In order to glean useful and actionable insights from organizational data, companies must have a structured data strategy and ensure that a culture of data is imbibed across the organization. However, changing a company’s culture is one of the most challenging parts of any data and analytics initiative, making it difficult to create a data-driven enterprise. In fact, according to the NewVantage Partners’ 2019 Big Data and AI Executive Survey, (which comprised of 64 C-level technology and business executives representing very large corporations), 72 percent of the organizations are yet to forge a data culture. 69 percent of the participants also reported that they are yet to create a data-driven organization.
A culture of data in the organization can only be brought about with prompt decision-making strategies and good directional leadership to drive the initiative.
Adopting a ‘Culture’ of Analytics
A culture of data in the organization extends beyond just having a team of data scientists. What it needs, instead, is a shared mentality across the company that recognizes the importance of data in business. A culture of analytics should ideally include an investment in the right infrastructure, technology and training that will help all business users harness insights to make better-informed business decisions.
When the ‘culture of analytics’ is established in a company, data and insights must become available across the entire organization, without business users having to wait for analysis or reports by the data science team. With insights readily available to all, making business decisions based on these insights, becomes second-nature to all business users.
Historically too, it has been observed that companies that use reliable data-driven analytics as a culture, see a steady rise in business growth. Their productivity and profitability rates are about 5 to 6 percent higher than their peers that fail to do so. According to a study by McKinsey, organizations see a six percent increase in profits in the first year when using data-driven analytics, which grows to nine percent after five years. According to the Harvard Business Review, data-driven decision-making practices are on the rise. The global big data market which is currently evaluated at $1.7 billion is predicted to swell to $9.4 billion by 2020.
Develop a Data-Focused Workforce in the Organization
According to an IDG survey report, 75 percent of business enterprises today are undertaking big data projects. But while data on its own is not useful to business, leveraging it effectively in order to gain strategic, actionable insights is what will deliver ROI. As data becomes increasingly important, companies are realizing the need to hire data-focused talent. Organizations today are adding new roles such as the Chief Data Officer (CDO) or Chief Analytics Officer (CAO), positions that were simply unheard of a decade ago.
Apart from hiring for data-oriented roles, companies must invest time, money and other resources in training the existing workforce to efficiently use technology to harness the power of data. It is also imperative that we hire data-focused individuals in roles that are stereotypically ‘not data-oriented.’
Some examples are sales and marketing positions that are not really associated with data. However, having data-oriented individuals in these roles ensures that the data strategies established by the C-level and data officers, are understood and aligned to their respective functions.
Many organizations today are also building data-focused teams that are a combination of C-level business leaders, data scientists, data officers and data architects to act as a governing body for all data-related initiatives. This initiates a global shift towards a culture of data in the company, impacting the overall future of your business. Hence, when establishing the importance of having a data-focused workforce, the HR team must be involved in the discussion so that they bring in talent that is aligned to these business requirements.
Many organizations today are also building data-focused teams that are a combination of C-level business leaders, data scientists, data officers and data architects to act as a governing body for all data-related initiatives. This initiates a global shift towards a culture of data in the company, impacting the overall future of your business. Hence, when establishing the importance of having a data-focused workforce, the HR team must be involved in the discussion so that they bring in talent that is aligned to these business requirements.
Build a Communication Channel
Although most enterprises have data-driven roles and specific teams assigned for establishing a culture of data in the organization, a major hurdle for them is effectively communicating the value of data and its effective use to all business users across the organization. The primary role of the CDO or CAO is to ensure that everyone in the company understands the company’s data policies, is thinking of data in the same way and using a common vocabulary to discuss it.
Eliminating Silos
When it comes to using data to your advantage, the culture of working in silos should be eliminated. While data officers and business managers may have a vision for leveraging data to aid business growth and solve business problems, they do not have the expertise to mine or analyze the data to glean actionable insights from it.
On the other hand, data scientists will not have any idea on what the organization’s vision is with respect to data. One way to eliminate this disconnect is to establish a communication channel between the two entities so as to maximize data-driven ROI. In order to understand how to get a positive outcome from all data initiatives, companies must have targeted business leadership training with an emphasis on effective communication between all data stakeholders.
Data Articulation
Employees must also be trained to effectively communicate their data-focused ideas to the company’s business leaders and other functions in the right terms and definitions. The act of using the right vocabulary to discuss data is known as ‘Data Articulation’, which is an important aspect of data communication. As an example, imagine someone from operations trying to discuss data strategies with a sales executive.
While both these people may have expertise in their respective fields, the terminology and definitions they use for similar concepts may be vastly different. Establishing a common vocabulary for data communication helps employees across the organization articulate their views on data better, making data actionable based on the business objectives and market realities.
Building an Efficient Network of Teams
Just as it is important to hire data-focused resources to enable a culture of data in the company, it is crucial that companies rethink the hierarchical structure of their traditional business operations. With a shared data-driven mentality across the organization, companies must build a flexible business model that is supported by a network of balanced teams, empowered leaders and decision-makers. By deviating from the hierarchical business structure, companies will have smaller, more flexible teams that are easier to work with.
While each team in the network can specialize in varied areas of expertise, they must also be well-balanced and have a diverse mix of talented individuals who can contribute to the overall success of the team. Smaller teams tend to be better connected and hence foster effective communication and transparency in decision-making processes.
When dealing with a flexible network of teams, the company can reassign resources, form and disband teams and change job roles and titles easily and as required. High-performing teams can be studied to see what accounts for their overall success, in turn modeling the other teams in the same manner.
Boosting Accountability and Productivity
When a network of teams specialized in different areas of expertise is formed, it becomes imperative that accountability among the resources is established. In order to do so, individual goals along with team-oriented milestones must be set for the entire network in order to make every resource accountable and more productive.
Having set goals both at an individual as well as team level makes it more efficient to track performance. Processes that focus on this agile business model must be clearly understood by the business leaders and support must be extended to the teams in order to increase their efficiency levels.
Additionally, data must be democratized with multi-team access to all the data scores and warehouses. Having more teams to efficiently process data ensures that more meaningful insights are garnered from it. This shift in methodology also gives a larger workforce the hands-on experience with how data is used to drive effective business processes.
Conclusion
Data that provides strategic, actionable insights, help businesses stay one step ahead of the competition and makes them better-prepared to handle market requirements. The need of the hour is a business leadership that understands the importance of data and invests time, money and effort into building the right framework – infrastructure, talent and strategies, for a data-driven enterprise.
If you’d like to know more about how leadership can help build a culture of data and analytics, please feel free to get in touch with our BI and analytics consultants for a personalized consultation.
