- September 15, 2018
- Posted by: admin
- Category: Uncategorized
Data analytics company – Data management strategies have undergone a significant change over the last decade. A decade ago the responsibility of data management laid with the IT department, while data analytics were performed in other departments individually based on the needs. Now, we are seeing a significant shift towards a more centralized approach to data management and analytics.
Much of the change can be attributed to the rise of predictive analytics that has made leveraging data and extracting insights, which have a significant impact on things like revenue and customer retention, much easier.
Still, not all companies are there yet. According to Gartner, only 50% of companies have a C-level role dedicated to data management and analytics. Data is still siloed in IT, and many departments still rely on basic calculations done in Excel and more complex analysis executed by the IT department.
Excel as an analytical tool has obvious limitation (data security, row limitation, two parameter analysis, etc.) but its usage as a primary analytical tool also puts a toll on IT capacity, creating overwhelm and backlogs.
Of course, that is not the reality of all companies. Many have groups of analytical professionals working in their respective departments, never communicating about addressing the overall analytical needs of the company. That is not all.
With a more widespread adoption of predictive analytics, each business unit has their own analytics requirements, database and analysis systems, and reporting hierarchies. Without someone in a position to pool together all individual requirements and align them with the overall business strategies, an organization will struggle to move beyond targeted analytics towards truly leveraging big data.
THE CHAMPION OF ANALYTICS STRATEGY
Effective analytical capabilities start with an enterprise-wide strategy that shows that what you want to accomplish and how. It needs to be detailed and incorporating laws your company needs to follow, such as GDPR. This means successful data analytics strategies start at the top.
Although the executive suite of a company needs to be fully immersed in defining a data and analytics strategy and setting expectations across the entire organization, each company needs an appointed person who acts as a link between the C-suite and the rest of the company. This way you can avoid that strategies and decisions are made in silos across the organization.
In the past, several different people have taken on that role: Chief Analytics Offices (CAO), Chief Data Officers (CDO), or Chief Technology Officers (CTO) just to name a few. However, in the end, the title of the person in changer does not matter for development and execution of a good corporate-level data analytics strategy.
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Article Credit: Dataconomy
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