The blueprint for setting up a data-first organization

In today's data-dominated business landscape, analytics has acquired a critical position across industries—yet, the global BI and data analytics adoption rate remains at 26%. This may be because the journey to becoming a fully data-driven organization can often be riddled with challenges.

In this article, we address these roadblocks with strategies and best practices that can transform business data culture through seamless BI adoption. Read on and empower your organization to thrive in this data-driven era.

Stages of analytics maturity

Analytics maturity refers to the level of proficiency a business has in leveraging data to arrive at decisions and driving business outcomes. While there's no hard and fast rule to defining these stages, we've identified three analytics maturity stages based on key parameters—the exploratory, democratized, and transformational stages.

Exploratory?

In the exploratory stage, organizations are at an early phase of grasping data concepts and embracing BI. Here, the main focus is to assess BI tools that suit specific business needs. After implementation, leadership plays a pivotal role in fostering data literacy across the organization, as possessing the right BI tools is futile without the ability to comprehend data effectively. Enhancing data literacy can be achieved through workshops and training programs!

Businesses at this stage of BI adoption often deal with the challenge of data silos, that hinders the integration of data from different sources for analysis. To overcome this issue, modern BI platforms offer robust data blending capabilities that facilitate holistic data insights by allowing users to analyze interconnected data in single visualizations.

As seen in the screenshot below, a consolidated dashboard provides comprehensive insights into the business by integrating data from various business applications.

Democratized?

Businesses in the democratized stage have the right BI tools in place, but the primary hurdle lies in encouraging widespread usage. To set up a data-first organization, employees at all levels must be enabled with the necessary skills to leverage data in their daily operations for optimal decision-making. For this, the leadership can facilitate data-centric events that discuss key data topics and best practices. Establishing feedback loops and recognizing good work are other ways of encouraging the workforce to adopt BI.

A primary reason for data and analytics to lie at the mercy of IT teams for so long was the amount of technical expertise it demanded. For this reason, BI platforms today aim to simplify analytics to enable people with even minimal tech know-how to perform analysis. Automation, advanced analytics, and AI-powered capabilities are flooding the BI market, making analytics more accessible than ever before!

Watch our complete webinar on The blueprint to setting up a data-first organization, as we delve deeper on how to improve analytics maturity and leverage automation and AI-powered capabilities offered in BI platforms.

Transformational?

Organizations in the transformational stage are in an auto-pilot mode when it comes to analyzing data. The question here is, "How do they sustain these data and analytics practices over time?"

Analytics procedures have an end of life. As businesses grow and priorities change, it's crucial to re-evaluate these procedures periodically. It can also be helpful to revisit training as this will allow users to resolve doubts, share experiences and learn about new developments in the field.

That said, BI and analytics is an ever-evolving industry with new and improved analytical capabilities constantly setting the trend. For this reason, it's key to keep a close tab on the new updates in your BI application to ensure your business is making the best use of the functionalities provided.

Currently, predictive and prescriptive analytical capabilities are penetrating the market as they go beyond offering holistic insights to supporting in the user's decision-making process. In the screenshot below, we explore prescriptive analytics, where the system recommends actions to make optimal decisions.

Conclusion

You can find your organization in any of these stages of analytics maturity. Ultimately, the aim is to move from the exploratory stage to the transformational stage—which can be geared using best practices discussed in this blog. A high level of analytics maturity and BI implementation in an organization can result in strategic decision-making, proactive planning, risk mitigation, and increased revenue. Watch our complete webinar on The blueprint to setting up a data-first organization to learn more.

You can also sign up for Zoho Analytics today, or schedule a free personalized demo with one of our experts.