Top 10 Enterprise Data Strategy to Transform Business

It’s a misconception that data strategy is only for big businesses, even small businesses can leverage data to optimally create a company’s growth trajectory.  According to a recent research report, companies that leverage enterprise data strategy are 58% more likely to exceed their revenue goals compared to those companies that are not utilizing data. Seagate Rethink Data Report states that companies utilize only 32% of the data available to them, just imagine how much can be achieved if the business is able to tap into the remaining 68% data and transform their business.

Why do organizations need a data strategy?

Data Silos

Data Silos are one of the biggest challenges faced by businesses where raw data gets separated and is not made accessible to the suitable stakeholder when required. To identify and eliminate these data silos, organizations need an Enterprise data strategy.

Shadow IT

“Shadow IT” is a term coined for the team that forms a separate branch when the data is completely decentralized. Such unplanned teams can create redundancy in data assets which results in confusion. This leads to data being mis-interpreted by different people both within and outside the organization.

Security, Privacy and Risk

Cyber attacks have become more frequent in recent years and companies invest a lot in protecting them from such attacks or data loss. When a company has a well-planned data strategy in place, there is no need to worry about data security. 

Benefits of Data Strategy

1. Data strategy improves the processes within the company which makes them more efficient and eliminates business risks upfront.

2. Data strategy can act as a vision for the top level executives to determine ROI for each project and thus helps in planning for future investments.

3. It also creates a data-driven culture among the employees which makes things more transparent and organized.

4. It helps the organization to deliver highly customized and tailor-made service experience to their clients and thus helps in customer retention.

Top 10 Enterprise Data Strategies

1. Understand how valuable your data really is

One of the common questions asked with respect to data is, “How much is data worth to you?”. One can measure the worth of data in many ways like cost of acquiring data, cost of storing the data and most importantly whether the data can be leveraged to increase the revenue of the organization. In some cases, data can also be valuable to others. A business can leverage the data to increase their revenue or improve customer experience, additionally they can look for interested buyers. An excellent example could be a hospital which collects a lot of patient data on a daily basis. This data can be of huge value to other related businesses like drug makers, insurance industry, disease researchers, etc. 

2. Determine what makes data valuable

It is indeed difficult to put a price tag on your data, but it is important to understand what makes your data valuable. 

— Completeness of the data is important, if some fields are missing in the data that is collected, then it may not be useful. 

–The next crucial factor is validity of the data. Is the data collected from a reliable source? Is the data trustable at all times? 

–Like many other things, data too comes with an expiry date. For many use cases, present data is important, so one should focus on generating and leveraging latest data.

–End of the day, the data that is being collected has to be utilized by the business leaders to grow their company.

3. Establish where you are on your data journey

A company can easily go wrong in their data strategy if they don’t track it in realtime. The organization should be in complete control of their data strategy and they should know in which phase of the data journey they are presently in. A company should always have a close watch on where they are on the data journey and stay focussed.

4. Learn to deal with data from various sources

A business will collect data from multiple sources on a daily basis. Data sources include but are not limited to IoT devices, video surveillance systems, customer end-points, social media, web, etc. Unless the organization has a proper data collection and data governance system in place, it will not be able to deal with humongous amounts of data that comes in from various sources.

5. Get a strategic commitment from the C-suite

Data will benefit different sets of departments in an organization in unique ways. Each of them would like to use data for a different purpose. It is important to have a comprehensive meeting with the C-Suite and develop a holistic way to collect and use data throughout the organization and across the departments.

6. In data we trust: Ensure your data is beyond reproach

The core basis of Artificial Intelligence is the data that is used to train the AI models. If corrupted or invalid data is to train an AI model then obviously the model would generate faulty results. Thus, it is important to build transparent, flawless and trustworthy data that will support and train AI models.

7. Seize upon the metadata opportunity

Metadata is again a data that defines and provides information about other data. If metadata is properly applied at all stages, then it would be easier for the organization to make the best use of the data as and when required. Some of the important aspects of metadata are source of data, analytics of who has seen the data, who has used it, and what it has been used for?

8. Embrace the importance of culture

It is critical for organizations to develop and create proper culture that will promote best practices for information exchange. If and when you come across a block in the flow of data exchange, the organization should determine what is causing the data blockage and take necessary steps to eliminate the blockage. 

9. Open things up, but trust no one

It is important to decentralize data and make it easily available for trusted sources. At the same time, it is critical to have a proper data protection protocol in place to prevent data theft or data loss. The security protocol has to be developed with complete transparency and trustworthiness.

10. Create a fully functioning data services pipeline

Transportation of data takes place at multiple levels including data migration to cloud, reformatting data, integration with other data sources, etc. For a smoother data transmission, the organization should design a fully automated data pipeline.

According to a research report by Constellation Research, it is predicted that 90% of the Fortune 500 companies will be either merged, acquired or go bankrupt by 2050. Companies that have embraced a successful data strategy can outperform others and stay on top for a longer period. Contact us for a detailed discussion on how to leverage data to grow your business revenue.

Building a Holistic Enterprise Data Strategy with TAFF

Some organization try to develop a data strategy by own. However, they often fail to provide a holistic viewpoint, a proven process, and a modern approach. A holistic enterprise data strategy leverages multidimensional capabilities to deliver the desired impact from all data generated in your ecosystem. An effective strategy prioritizes the maintenance and improvement of data quality, integrity, and accessibility. Data management, when aligned closely with business objectives, significantly drives the execution of the strategy.

Leverage your company’s data strategically through a holistic approach that tells you what, when, why, and what next. Contact us today to discuss with an Expert.

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