Data-driven organizations know how to leverage their data as a strategic asset to optimize business processes, improve decision making, enhance the customer experience and increase revenue. But leveraging these assets is about far more than just managing data, it’s about building a culture committed to maximizing data value, where stakeholders are engaged and business users are empowered to seek out data to augment business strategies and objectives.
A comprehensive data management strategy should include a foundation of data governance and metadata management to promote data understanding, accessibility, usability, and utilization. The underlying culture that makes such a strategy successful requires a partnership between business and IT, accountability among data owners and stewards, and cooperation and collaboration across an enterprise to gather and maintain critical information such as conceptual metadata. All of this should enable business users to easily locate and apply data to business problems, turning that raw data into actionable insights.
However, building this culture and becoming a data-driven organization doesn’t happen overnight. There are many steps business leaders must take to implement metadata management. In my previous blog, we focused on the building blocks of metadata management. In this blog, we’ll examine how organizations can cultivate a data-driven culture.
Solid data management must begin with the right tools, but it is the combination of technology, people and processes that enable enterprise-level excellence. The world’s finest hammer may as well be a paperweight without a skilled craftsman to wield it, which is why data management success starts with the right team.
As anyone who has tried to implement a data management solution will tell you, without executive buy-in and budget, the project is dead in the water. Senior management needs to understand and promote the value of data assets and the importance building a data-driven culture, and demonstrate that commitment as a data management team is built. Leadership needs to hire the right expert who can evangelize and oversee the data strategy for the entire enterprise. Many organizations today tap a Chief Data Officer (CDO), while others leverage data consultants to act as a de facto CDO.
Immediately under the CDO should be a senior director to act as the head of enterprise adoption. Their responsibilities include integration, adoption and compliance for new data policies, standards, analytical methods, and various capabilities recommended by the CDO. Success in this position requires extensive experience in change management, and a deep understanding of technology development lifecycles.
Next, organizations should enlist a technically savvy senior manager to take on the role of data engineering manager. This role is responsible for leading teams that build high performance, scalable data solutions to meet the needs of data creators, managers and consumers. This person may also manage the data platform and work with a variety of teams and individuals, including product engineers, product managers, designers, analysts and data scientists to understand their data supply chain needs and develop innovative solutions for data ingestion, preparation and delivery.
To round out the team is the data evangelist. This position can be filled by a data analyst experienced in publicizing and energizing the work of others. This job is essential in driving data knowledge participation to discuss, organize and define data from diverging lines of business. There are a variety of approaches the data evangelist can take, but the main goal is to spread broad data knowledge and encourage participation from and collaboration among different departments.
Among the data team, the data evangelist is essential to creating a data-driven organization, because they are likely spear-heading organizational efforts to gather conceptual metadata. The data evangelist, or their designated team members, is tasked with gathering that data which resides within the minds of employees across varied departments and lines of business. To gather this conceptual metadata across business functions, they must interview subject matter experts and work cross-functionally with various business and technology teams.
There are, however, many barriers to gathering this knowledge. First, there is simply a matter of logistics. Gathering experts from various departments together in the same room at the same time, in order to share their expertise, is no simple task. Then there is the general level of skepticism that comes with the introduction of any new process or technology. There will be change averse employees, and those who doubt the efficacy of the new procedures. It can take time to create converts among employees. Lastly, there are those employees who feel threatened by shared knowledge. They guard the knowledge they have as a sort of shield protecting them and their position. These employees will not readily give up what they perceive as a source of their power.
However, knowing these obstacles exist is the first step to overcoming them. The data team needs to find innovative ways to engage users and encourage their involvement. One approach a data evangelist may utilize to motivate participation is by implementing an internal marketing campaign to get people excited about data and gain their buy-in. For example, the data evangelist can craft various marketing materials to connect people with data insights to show how data specifically benefits their team. They can also take a more entertaining approach and use “gamification” or competitions to increase participation and interest, or train the team using real-world examples to demonstrate how data knowledge is relevant to their work.
If internal marketing doesn’t do the trick, data evangelists can work with the human resources (HR) department to further engage employees. HR can provide special recognition for data engagement, like acknowledgements on ID tags and email signatures, prestige giveaways, or exclusive perks like time off, bonuses, free lunches, etc. to help spur participation.
In a data-driven culture where participation is encouraged, rewarded and respected, teams are more likely to take an active role in data analysis to make to smarter business decisions, enhance strategies and fine-tune objectives to gain a competitive advantage and increase revenue.
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