Data Strategy Roadmap - Tips and Guidance

Treat Data as a source of innovation, new revenue and strategic advantage! Data like intellectual property, patterns, or a brand is a critical intangible asset for any business today.

Data was used for measuring and managing business processes and assisting in forecasting and long-term planning.

Generating data is often the most straightforward part in significant quantities continuously created by various sources. The greatest challenge is harnessing the data and turning it into valuable insights. Traditional analytics based on spreadsheets have given way to big data, where unstructured information joins with powerful new computational tools. Data to become a natural source of value, businesses need to change the way they think about data. They need to treat it as a critical strategic asset.

Once you start to treat data as an asset, you need to develop a data strategy. That includes understanding what day you need and how you will apply it.

At REDT, we break the strategy roadmap creation into three steps:

Phase 1?-?Business strategy?– Preparation - Define the Goals, Problem-solving and set limits

In this phase, we understand your requirements and your desired outcome from data management. What area do you want to address and prioritise reporting and workflow systems?

Afterwards, we define the various formats, tools, and interfaces for how data can be used:

• Descriptive reporting and analytics– (Why did this happen?)?
• Diagnostic analytics – (What we can learn from it?)?
• Predictive analytics – (What's most likely to happen? )
• Prescriptive analytics – (What should we do? )
• Cognitive analytics - (New ways if working! )

The following steps will define all algorithms, KPI and scorecards. Having all data sources, frequency, quantity established, we will draw the data workflows (similar as you see in the cover photo). Based on Return of investment, we will write a manual of Data Strategy Roadmap that will be given to the IT team and become the bible of this process.

Without these steps, the Data application chose to implement, and the data management structure will be a failure or a process more costly than budgeting. You need to align Data to business goals for a successful roadmap.

Phase 2?-?Data application & - Data management

Here starts the magic and the fundamental know-how where the data lakes marts and structured, hosted and managed. It is recommended an MVP implementation align the IT infrastructure and digitalisation of the company before we move at performance across the corporation.

Phase 3?– Scalability – Implement Red T across the portfolio??

There are the roles necessary to deliver and implement a data strategy. Team size and designations are adapted based on the complexity of the project and can be full time, part-time, project-based etc.:

• Chief data officer
• A data governance program manager?
• Data steward
• Data owner
• Data architect
• Data user

Good data governance may take 3 to 6 months to institute. But once it's in place, you'll appreciate the better outcomes that it'll drive.

The average tenure for the roles of the Data management team is roughly two years. The reason is that the parts are often poorly defined, and the new chief data officer's ability to make a change is limited.

It's critical that the new chief be empathetic, a great communicator, and someone who's highly collaborative. We will help overcome the fear many will have that the new role represents a loss of some degree of autonomy over the data that their part of the company gathers, which, truth be told the reality of the situation. A lack of clarity on that part can cause politics and fear to get in the way of progress.

At its best, the introduction of the chief data officer is also an invitation for greater collaboration across the company, as the new leader should bring the leaders of the other functions together for better coordination of efforts across the company. Data strategy should involve making the traditional silos of the business more porous so that collaborations can percolate from across the enterprise.?

We will help you set up your chief data officer role and department for success by applying these difference-making techniques. We are ready to employ the team on our payroll, and after the project is complete, you can insource them.

We drive the process of embedding these digital capabilities and digital talents, like data analytics and AI, directly into your business segments. The goal is to raise the bar on data knowledge. The more the broader team is aware of the power of harnessing data, ultimately to make better decisions for the company and the company's customers, the better off everyone will be.

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