https://www.datatobiz.com/blog/data-strategy-for-business-growth/ We all know that an immense amount of data is generated with every passing second. From our Uber ride to ordering a burger in 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 as 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 amongst one of 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.

1. Importance of Building a
Data Strategy for
Business Growth

2. 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 in 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.

3. 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.
A well-defined data strategy will comprise of –
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.

4. What is a Data Strategy
Framework?

5. 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.

6. 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 of improvement that organizations need to focus on.

7. 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 the 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.

8. Govern
The last part lies with governance to ensure the efficacy and usability of the data remains 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 adhering to the standard data policies.

9. Data Strategy Roadmap

10. 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 for effective data
management.
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. At 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 organizations.
Factors to be considered for the data strategy roadmap are:
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.

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business-growth/