Understanding patterns and behaviors through data is key to developing products and services that really win the market.

Every business needs a data strategy!

But what does it look like in practice?

Today,we go through how to design and implement a data strategy for your business that delivers business value.

And we use a six step data strategy framework to do it.

Listen, Assess, Apply, Test, Execute and Scale.

STEP 1:LISTEN

The first step is understanding your business objectives by listening.

While listening focus on

How to increase revenue,
How to decrease risk and
How to improve operational efficiencies.

Identify areas where data can be used to achieve goals and areas that require digital transformation

STEP 2: ASSESS

Asses the current state of your data use and data governance across your business.

Conduct deep design thinking sessions to really learn more.

Review these three key areas:

Types of data being used
The culture around data use &
Operational workflows that use data.

It will give you that understanding of how customer, employee, operational, transactional and external data is being used across the team.

STEP 3: APPLY

The next step is to apply what you've learned in steps one and two

and actually outline it in a document and that is truly your data strategy for moving forward.

However do not jump straight to a technology solution.

Take a moment, pause and include the people, processes and technology needed to take advantage of all that data.

STEP 4:TEST

Step four focuses on testing your data strategy and refining it to establish those controls that are needed to be successful.

During the test scenarios

Look for areas in your data strategy that need to be refined to ensure

data quality, data privacy, and data security.

Outline data governance policies that actually helps protect your data.

STEP 5:EXECUTE

Now you can go ahead and develop those small focus MVPs [minimum viable products] in step five.

Mind you these MVPs need to go ahead and show progress in a short amount of time.

Then iterate along the way, Use sprints to ensure that your MVP is aligned with business outcomes.

And test and refine the solution until it truly meets the intended need.

STEP 6:SCALE

You can now scale your solution to other functional areas and use cases.

If every step is done properly, the results of your solutions will cause a natural culture shift.

as everyone sees the value and starts craving for data-driven processes.

Example

Take an example in a modern banking sector

The biggest challenge for banks today is competing against the customer experiences offered by fintech [financial technology].

As you "listen" to bank stakeholders in step one and assess the state of the entire bank in step two.

You're likely to notice data silos across different lines of business that lead to operational inefficiencies. This is one of the biggest problem faced by most businesses.

With the understanding developed in step one and two, a data strategy can be created, in step 3.

In step 4, the data strategy is tested for KYC [know your customer] regulatory compliance and beyond.The focus here is integrating client datasets across the organization without sacrificing data privacy and data security, and this is done through proper data sharing and permissions.

Step 5, on executing the strategy,

One of the small focus MVP to be developed would be the Loan Origination and Approval system for fastening the customer loan processing.

Loan origination and approval has high ROI [return on investment] but a short enough production time,Therefore the value can be shown quickly here.

Also the MVP can be scaled to other lines of business like credit cards, customer service or sales.

As the solution demonstrates business value, data culture grows organically across the team.

NB:

A data driven mindset develops across when everyone sees the value of data.

Mind you a data driven business will always be ahead in market shares, in sales and growth. Therefore having a team that comprehends this is a powerful advantage against any competitor.

For data strategy in relation with artificial intelligence read: How Artificial Intelligence Can Help Improve Your Business Operations

Making Sense Of Your Business With Data-Driven Mindset

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