Data Driven? What are you talking about?

Data Driven is making data and analytics a core component of your business strategy, organizational culture, and processes .

It doesn’t involve  installing applications and tools in fact hiring a dedicated team of data professionals, committing to a significant data infrastructure investment, and aslo running a one-time data literacy program.

Data-Driven organizations must acknowledge the value of gathering raw data and that business choices shouldn’t be based only on it.

Instead, they gather data, analyze it, and draw conclusions to solve business issues, spot new business prospects, and increase profitability.

Lets Start With These 5 D&A keys:

Those are some Data & Analytics keys to follow to make sure that you are striving to become a Data-Driven Organization:

Make sure you choose the right reengineering decision:

Data-Driven Organizations that benefit from data, analytics, as well as from artificial intelligence (AI)  realize the value of reengineered decisions.

Understanding the decision-making process further coordinating key decisions within this framework helps you start the discussion and create the business case for proceeding.

Make sure that you:

• Determine the results you are willing for from your decisions;
• Coordinate with essential stakeholders on the use of data and analytics in decision-making;
• Communicate and make sure the business benefits of Data & Analytics in the decision-making process;
• Monitor the consequences of your decisions.

Ensure to prioritize analytics and data:

Leaders in Data & Analyticss (D&A) are becoming more and more critical to company strategy. In fact you expect to exceed your standard support role and create commercial value for the entire company. In case of lack of help from work/tools to identify chances for value creation, this new requirement may prove difficult.

To level up your set on the Data & Analytics value proposition, you must:

• Identify the D&A value proposition for your organization;
• Positioning decision improvement as a way for D&A to produce value should be made explicit;
• Harmonize your D&A investment to promote your success;
• Employ value stream management to guarantee value delivery.

Augment decisions with AI:

It’s not far from now that all decisions that use data will at the very least be automate.

In fact businesses are using AI to help them make the right decisions at the right moment.

For example, the ideal buyer for their new product, or even more how people feel about various issues, therfore what these individuals might want to do next.

The business firmly root in this technology.

Data-driven decisions are made in various methods ranging from fully-automated to primarily human-based.

Thanks to artificial intelligence, organizations that include decision automation in their strategy will likely succeed by making decisions more quickly, intelligently, even with greater granularity.

Data fabric role in your data management:

In the next few years, Data fabric will decrease human-Driven data administration and management activities in reverse it will increase more than twice the Data use efficiency.

First, what do we hear about Data Fabric?

Data fabric is a single environment that enables organizations to manage their data and consists of a unified structure and the services or technologies that run on it.

Data fabric has two essential objectives: maximizing your data’s value and facilitating your digital transformation.

For various use cases, modern data management systems should be capable of connecting/collecting, besides to integrating, even transporting data to and from many sources to any location/destination.

Indeed data fabric structure can indicate what to add, and enhance even integrate data all the same time.

Assure to including the appropriate skills and capabilities in your Data & Analytics organization:

In additing to finding,  and retaining as well as managing Data & Analytics personnel to support these initiatives will remain challenging as the demand for data and analytics soars.

In fact Data & Analytics requires a long-term strategic plan.

A long-term Data & Analytics talent plan is required: a rigorous strategy for attracting,  and recruiting,  as well as managing, and preserving staff.

Enabling specialist data science and engineering resources to be close to business problems and the executives handling them is the key to a successful D&A function.

To sum up a rigorous strategy and plan that is in line with business requirements and is backed by the appropriate people and leadership are necessary for the effectiveness of Data & Analytics.