This is the latest post in a three-part series on transformational analytics for the enterprise. In case you missed reading, read the first Governance and data management that empowers your digital business, and the second day State-of-the-art analytics for quick decisions.

Data-leading organizations see benefits such as customer acquisition and retention, engaged employees, and operational efficiency. While analytics at scale promise many transformative business outcomes, most organizations struggle to build a large-scale data culture that values ​​and practices data-driven decision making. Could IT leaders be too focused on implementing technology and not enough on empowering their employees?

The massive acceleration of digital transformation has created new ways of working, and you have seen for yourself the critical impact your people can have when you empower them with reliable data. “Nearly two-thirds (64%) of organizations that were most successful in analytics projects in the past two years increased spending on data management and analytics products and services as a result of the pandemic,” 451 search reports, part of S&P Global Market Intelligence. [1]

Your employees are brilliant, creative, and hard-working – and they know exactly what questions to ask to get valuable answers that can propel your business forward. As a trusted IT partner for these team members, you can lead a thoughtful, comprehensive, and people-centred approach to the practice of enterprise-wide analytics. Leadership for success across three areas will empower your entire employee base to be more data-driven:

  1. Adopt an agile approach to managing your analytics environment
  2. Supporting employees in developing their analytical skills
  3. Foster a community that builds and celebrates your data culture

Let’s take a closer look at each of them.

1. Adopt agile implementation practices

With modern business intelligence, IT is introducing a controlled model of self-service data to everyone, rather than continuing to collect requirements and design reports. Here are some of the ways IT can help drive business to greater results through the ongoing deployment and management of an enterprise’s scalable analytics environment:

  • Accommodate growth through an agile approach to support the analytics environment: Analytics is becoming increasingly important to organizations, particularly with increasing adoption across businesses. For this reason, you should consider reassessing server usage more frequently than other technology solutions – including changing your architecture to match the evolving needs of the organization. If your analytics solution is flexible, you won’t be limited to any specific architecture, data sources, or cloud deployments. Adopt agile practices for proactive planning and monitoring; “Set it and forget it” implementation creates the risk of insufficient resources failing to support motivated data users with their increasing data workloads.
  • Help your teams take action in the context of their business processes: Embed data assets into existing employee workflows and applications by setting up email subscriptions, chat alerts, and @mentions, or include analytics where employees actually spend their time—like your internal portals and your CRM. Not only does this help people seamlessly engage with contextual analytics, right now, but it can shorten time to solve problems with automation and intuitive AI. Consider impact across your customers’ lifecycles as you help your organization’s employees ask questions about their data in natural language, get accurate answers, and increase cross-functional collaboration, ultimately helping people act when data is most relevant.
  • Ensure alignment with strategic objectives and business outcomes: If you are just starting to build a self-service analytics program, start with use cases aligned with your priority areas. Some analytics solutions, including Tableau, offer department and industry-specific dashboard templates that can be customized to your needs, rather than starting from scratch. Focusing on high priority use cases will encourage interaction with data and support your strategic goals. IT must identify and socialize success metrics based on business results to demonstrate program effectiveness as more teams adopt and develop the use of their analytics.

2. Support analytics mastery across business

Data knowledge is the ability to explore, understand, and communicate with data—key to the success of organizations with analytics for data-driven decision making. Information technology plays a strategic role in facilitating a collaborative, data-driven culture across businesses in several ways.

  • Establishing a data literacy baseline across the organization: Time and time again, customers tell us that developing employee data skills is a major challenge to effectively deploy their analytics platform. Whether it is hiring new talent or reskilling existing employees, having a basic data literacy base across the organization is critical in developing a data culture. What is important for everyone to know when using your data? How does this baseline change depending on the team, skill level, or type of data people access?
  • Centralization of support resources and learning documents: Giving employees a central place to get answers to their data-related questions, such as an internal portal or a Wiki, will reduce barriers in their journeys to become more data-dependent. This also helps ensure standard processes and quality content across the company. The repository should include relevant examples of analytics content and documented learning from your analytics initiatives so people can get up to speed quickly, as well as detailed information about avenues for assistance, collaboration, and training opportunities. Actively maintain these assets and refine practices while strengthening your data culture.
  • Develop learning paths for beginners on board and hone the deep experience of others: Whether you develop in-house training or rely on external resources and services, it is important to provide comprehensive, self-directed, or targeted training to keep users informed of the appropriate level of skill and knowledge for their roles. Then, ensure a smooth transition from basic analysis to more advanced analysis, matching appropriate technical capabilities and responsibilities with the right use cases for their functionality.

3. Strengthening the community among data users

Building an internal community gives people a space to ask questions, share best practices, and celebrate achievements – all while enjoying the data. These initiatives do not have to be large, straightforward programmes; As engagement grows, formalize it with dedicated owners, leaders, and operations.

  • Launching a software effort to build a community around data: Give people outlets for inspiration, search for answers, and learn new skills. This should include support-based programs, such as one-on-one coaching, lunch and learning, and user groups, as well as competitions that encourage creative problem-solving or collaboration across teams. Ultimately, the goal is to get people to broaden their perspective and increase their data skills through new connections.
  • Formal communication wins data to evangelize your analytics program: Don’t be afraid to sound your horn — and encourage employees to do the same. Share wins and success patterns to help create a virtuous circle that broadens and deepens engagement across your organization. Publicly identify data champions and reward them with career-improving opportunities. As your data culture evolves, consider the leadership roles of formal data.
  • Expand support for your internal users with a diverse global data community: Searching outside the walls of your organization for inspiration and answers to common problems can help accelerate your team’s skills, encourage people to find creative solutions, and ensure enduring analytical engagement. In the Tableau community, over a million data enthusiasts around the world – from analysts and academics to developers and data leaders – help each other every day to achieve personal and professional goals and personally realize the value that analytics has brought them.

Start small to succeed at scale – take the first step today

At Tableau, we work with organizations around the world that have accelerated their digital transformation by developing their data strategy. The big success factor is whether the company can effectively create a strong data culture where people are empowered to use data regardless of their skill level. Information technology plays a valuable role in empowering everyone with a reliable environment for analysis, data literacy needed to find and act on insights, and building a community that encourages and celebrates data culture.

If the process seems daunting, you can take incremental steps to build these capabilities now, knowing that the steps you take today will have a significant impact on the resilience and resilience of your business. And to help organizations everywhere, we’ve developed a proven methodology for scaling analytics and building your data culture: the Tableau chart.

Tableau Blueprint helps organizations like yours measure the maturity of their analytics. From IT strategy and business alignment to flexibility, efficiency, and community, our approach provides a formal framework for questions to consider along with step-by-step guidance. With it, you have a powerful tool at your disposal to improve the scalability of your analytics software. You can start now –Evaluate our quick planner.

[1] Source: 451 Research’s Voice of the Enterprise: Data & Analytics, Data Management & Analytics 2020

Copyright © 2021 IDG Communications, Inc.

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