Why is Building a Data Strategy Important For Your Business Growth?

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We all know that an immense amount of data is generated with every passing second. From our Uber ride to ordering a burger at McDonald’s or every transaction that we make at the ATM, everything is recorded and stockpiled for further analysis.

In the past, data was perceived as nothing but a by-product of business activity, but today it has a value and is considered more of an economic asset.

All the big enterprises generate numerous data, which they want to utilize for the benefit of their company but still struggle in managing, sharing, and turning it into useful information. If you are among one those business owners who are looking forward to utilizing the data that has been just stored in your systems, you have come to the right place.

In this article, you will know all about why is data strategy important, how to strategically manage your data, and whom to consult by uncovering data strategy.


What Are the Advantages of Implementing a Data Strategy?

Listed below are some of the benefits of implementing a data strategy in your organization’s operations:-

  1. Organizations can understand their customers way better with the help of data and analytics. This can help them develop products or execute services that would more likely than not would be ideal as per the expectations and interests of the customers, hence improving customer experience.
  2. Data strategy ensures that the data is accessible to the stakeholders. This also makes sure that the data is shared in a safe manner. Moreover, it eliminates data management challenges such as data duplication across different departments of the organization, data silos, etc.
  3. Implementing a data strategy would encourage a data-driven culture throughout the organization. It will be a blueprint for everyone to follow and which would improve the employees’ data literacy and they’ll have a better understanding of how to leverage it.

What is Data Strategy?

In this modern world, we are bombarded with a continuous flow of data in our lives. The same can be said for business houses as well. But, having said so, the raw data will render useless unless we cleanse, sort, process, and churn out the insights out of it.

Though we all understand the importance of it, unfortunately, most organizations are unable to leverage the benefit of the most powerful weapon in their arsenal – their data set. As per research, less than half of the organizations can leverage their data for decision making and only 1% of the unstructured data is being utilized as of now.

Organizations need a proper data strategy to smoothen the operational flow. Data Strategy can be defined in simple terms as a complete and comprehensive strategy for collating, governing, analyzing, and identifying the relevant intel out of the raw data and putting it to use for making business decisions in a data-driven manner. 

Data strategy is inherently driven by the organization’s goal and overall business strategy. Whether it is better decision making, understanding the pain areas of the customers, or designing a product–data strategy can make a paradigm shift in the organizations’ business approach.

A well-defined data strategy will comprise of – 

  • A properly structured vision for data management.
  • Proper business use cases.
  • Aptly defined goals for the data assets under management.
  • All KPIs and KRAs to measure success.
  • Short-term and long-term objectives to achieve.
  • Properly designed roles and responsibilities.

In this fiercely competitive world, having a well-defined data strategy puts a business in a better position than its competitors. A well-round strategy defines all the aspects and considers all the factors so the management can make effective data-driven decisions to drive the organization.


What is a Data Strategy Framework?

Any strategy can be only defined when put in a proper and systematic framework. A framework goes by as the supporting structure underlying the concept or strategy. The entirety of data strategy success is solely dependent on how properly defined the framework is.

With sophisticated platforms and methodology for data retention, the organizations do get the half job done but the other half is completely reliant on the tactical and strategic understanding of the 360-degree data strategy. A framework comes here for the rescue. 

A properly defined data strategy framework covers multitudes of disciplines from data management. It comprises five core components that collaboratively work together as the building block for the comprehensive data management strategy – Identify, Store, Provision, Process, and Govern.

Identify

No matter how many terabytes of data we possess, none of this would matter much if we don’t know the proper identification and representation of the relevant content. Whether it is structured or unstructured, modifying and processing wouldn’t be possible if the data doesn’t cater to a properly defined format and value representation.

Identification comprises the establishment of pertinent data element naming and proper value conventions. Having precise and accurate metadata (data about data) for identifying and referencing purposes is the sole essence of this first stage. 

Store

Once the data is identified, the data needs to be stored somewhere safe and in a secure manner. In simple terms, putting data in a proper structure and safe storage so it can be retrieved, accessed, and analyzed whenever in need in the future, is the main agenda of data storing. Many organizations do effectively define the storage mechanism, but in practicality, there is a lot of scope for improvement that organizations need to focus on.

Provision

Previously organizations used to store data in silos and whenever needed, they used to retrieve the data for an individual business need. But now there is a complete shift in the business management process. Having data always ready for retrieval and usage is not an add-on capability, rather it is the need of the hour.

Provision is defined as the packaging of data systematically so it can be shared and reused. Also, it provides the appropriate rules and access as the guideline for data usage.

Process

All other steps will fall apart if the processing of raw data into meaningful information is not done properly. Processing is the most complex part. From data cleansing to data formulating – it takes care of all the steps required to provide a unified data view. It hides all the complexities in the back end and gives a complete viewpoint for the users.

Govern

The last part lies with governance to ensure the efficacy and usability of the data remain high. It constitutes multiple steps such as managing data security, establishing data correction logic, setting up new data management rules, and many more. Data governance ensures that the data is consistently usable and adheres to standard data policies.


Data Strategy Roadmap

Once we understand what data strategy is, putting all the points together and making an actionable plan is what a data strategy roadmap does. It is the culmination of operation and strategy. Roadmap collates all the activities and puts a proper structure around them. In the initial phase, all activities look equally important, but it is crucial from a business perspective to prioritize the activities. 

A well-defined data strategy roadmap bridges the gap between the present and the future state. It also defines clearly the operational feasibility and expected ROI. The plan is put together revolving around the business aspect in the center so it can drive results for the organization.

Factors to be considered for the data strategy roadmap are:

  • Availability of adequate staff and matching their skill set with business requirements.
  • The complete flow of budgeting in case capital investment is needed.
  • Identification of the competing projects or the barriers to effective data management.

An organization should be extremely careful while driving the data strategy. With a well-thought strategy, a company can be miles ahead of its competition.


Problems An Efficient Data Strategy Can Solve


Conclusion

Big Data and Data Analytics have been able to transform business in a way that none of us could have imagined years before.

data strategy

Methods of analyzing data are rapidly evolving and the importance of data is expected to increase in every aspect. Therefore, the companies that will be able to devise robust strategies to manage their data will definitely stand out from the rest and achieve their goals.

At DataToBiz the data analytics consultants find the specific pieces of data, which will benefit an organization.  They carry various operations on test data to validate the strategy and make it more profound. The professionals also possess expertise in data visualization, data mining, data warehousing, artificial intelligence, and machine learning.

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