Big data analytics has a big potential to be the transformation element for a company and for the industry in general, especially in Supply Chain.
Companies like Facebook, Amazon, and Uber have been using big data analysis for their own success. Other companies like AT&T, General Electric, and American Express have been changing the way they compete in the marketplace through the application of big data analysis.
Any company can use big data analysis to create benefits as:
- Reduce operating costs of their companies by improving the efficiency of business processes, improving all the supply chains processes.
- Increase the revenues dramatically by improving their effectiveness in the marketplace, and growing customer relationships.
- Reduce dramatically the risks of no compliance by eliminating fines from lack of government compliance.
The implementation of big data is not a simple project. It will be a big journey that involves many different projects to continuously gain more value from your big data.
With time your big data journey will evolve through five different phases in general:
- Ad-hoc: This is the earliest phase where organizations test and learn about their big data needs.
- Opportunistic: This is the phase where an organization starts to deliver value to their business, building their skills and knowledge.
- Repeatable: This phase is where a company creates a replicable model for big data projects and starts to operationalize them.
- Managed: This phase is where big data analytics becomes a managed service that starts to spread across the organization.
- Optimized: In this phase is where the big data becomes a well-synchronized machine, delivering on a continuous basis new projects that make exponential the value to the business.
As the company passes through these phases, it will see an exponential increase in value and momentum with your big data implementation.