The payout for a data-driven organization is an absolute delight, i.e., effective and improved decision making, proactive responses to the customer needs, and the ability to stay ahead of the competition with innovative ideas and methods. Data-driven organizations can work faster, better understand the impact of decisions, and ensure that all elements of the organization have the opportunity to suggest ideas that improve the customer-product relationship.
Exploding amounts of data can usher in a new era of fact-based innovation in companies and underpin new ideas with substantial evidence. Hoping to better satisfy customers, streamline operations, and clarify strategy, companies have collected data over the past decade, invested in technology, and paid well for analytical talent. For many companies, however, a robust and data-driven culture remains elusive, and data is rarely the universal foundation for decision-making.
Why is it so difficult?
The main obstacles to creating data-based businesses are non-technical. They are cultural. It’s easy enough to describe how data is inserted into a decision-making process. It is far more challenging to do this regularly or even automatically for employees – a change in mindset that is a daunting challenge.
Therefore, every organization must first adhere to these best practices, which are tailored to different aspects of the organization. The best practices can be implemented to any data-driven culture, even if the cloud is excluded from the conversation.
When it comes to people:
- Encouragement and empowerment to learn continuously.
- Access to data for all employees in the organization.
- Culture of collaboration
How can you incorporate data culture into business operations?
- First, make sure that every decision is supported by data.
- Strong, consistent data management
- Introduce methods that encourage top-down decision-making collaboration.
- Organization-wide knowledge of the value of data.
Integrate technologies that drive decision making with data
- Invest in self-service tools
- Scalable platforms that business units can use to provide different tools
- Complete control over the data
Being a data-driven organization means simplifying all decision-making processes. This ensures that decisions can be made automatically, quickly, and effectively measured and restored when errors occur. All processes should be broken down into individual elements and, if possible, automated. There are certain business operations where manual input is required at different stages. The key, however, is to minimize and eliminate them as soon as data is at disposal to support the decisions.
One easy way to prioritize the transformation of decision-making processes is to measure the cost of a decision. Decisions with low downtime costs or high returns should first be automated. Decisions with higher downtime costs, often including the impact on human life, should be the last to be automated until appropriate safeguards and controls are in place to avoid the risk of negative consequences.
This process of re-engineering depends on the employees who understand today’s processes and is therefore commissioned to automate these processes. Cultural habits need to be developed to encourage employees to rethink, let go of manual functions earlier, and encourage collaboration on built-in data sets to better facilitate departmental decision making.
Don’t be afraid of the cultural change
The cultural change requires new skills, both technical and soft skills so that employees can work effectively. The training should complement any external attitude in the organization. This training should focus on enabling employees with new skills to transition to a data-driven organization, but also encouraging employees to continuously improve their data usage.
To build a data-driven organization, you have to commit yourself to the maturation of people, processes, and technologies. Technology must allow that the processes are defined and carried out by people. A data-driven organization integrates data sets, provides access, and promotes the automation of discrete process elements. These organizations focus on measuring all decisions, so that