish governance mechanisms, helping to maintain superior data quality for deriving data-based business intelligence.
- Integrated Data Analytics: Embedded data analytics tools encourage easy adoption and ensure seamless data correlation across functions to derive comprehensive valuable insights.
- New Business Models: Data, machine learning, and artificial intelligence are revolutionizing the business landscape. Businesses are increasingly turning towards new data-powered business models to respond promptly to growing customer demands and rapidly evolving operational models. Innovative enterprises must leverage advanced analytics for transforming data into actionable insights through predictive analytics, real-time data stream ingestion, and data-driven recommendations to reimagine their business strategy.
- Mergers and Acquisitions: With mergers and acquisitions, businesses aim to enable synergies by integrating primary business functions and optimizing processes to create more value. However, migration and integration of business applications might make a massive undertaking for the IT team. Organizations using traditional data management approaches struggle to control the integration process efficiently. To ensure the commercial viability of such decisions, IT must develop and implement a structured integration process and employ flexible techniques such as data warehousing to seamlessly aggregate and organize data for enhancing the value of such strategic decisions.
- Technical Debt: Integrating complex divested systems and unsuccessful data migration create technical debt. An ineffective data management process across complex enterprise applications may require additional efforts if not evaluated correctly. However, warehousing solutions can rescue organizations from incurring technical debt by minimizing the efforts needed.