Wednesday, June 29, 2022

How businesses can benefit from a data-driven culture

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Shreya Christinahttps://cafe-madrid.com
Shreya has been with cafe-madrid.com for 3 years, writing copy for client websites, blog posts, EDMs and other mediums to engage readers and encourage action. By collaborating with clients, our SEO manager and the wider cafe-madrid.com team, Shreya seeks to understand an audience before creating memorable, persuasive copy.

CEO of Intellectual soft, the technology partner of Fortune 500 organizations.

Experts at the McKinsey Global Institute have said that modern data-driven organizations: 23 times more likely to attract new customers than those who fail. How do you convert all those gigantic amounts of raw data into actionable insights and create a strong basis for decision-making? An equally good data-driven company culture could be the right choice.

Business leaders and executives have a vast amount of information at their fingertips that can drive future-proof, data-driven innovation: better customer satisfaction, refined action plans, and streamlined operations. But with the more than two-thirds of the data collected going unused each year, such ambitious goals are simply elusive for most companies, meaning there is no such thing as a lack of data. Instead, there is a need to create a corporate culture that encourages new initiatives, practices, and habits to embed decisions into data across the business.

Five steps to a data-driven corporate culture

Step One: Bringing in a Single Source of Truth

While it may be a hefty investment, most companies strive for more precision because they simply can’t afford to grope in the dark. Entering a single source of truth that covers all of your systems, departments, and teams is perhaps the most critical step in paving the way for your new data-driven culture. Based on my own experience in this field, I can reasonably conclude that: (1) a well-thought-out set of onboarding rules, (2) standard procedures, or (3) a unified and comprehensive knowledge base for each of your projects are all pretty good ways to get started at that time.

Step Two: Refine Default Data Dictionary

To stay informed, all employees of your company, not just data specialists and executives, need a unified glossary and well-thought-out definitions. That is why refining a standard data dictionary, making it clear, concise and agreed upon, would be the next critical thing to be done just after a single source of truth has been chosen.

Step Three: Support Wider Data Access and Use

Business owners and C-suite executives need a maximum, accurate, global view of business performance. Broader access to data and, more importantly, its broad day-to-day adoption across the business requires at least one common self-service reporting system with varying levels of access and rules-based task flows built across specific performance goals, departments, or operations. After all, everyone likes nicely structured data, for example when a customer can easily follow the current progress to date via interactive dashboards or chatbots. The same goes for your team, keeping everyone involved and always up to date on the most important things.

Step Four: Promote Data Literacy Across the Organization

Once the company has everything in place with full access and widespread adoption of data, it’s time to double-check all departments for data literacy and understanding. Ultimately, engaging more employees through iterative courses and training can significantly improve the efficiency of data-driven applications. In addition, I must emphasize that Intellectsoft has repeatedly faced similar challenges. From our experience, another good way to ensure data literacy without investing too much time and effort is to promote weekly digests and highlights. For example, by delivering industry-specific information via email digests or weekly newsletters, you can broadcast it internally or for your high-profile clients.

Step Five: Experiment with Data, Test and Learn

To explain analytical choices based on rock-solid statistics, you need to make proofs of concept simple and robust. By doing so, the risk of poor decision making can be minimized, in line with forcing analysts to grapple with potential uncertainties in A/B testing (i.e., whether there are too few samples, or whether the data is reliable). for certain models, e.g. emerging competitive dynamics).

Benefits of data-driven decision making for your business

Data-driven decision-making can provide a range of significant and immediate benefits to most businesses across a variety of industries. Here’s a list of the benefits of data-driven decisions when you embed them in data:

• Sustainable improvement: It drives continuous improvement across the organization by making it much easier to implement best practices and courses or actions with verifiable results based on past performance.

• Faster decisions: This optimizes the average time spent coming up with objective solutions and highly accurate expectations. In addition, when used appropriately, data can make experiments less risky, in line with better odds of earlier success.

• Greater transparency: Data-driven decision-making contributes to faster and, most importantly, fully visible and traceable approval processes by team members, which in turn supports a high level of compliance and accountability.

• Full market research: Data helps generate actionable market insights based on real facts and proven statistics. By eliminating guesswork and uncertainty, it becomes a good complement to extensive market research and winning business initiatives that may not have been available until now.

• Optimized spend: The money-saving potential of data-driven decisions should never be underestimated, as it can quickly increase operational efficiency, in line with providing a solid background for cost-effective strategies and keeping the best of them in the long run.

• Organizational consistency: This helps each member to deeply understand how it is better to root data in decisions, highlighting best practices and actionable scenarios that can be unified and popularized across different work areas and departments. Ultimately, making decisions in a data-driven manner can become the habit, significantly improving service consistency and engagement across the business.

Summarized

The main obstacle to making business decisions truly data-driven is not technical. The problems are of a cultural nature, as it is not a problem to involve data and technology in a decision-making process when necessary. Making this course normal, almost on autopilot, for employees – it’s a mindset shift. And it is a challenge that every modern company faces.


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