PwC's 2016 Industry 4.0: Building the Industrial Enterprise survey has bad and good news!
- of 2,000 respondents only 18% rate the maturity of their data analytics as advanced. Only half use data to drive decisions. That's the alarming part.
- Dan DiFilippo states that cost-effective data analytics tools available and gives practical tips to make data-driven decision the standard in your company
Add another observation:-
Most organisations can access only between 10% and 30% of the data INTERNALLY stored which means that any analytics is severely limited in value. Free text fields, emails, photo & video meta data are usually outside the data analysed.
Data is at the heart of the matter so look for platforms that can analyse most of the data in an organisation like that from 360Globalnet. This includes purpose built analytics to allow decision makers to make and execute decisions with the confidence they have a complete view of available data.
- embedded in enterprise apps
- embedded in manufacturing processes
- offer secure and intuitive self-service BI
Make sure the BI and Analytics delivers relevant insight to all the audience Dan mentions:-
- Regulatory bodies
That means licensing that is scalable commercially. Beware small "out-of-the-box" solutions that are beguiling in demos and proof of concepts to tens of users and become cost crippling when deployed widely.
Lastly, do not believe you can embrace the Internet of Things (IoT), adopt machine learning, AI or even analyse streaming data unless you have got the basics of data management and simple analytics right. See where you stand on the Business Analytics Maturity Model and don't run before you can walk.
Data analytics is at the very heart of Industry 4.0. Leading industrial companies are embracing Industry 4.0 to create tightly woven digital ecosystems of employees, customers, partners, and suppliers—empowering them to rapidly deliver customized products and services while increasing revenue and driving down costs. To remain competitive, every industrial company should review its data analytics skills and organizational structures, making sure it can capture, analyze and fully leverage the data at executives’ fingertips to refine products and services and meet changing customer needs.