When “Moneyball” was first released in 2011, it revealed the secrets to the success of the unfancied Oakland Athletics baseball team’s 20 game winning streak in 2002. The secret was the emergence of sports science and a focus on deep data analysis. Much like Warren Buffett’s famous value-based investment model, the Athletics looked out for undervalued players and brought them together to form a winning team.
While this may seem obvious, the emphasis on data to truly understand performance is more complex than it looks. Sport is a good example of where reputation can precede cold, hard facts. The Oakland Athletics were unfancied because it let star players leave, only to be replaced by relative unknowns. As it turned out, the unknowns comfortably outperformed the stars.
That is the value of data management.
The lessons from Buffett and Moneyball can be applied to the world of business. With a robust data strategy in place, companies can optimize performance, integrate multiple systems, and be ready for the digital age. Clean data supported by a strong management strategy can take API functions to the next level.
Data Management Strategy
Simply put, a data management strategy is a company’s roadmap to using data efficiently to achieve its objectives. As technology and 5G networks continue to evolve, the value of data increases daily. With a well-thought-out and coherent strategy in place, businesses can avoid the following pitfalls:
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Bad Data: This is a term that applies to duplicate, incompatible, or missing data from various sources. Bad data can distort the true picture of a company’s performance and hinder business operations.
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Lack of Real-Time Visibility: Poor quality data hinders the company’s ability to manage operations in real-time.
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Waste of Resources: Without a data strategy, teams can be distracted by unnecessary and unproductive tasks relating to admin and data management.
The purpose of a data management strategy is to maximize efficiency, automate processes, increase accuracy. By minimizing the risk of error and the resources it uses, data can become an indispensable asset that drives a business towards digital transformation.
In order to develop a winning data management strategy, a business should take the following steps:
1. Identify the Business Objectives:
The first step is to identify the objectives of the business - both in the short and long-term. In doing so, teams will be able to focus the strategy on a specific set of data that’s relevant to company performance. This step can be broken down into three parts:
- Identify the overall objectives of the business
- What data apply to those objectives
- How to track and monitor progress against those objectives
Answering those three key questions will help businesses focus on a few key metrics, leading to a focused and honed strategy.
2. Outline (and Automate) Data Processes
Once the objectives are defined and set, it will then be time to review the data processes. This involves the collection, preparation, storage, and distribution of data. As a starting point, it’s essential to have a hub where all the data is brought together into one platform for users to access.
Using a data management tool like DiCentral’s EDI integration solution will enable teams to manage the data and set up automated processes. The idea is to minimize human input, freeing employees up to focus on more productive tasks and reduce the risk of error.
Other elements include the formatting of the data, integrating data flows, and balancing access with security. By building the infrastructure and organizing the data, companies will be well-placed to undergo digital transformation. Invoicing times at digitized businesses, for example, have been cut by an average of 50% compared to old-paper-based processes.
3. Data Governance
This is an aspect that has both ethical and business considerations. The ethical side centers on data privacy and ensuring private information from customers, and other stakeholders do not leak out. In 2019 alone, there were nearly 8 billion data records exposed, illustrating the importance of data security. Countries and international organizations have taken action over the past decade to protect personal privacy. The EU’s GDPR is a leading example.
On the commercial side, it pays to have proper data governance:
- It protects the quality of data, leading to more accurate analysis and streamlined operations.
- It reduces the risk of data theft, including valuable intellectual property.
- It helps to avert costly legal action in the event of personal privacy being compromised.
Having complete data governance also fosters consistency in the handling of data across the organization. By ensuring all employees and stakeholders handle the data with sensitivity, the company as a whole will be able to strike a balance between data security and access.
4. Training and Implementation
To maximize the implementation of the data strategy, it’s critical to ensure sufficient training for teams. This can be done using a number of methods, including workshops, webinars, and the onboarding process for new hires. Having a cohesive understanding of data and the relevant KPIs gives teams a clear sense of direction. It could be more effective for some companies to leave the core data management in the IT team’s hands, where any issues can be quickly resolved.
However, a company-wide buy-in of the data strategy will be pivotal to its success because it’s not only about the quality of data but how it is used.
Data Management Leads to Smooth APIs
One of the key benefits of an efficient and well-managed data strategy is it increases APIs’ ability. As we’ve said in the past, APIs are like the engines of businesses, with data being the fuel that drives them. Before being usable for cars, oil needs to go through a refining process to become premium gasoline for it to function.
Data should be viewed in the same way.
For APIs, having accurate, clean data will lead to smoother integrations and more efficient processes. With the ability to see reliable information in real-time, companies can continually monitor performance and refine strategies. After a potentially disruptive period of setting up, data management can prove to be the pathway to digital maturity and future-proof businesses.
In one sense, data should be seen as the fuel of the future.
