"In the end, you should only measure and look at the numbers that drive action; meaning that the data tells you what you should do next. "
Every industry uses its data to make better business decisions. However, what sets apart the most successful ones is the ability to manage the data as an asset across the respective enterprise. This ability comes from a strong technical foundation, strategies to govern the data handling process, and accountability to manage the data. These factors are very important for businesses to generate value, meet objectives and gain a competitive advantage.
The Mindset of a Data Leader
In 2017, Big Data Executive Survey, 41.4 percent of executives believed that Chief Data Officer (CDO) should manage and leverage data as an enterprise business asset. There are many organizations, however, that have failed to invest in resources necessary to realize the data’s inherent value. It is easy to become overwhelmed by the challenge of turning data from a record into a core facet of business operations. Organizations may feel doomed by not knowing where to begin with. CDOs can take comfort knowing that the process will take time and change won’t happen overnight.
To unfold the value of an organization’s data, a CDO must implement a clear strategy. The best strategies must be tailored as per the needs of the enterprise and should help the CDO to engage stakeholders, plan for the future, implement projects and drive the business to success.
Traditional Vs Modern
In a data-driven era, it’s not just about the data and information; it’s also about getting access to it. This could help an organization to build new business models, to get the right information, do data-driven marketing, and so on. It’s all in the collection and the correlation of data. Let’s delve into an example.
Traditionally, data models and databases were used to determine profitability. The historical figures, cost, production, break-even point, etc would tell us if the company could survive or fall. Today we have the IoT (Internet of Things) that has a lot of data on actual productivity like output, maintenance status, etc. Predictive analysis can be done by looking at the competitors and all this correlation can give us a better picture of the profitability of a business and influence our decision making.
How to Treat Data as an Asset
Here is a step by step process that companies can employ to manage their data efficiently.
Clean your system of any unwanted data. Question your intentions. What you have, why you have, and what’s your need. You must do the housekeeping to maintain your data. Regulate the data and clean up what you don’t need. Resources should be spent to clean, store, protect and secure vital information.
2. Exercise Control
Once you know what you should keep, you need to understand precisely what you have kept and where: in data centers on laptops, mobile devices, or with cloud providers. The next thing to figure out is who’s accessing your data and why. You must know how your data is being treated.
3. Give it the right place
When it comes to storing data, make sure that you are storing them in a safe place such as the data home. Also, keep a focus on your data strategy methods so they can be easily found or recovered.
4. Put it to Use
You have done everything to make the data readily available to you. Now, make sure to use it and gain value from it. The ability to apply data analytics, artificial intelligence, machine learning, and big data techniques to your data can help you understand it better and create opportunities with it.
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The Time for a Change
It is important to understand that data is an intangible business asset. It is the fuel that powers multiple use cases or opportunities that the business may want to go after as a part of the digital transformation. Active management of data knowledge by and for the business is imperative for the modern firm to manage the data asset in line with the business needs and priorities.
Not only that, to secure and to protect it is also the challenge and the solution to many factors like interrupted processes, poor customer experiences, and intrinsic costs. It would be right to say that a cultural shift to a data-focused strategy can ensure the long-term success of an organization.
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