Data has become a commodity of the masses, encurtaining all aspects of our lives. All successful businesses, public or private, are now tracking their generated data to keep their input and output in checking and monitoring their performances. In their efforts, they turn to data scientists, those experts in data analysis and management, to handle their data-based needs.
More recently, isolated data analysis and project-based interpretation and collection of data have almost become extinct, and instead a culture of data that encompasses all aspects, has emerged. The real challenge here is for companies and businesses to move towards a future where all decisions and policies are implemented in consideration of this data-driven culture.
Definition of Data-driven culture: what is it?
Data culture is in practice, the pivoting of decision-making processes in a company from the traditional model of management, and towards a system of data-aware decision-making. Traditionally, managers and directors make such decisions based on their insight and work experience, and while this method has proven to be successful in most cases, it leaves a lot to chance. On the other hand, a data-driven culture of management takes into account existing data from previous efforts, to ensure that the policies in question will bear the results that are in the best interests of the company.
The data used to cultivate such a system comprises a wide variety of factors, including economic parameters of the company’s performance, in addition to the broader market and even some seemingly unrelated aspects, like political and social events, and the overall status of the workforce. This method, however, is not only suitable for commercial uses; it can also be implemented in areas such as urban planning and others that could benefit from objective data analysis.
The creation of a successful data culture is dependent on how data is handled in a business. In other words, real results can only be achieved through the participation of all the personnel involved in the process of generating data.
The main objective of a successful data culture plan is encouraging the employees to share their data and create a rich dataset that will enhance decision-making in the company.
Achieving this goal means you will have a working framework to actively share data between employees, data analysts, and strategists in all layers of the company. Armed with this system, you will be able to try out different strategies for your business and figure out the impacts of your decisions across different units in the company.
Why a data-driven culture matters
Collecting data is only the first step in utilizing data for your business. However, more data does not necessarily mean better performance in data analysis, so in a data-driven culture, generating meaningful data that can help provide insight into how your business is performing is the main aim.
Promotes efficient decision-making across your company:
The reliability of data is what brings efficiency to a decision-making system that benefits from the data-driven culture. The interpretation of this data and figuring out what part of the collected data can be analyzed for a breakthrough in a case is easier with such segmentation of data. Another occasion for which data-driven culture may provide insight is figuring out the perfect time for launching a new product or service. The trend in data will determine the best time for a launch that guarantees maximum impact for your product.
Delivers a realistic timeline of achieving your goals:
By providing an account of the progress for each section, and cross-processing the performance of each unit, a data-driven culture can identify the progress of each endeavor and its success rate. By analyzing this data, a data scientist can help predict the future of the company.
Increases communication between different departments:
By collecting all the data from different sections of the company, the accumulated data-set can be used by the various units to achieve organizational harmony. By identifying the impact of their work on other units, each section will be able to adjust its operations for maximum efficiency. This coordinated effort can only be achieved through the establishment of an all-inclusive data culture.
How do you foster a data-driven culture?
To ensure the reliability of data analysis results, all the personnel involved in generating the data must be aware of the implications of their actions in the process, so that they will know not to cause any ambiguity in the gathered data. This inclusion in the process of data analysis will also serve as a morale booster, as employees will have a tangible understanding of their growth and impact on the company. To foster a reliable data-driven culture, you can try and:
Create a data guide for your organization
This guide should contain tips and details on how data is gathered and categorized in your company, to raise awareness about the data collection process. This guide will serve as a unifying factor in creating a shared understanding of data culture in the company.
The guide should address significant sources of ambiguity in the data collection process.
Promote data awareness in your company
Data skills are one of the key requirements in many data-driven companies. It doesn’t mean your workforce should consist entirely of data scientists, but a background knowledge of data analysis will certainly improve the positive impacts of data-driven decision-making.
Once you have a clear understanding of the level of data skills in your employees, you can hand out literature or hold a meeting to improve their understanding of data science and its role in decision making.
Utilize the data to gain customer insight
The trends of the market and popular demand are dynamic and unstable at first glance. But using data science to analyze the patterns of consumption and customer behavior can help you gain customer insight, which is the sharpest edge in today’s competitive market. This insight helps you realize the impact of your decisions on customer experience, thus giving you the ability to improve their experience over time.
Data-driven culture statistics
Data-driven decision-making has proven its benefits for many businesses worldwide, and all successful large-scale companies implement the results of data analysis in their decision-making process. MIT researchers have found that companies with a keen focus on developing a data-driven culture have enjoyed an increase of five to six percent in their output. For a large-scale fortune 1000 company, this seemingly small amount would mean millions in revenue.
Data-driven companies
Achieving a completely data-driven culture in your business can be challenging at first, but the results are guaranteed to be a return on your efforts and investment. Through data analysis, you will have a better idea about the impact of your business plans and marketing campaigns, which means you can use the insight to improve existing plans and use the experience in developing future campaigns. Advertising is never cheap, so you can make sure your advertising campaigns are delivering the results you are paying for by reviewing the data-driven statistics.
A successful example of data-driven companies is Netflix, which has used data analytics to create user-oriented advertising that analyzes past choices by the users to predict their soon-to-be favorite movies and series. Through their huge user base, they have been able to collect data from 100 million users, which gives them incredible insight into the market.
What is a data-driven culture DATOM?
DATOM is a software application that analyzes the overall performance of data analytics solutions and techniques which are used by a company. It diagnoses the efficiency of data collection and identifies discrepancies in data-driven solutions.
DATOM provides:
- Simple operating models: a holistic approach to achieving the goals through parameters defined by data collection. In other words, it makes sure that your business plans are all in line to achieve a single goal, and prevents conflicts of interest among endeavors.
- Governance models: a proposed model of governance in data systems, which is aimed at increasing data efficiency.
- Future-ready frameworks: it predicts the outcomes of applied business models, to ensure data maturity for future operations. This Strategy helps companies prepare for upcoming challenges.
Data is inevitable, so start developing a data culture
Data analysis isn’t just for digital platforms and websites; it can be utilized to improve the operational model of any companies or businesses. Have you been experiencing a decline in your business despite maintaining the same customer base? Tracking the performance of your business is much easier if you’ve invested in creating a rich and mature data culture in your operations. This means all endeavors are accounted for because transparency is one of the key elements in creating an efficient workplace.
The power of information in today’s confusing and seemingly incoherent world has never been more clear. A data-driven business with a mature data culture provides an efficient flow of information that can be used to make informed decisions that can shape the future of your company. By implementing this system of data culture cultivation, you can find the best path forward for your company.