Enterprise Analytics as a function enables the Business Leaders in an organization (across levels – operational/ tactical/strategic) to make decisions which are fact based and help accelerate the Business outcomes.
In today’s Enterprise there are data of wide variety ranging from the journey of an online visitor in the company’s website to what customers speak about the CO & its products/services in the online (inclusive of social media) space. The data includes the responses and sales conversions received against a marketing campaign, operational data generated at its manufacturing shop floors and machines, how its products and services perform during customer usage, what are the failure modes of its products and what kind of fixes are done and how is it occupying customer mindshare with respect to key competition. That is an ocean of data & information!! Enterprise Analytics function helps in synthesizing this plethora of data and arrive at actionable insights to the business managers.
Establishing a successful enterprise analytics capability needs following components:
- Business Managers who are eager to consume data- based- Insights and use them for decision making (a data-driven-mindset)
- Sufficient data of good quality
- Scoped out analytics engagement
- Clear articulation of what business problem/ business opportunity we are going after via analytics
- Keep the short term goals in mind while working towards sustainable long term solutions
- A habit of quantifying and sharing of the business impact or value enabled by analytics
- A pragmatic approach suiting the organizational culture rather than a ‘boil the ocean’ approach
Reaching this far with the implementation means that the organization has been successful in accepting the enterprise analytics way. The above components ensure that your enterprise analytics work towards delivering the best for the organization and lead to the desired results.
It is very import for the enterprise wide technology roadmap to be aligned with the organizational goals. Segmenting the various users in the enterprise would help in identifying the right tools stack and deploying them.
There are some tools that reach only half of your total employee base. There can be some technologies/ tools that are meant for only data scientists, some for the super users and others can be for the casual users who are not much deep into data analysis..
The trend in Enterprise Analytics is being opined as more of “as-a-service” offerings, this will simplify the transition to democratization of data within organizations. This service alignment drift is not new to business, but it is new to the advanced data analytics functions of the business.
This trend will only get stronger in the approaching years, particularly with the increasing emphasis on the Internet of Things (IOT).
(Disclaimer: This is a guest post submitted on Techstory by the mentioned authors.All the contents and images in the article have been provided to Techstory by the authors of the article. Techstory is not responsible or liable for any content in this article.)
About The Author:
Ganapathy V, currently leads the Enterprise Analytics practice for Philips globally; as part of the Philips Group Level Business Transformation. In his role he is championing scaling up of ‘Analytics’ as a differentiating capability for Philips.
He is responsible for Global delivery of Analytics services to all functions of Philips for their Consumer Lifestyle, and Healthcare Business Units.