DATABERG
How to become a data-driven company? (5 practices to adopt)
In 2019 data analytics is an irreplaceable tool for achieving organizational success. However, to accomplish our goals, it is not enough only to collect, store, and analyze data.
The real data-driven, measurable growth, and development come with the establishment of data-driven company culture. This type of culture actively uses data resources as a primary asset to make smart decisions and ensure future growth. What is more, utilizing data as the foundation of the corporate strategy helps to boost profit and sales, increase both employee and customer satisfaction, enhance productivity, establish a strong corporate culture and ensure efficient decision-making, planning, and risk assessment processes.
But how to actually become such a company? Well, according to Christopher S Penn, every data-driven organization passes through five evolutionary stages:
- Data resistant. The business does not use data for any purpose.
- Data-curious. The business sees an opportunity to integrate and use data to enhance the success of its operations.
- Data-aware. The business starts using data analytics for some of its operational processes.
- Data savvy. The business starts using data analytics in multiple areas of operation and across different departments. It also starts deriving data insights and uses them for decision-making.
- Data-driven. The business uses data as a primary asset for establishing strategic planning, setting objectives, and assessing future risks.
To go from stage 1 to stage 5 is a very complex process, requiring time, effort, and resources. But that should not sound discouraging.
Below, we have selected five effective practices that will help your organization to smoothly become a data-driven company.
Adopt data-governance policy
It is not enough only to collect, store, analyze, and interpret data. It is essential to ensure that the available data is trustworthy, consistent, transparent, and with high quality.
The best way to achieve this is to adopt a Data Governance policy. By doing so, we set clear guidelines on how to manage the data: from the collection process through processing to deriving insights. This way, we ensure that our data resources (including metadata) are with high quality, trustworthy, categorized properly and accessible, and can be confidently used for further organizational purposes, such as strategy building. In addition, proper data management mitigates the risk of occurring errors, as they can be identified and tackled in real-time to ensure the smooth flow of business operations.
Another positive aspect of DG that helps businesses to become data-driven is the opportunity for catalog integration. Such a catalog enables narrowing data results according to set criteria, as well as visualizing relationships and lineage between different datasets. This helps the management to have a clear picture of the data integration processes, allowing to enhance its planning, leading into more complex future-oriented decisions.
DG also helps businesses to comply with the legal rules and regulations in their country and industry of operation, and this way prevents the accumulation of any extra costs. Besides, legal compliance will make any data transactions more secure and leak-resistant.
Establish data democratization
Any data-driven company should adopt data-driven decision-making processes at all organizational levels, including departmental, team, and managerial level. To achieve this, the available data resources should be accessible to, and readable by everybody in a particular company: in other words, the business entity should establish data democratization, naturally keeping legal limitations in mind.
Such practice facilitates the planning processes, ensuring transparency in data management, limits the occurrence of any misunderstandings, eases communication, prevents any duplication of tasks, and as a result, saves time and optimizes jobs.
Another benefit is that data democratization breaks down data silos. It allows every employee and department to have access to joint data resources and make decisions based on the particular data they need. Moreover, it contributes to a better understanding of the work of the various other departments and the organization as a whole.
Choose the storage type that works for you.
How your company stores data is a crucial factor when you decide it to become a data-driven business entity. And it is essential to choose storage that best suits your company's needs. Let's compare data lakes and data warehouses to give some more clarity.
- Data lake. This is the best way to ensure data democratization, as data-sets stored in those lakes are accessible to employees of all organizational levels. One great advantage is the fact that data lakes are inexpensive because huge amounts of data are collected in its raw format and are not processed, categorized, or filtered. What is more, this type of storage allows real-time decision-making regarding the purpose of the data: it is flexible to instantly change and customize the data format to suit sudden company needs. Besides, every time when certain data set is being used, a raw copy of the same set stays in the data lake. This ensures transparency, security, and flexibility of data.
- Data warehouse. The greatest advantage of data warehouses is the fact that they store huge amounts of data in a structured, categorized, and meaningful way, and ensure its quality and consistency. The data in them already have a purpose, and no storage space is wasted for data that are not in use. On the other hand, this structure loses part of its flexibility due to its fixed structure. Additional licensing costs for database applications may also incur.
Gain business clarity from the data
Having access to vast amounts of business-related data can bring many new benefits and opportunities, including:
- Derive insights
- Identify trends and tendencies in operations and customer behavior
- Understand clients' desires and needs better
- Measure performance efficiency
- Recognize operational systematic and non-systematic errors
- Identify market gaps
- Measure employee satisfaction
Base your decision-making on data insights
Data-driven companies should use data as a primary tool for decision-making, planning, strategy building, and risk assessment processes. To achieve this, we have to make sure that all the departmental and operational units take data-driven actions, which are not only aligned across departments but also with the main organizational objective, goal, mission, and vision.
These goals can be met by providing high-quality data integration software and user-friendly tools and platforms, available to all users.
Conclusion
Data-driven companies have the potential to be the most successful companies on the market, independent of the industry of their operations. An evidence-based, data-driven strategy from all organizational levels leads to higher efficiency, continuous growth, constant product development and innovation, providing the desired competitive advantage.