One of the points I’ve been stressing for a long time now is that: It’s not about data It’s about business, the business outcomes, about the value that is generated for business.
Business is the driver, data and what it produces is the enabler. As any other corporate asset, data’s purpose is to generate business value.
It’s not about quality data, it’s not about master data or reference data, it’s not about detailed analytics or cutting-edge machine learning or AI models.
The common sense
Organizations have apprehended the importance of data in their businesses and are looking deeper into data to gain a competitive advantage, implementing machine learning and artificial intelligence to achieve new business objectives and to move ahead of competitors in the industry.
A data asset is every piece of data that organizations use to generate revenues, they are currently among its the most valuable assets, and organizations must invest seriously on managing these assets.
Managing an organization’s data assets improves their decisions, their customers experience and loyalty, it impacts offer and innovation, impacts operation efficiency, it impacts processes, minimizing inefficiencies and reducing costs, it impacts risk and compliance, and may generate new revenue streams.
Organizations that manage their data as a true corporate asset rely on their data assets to develop new products, improve current products, and create better ways of providing value to their customers, employees, and stakeholders.
Truth is that the success of any data related initiative is measured on how it impacts business performance.
The true measure of success is the quality of the organization’s decision processes; the organizations best able to make the best insight-driven decisions faster will gain the competitive edge.
The transformation process that leads to a data driven organization must be wholeheartedly supported on the business strategy and objectives.
Project graveyards are cluttered with data initiatives that did not deliver clear ROI.
With a strong leadership and business focus, data initiatives will pay for themselves by adding real ROI to business initiatives.
The true important questions are the following:
How is it impacting your customer and experience loyalty?
· What is the role of data in your customer relationship processes?
· What customer processes are data dependent and how are they performing?
· What data elements are critical in those processes?
· Is data being used to improve customer service, for up-selling or cross-selling?
How is it impacting your offer and innovation?
· What product, offer and innovation processes heavily dependent on data?
· Are the right people having timely access to that information?
How is it impacting operation efficiency?
· What gains can be achieved in your operations by a more efficient use of data?
· What are the negative impacts of bad quality data in those processes?
How is it impacting processes, minimizing inefficiencies, or reducing costs?
· What are the effects of data in business-critical processes?
· How are those critical data elements being managed?
How is it impacting risk and compliance?
· What data elements are critical to risk and compliance?
· What data related processes are directed implicated in risk in compliance?
· Are those processes properly managed and controlled?
· Are they documented? Are they being developed manually, or using spreadsheets?
These are the answers you need
Although oversimplified these are the questions that need to be answered before deciding on any data initiative.
Data-driven business means business-driven data – it’s about business.
In organization that invested heavily in technology as a first step toward becoming data-oriented, these transformations are still hampered by ill-defined processes and business roadblocks.
The success of any data related initiative is measured on how it impacts business performance.
The true measure of success is the quality of the organization’s decision processes; the organizations best able to make the best insight-driven decisions faster will gain the competitive edge.
Rather than undertaking massive change, organizations should concentrate on targeted efforts to build a data-driven culture. Don’t focus on overall data-driven transformation, identify specific projects and business initiatives that move the organization in the right direction.
A strict alignment with business goals and objectives – Keeping in mind that “data exists to serve business”, this means that any data governance process must be supported on strong business cases, with objectives anchored on business objectives, otherwise it will be viewed as another siloed IT project with no perceived value from the business side.