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Building Data Centric Culture

In today’s world, lot of businesses are leveraging data to gain advantage over their competitors. At the same time there are even more companies who are struggling to get their digitalisation story right. A primary reason for this struggle is lacking a culture of data-centricity. Data is the most valuable asset of a company as it helps them generate insights. Building a data centric culture means replacing gut feeling with data-derived facts. Decision makers are often required to generate ideas and formulate strategies. So, this means they need to understand the data and make sense of the culture that exists around the data. In this blog we will delve into what is data centric culture and how can organizations build a data centric culture.

Defining data centric culture

An organisation is said to be data centric if data is pushed into the centre of all decision-making processes in all departments, as opposed to few isolated use cases. This can be achieved if all the employees have a deep appreciation for data, all employees use data widely, and there is all-round collaboration between employees and departments in sharing of data.

To arrive at this destination, organizations will have to engender massive behavioural changes at large scale. There are two prerequisites for starting this shift – providing access to quality data and improving overall data literacy. Continuously improving the quality of data and making it accessible to all employees empowers them and plays a central role in building a data centric culture. But this alone cannot meet the desired business objective if the employees lack knowledge of extracting insights from the data. For this it is important that organization modify their processes as well create forums which encourages all to interpret data and constantly evolve their understanding.

Benefits of data centric culture

As organizations provide centralised access to high quality data and train employees to interpret data accurately, it gradually starts replacing guesswork with informed decision making. It also sharpens the focus of business strategy and makes it more goal oriented. Additional benefits that can accrue from a data-centric culture are as follows:

Improve collaboration

As the access to quality data becomes easy it automatically leads to sharing of reports and information across the organization. With deepening of understanding of data there is widespread co-ownership of business goals, processes, and metrics. All these leads to greater transparency and cross-team collaboration in the decision-making process.

Optimise spending

With increased usage of data, the inefficiencies within the processes will start bubbling up eventually leading to reducing the cost. Teams would also be able to establish causality between spending and results. This helps in two ways: doubling down on investments that yields better results, and eliminating arbitrary cost cutting that affects morale negatively.

Aligning offering to customers

As data centricity prevails in the organization it will compel marketing to become more scientific and transparent. They will start focusing on tracking customer’s journey, their interests, and their consumption patterns. Analysis of all these data will lead to pinpointing of customer preferences, understanding the customer expectations and thereby providing better services and products.

Develop new business model

With the democratisation of data and widespread usage of analytics, the R&D and product teams would be able to uncover hidden opportunities and foresee future trends. They can also quickly detect changing consumer behaviour, listen to new customer needs, and discover emerging use cases for other customer segments. All these lead to products and services innovation paving the way to new revenue streams.

Maximising growth

Data analytics plays a significant role in comparing performance amongst teams, departments and regions. Such comparison can help identify internal problems, opportunities, and on digging deeper eventually lead to the root cause of under or over performance. Based on the root cause analysis, organizations can develop pinpointed sales and marketing strategy that can improve performance, increase efficiency, and ultimately boost revenue.

Obstacles to data centric culture

A very interesting and pertinent question is why some companies can derive insights from their data and use it successfully for gaining competitive advantage, while others struggle and fail to meaningfully leverage their data. It is not as if those companies, who fail to leverage data, has shortage of usable data in the organization. Then what are the barriers for these organizations to move beyond data collection. Enumerated below are some of these obstacles:

Centralised data gatekeeper

If there a single department which oversees managing all the data and reporting, then it does not lead to widespread understanding of data. Naturally, it prevents people across the team to collaborate on reports, goals, processes, and metrics. Such data access bottlenecks are the major inhibitor of building a data centric culture.

Ignorance of business users

When business users lack understanding for maximizing data usage, to drive the business forward, they will not justify investments in data and data management projects. The consequence of this is a prevailing sense of apathy or hesitation for data all around.

Difficulty in accessing data

If it is challenging for employees to access quality data with ease then they will not be motivated to use data on a day-to-day basis, streamline data analysis and reporting and making all data-based insights actionable.

Existence of data security concerns

If some teams and groups within the organization are concerned that sharing of data would lead to compliance violations and security breaches, then they will hesitate to collaborate with other teams using the data that they produce.

Striving towards a data centric culture

Building a culture is complex and hard work. It requires changing the behaviour of people and that means consistent and transparent communication, layers and layers of training and thrust at multiple levels. It also involves modifying internal processes and practices, adopting new tools, acquiring new skills and following new approaches. All these demands a proper strategy, investments, and time commitment. So, building a data centric culture is not possible without serious commitment from Top management of the organization. Here are a few points for consideration:

Spearhead the efforts

Organization leaders must lead from the front and cultivate the habit of making decision based on data consistently. They must also routinely demonstrate that all ideas, suggestions, and input backed by data are promoted and those without factual basis will not be carried forward. This will inspire others to copy the behaviour, align with management and gradually put it into their day-to-day practice.

Blur departmental boundaries

Management should initiate projects that requires cross team involvement and cross pollination of insights. All the experimentation with data and ideas must be encouraged as must be connecting starting hypothesis with observed results. The departmental boundaries can be made porous to allow for co-owning of goals, processes, and metrics. Only with such high cross-team collaborations, the culture of data curiosity and turning insights into actions will be spread widely.

Start small and build gradually

Building a data centric culture is a paradigm shift and requires changes of large magnitude. If you start this shift with very ambitious project, requiring large investments and longer execution cycles, then the chances of it succeeding reduces drastically. It is prudent to start with small initiatives where it is easy to demonstrate the impact of leveraging data insights. As the quick wins starts accumulating it will give confidence to wider section of people to adopt data in their daily activities. This in turn will help progressively execute more complex projects and initiatives using data-based insights and decisions, thereby gradually developing the data centric culture.

Make measurement and tracking central

The strategic significance of data analytics can be best realised when following activities are institutionalised within the organization: clear focus on business outcomes that matters, well defined metrics that best measures these outcomes, the current state of these metrics, the target state of the metrics desired, linking of organization initiatives to metrics and estimation of likely impact by initiatives, measurement of actual contribution versus estimation for each initiative.

Focus on end user experience

The need for data insights must emerge bottoms up for successful adoption across the organisation. All the dashboard and reports must consider the needs, preferences and frustrations of end users. Also, careful attention needs to be given to the usefulness and usability of reports. The end user experience is of paramount importance in driving the data centric culture.

Experiment before taking actions

Push strongly to precede all major organization initiatives with experimentation. This way teams can adopt a ‘test and learn’ approach where data analysis can be used as a tool for eliminating uncertainty and for making informed decisions. As experimentation is widely adopted across organizations it will usher in data centric culture automatically.

Work on increasing data literacy

Organisations need to plan to invest in trainings for increasing the awareness of data access and improving the understanding of data. This is a better strategy compared to hiring data specialists who will drive informed decision making centrally. As more and more people get comfortable with interpretation of data and have top of mind recall of key insights, they are likely to use it more and more in their daily activities. It will also spur intra team and inter team collaboration of actionable insights.

Build awareness for data security and compliance

Organizations should also invest in training which helps build awareness of security and compliance requirements at every step. This approach is more effective rather than having gatekeepers who spend all time telling people that they are doing things wrong. When security and compliance teams can create accountability into individual processes, they deliver immense value and help flourish a data centric culture.

Conclusion

Now you have developed a basic approach for building a data centric culture within your organization. Hopefully, armed with this knowledge you will perhaps be able to streamline your data reporting and ensure that data is at forefront of all decision-making. Please contact IOO Labs team if you need further help with data analysis or data reporting. Our team has deep expertise in using Power BI to extract actionable insight from data.

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