Pervasive Analytics: The Crystal Ball for Enterprises
Data growth is showing no signs of slowing down, but according to the experts, enterprises only use 12% for analytics. With this huge opportunity to leverage customer and market insights to drive future growth, what’s holding companies back?
It’s not as simple as just accessing your enterprise data. Traditional methods of data collection and storage have not always placed organisations in the best position to make the most out of their own information. Silos of data have evolved within most information architectures that make it almost impossible to combine into useful analytics.
Security and administrative frameworks are also a problem; they are either not in place or not sufficient for the massive task of data processing. This often results in a quick (and costly) solution being implemented that doesn’t fully meet the needs of the organisation, now or in the future.
With these, and many other challenges, companies find it difficult to see how they can implement an effective data model.
How can organisations prepare themselves for using analytics?
Before thinking about implementing a pervasive analytics model within your organisation, you need to think about your future organisation and consider:
Which of our current business processes would be improved if we had access to better analytics?
For example, would you like to eliminate human input to a repetitive administrative task? Or combine all warehouse stock to reduce wastage and storage costs?
How could our customers’ journey be improved by leveraging analytics?
For example, would you like customers to be able to see the exact stock levels across any of your locations online? Or would you like to offer your customers product options based on their previous purchasing activity?
Then, you can look at actionable steps to make these a reality:
- Eliminate data silos wherever possible
- Extend information architecture to capture larger volumes of data (structured and unstructured)
- Focus on collecting quality data, think about output before what you need to gather
- Facilitate an environment within your organisation that fosters analytic innovation
- Involve employees in the process by bringing analytics to the operational level and equipping them with workflow tools and skills
What are some key elements of pervasive analytics that enterprises need to consider?
Analytics enable you to learn from the past, react in the present and predict the future – but the framework must be in place for you to leverage this
Fast access and analysis of data is imperative for an effective enterprise analytics model so you need to have the right people with the right skills to do this
Combine structured, unstructured and binary data sources to give you the most holistic picture and insights
Your pervasive analytics model must fit seamlessly into your existing enterprise architectures
You need to be able to access analytics across all devices, including mobile
Look into your company’s future in just a few clicks and start your own enterprise data journey.
This article is based on a blog post previously published by me at Blue Ocean Systems
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Data analysis is costly effrt. Analyst cost much, data engineers event more. Add up hardware and software costs and you're close to backrupcy. And then you have chief-something who just cant embrase data-driven and turns to rage when these weird-looking analysts tell him his decisions were wrong.
Typical story.
@bronevik Thanks for your opinion!
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Thanks!