Simplify Your Analytics Strategy
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This document provides tips for simplifying an analytics strategy. It recommends accelerating data by creating a hybrid data platform. It also suggests delegating work to analytics technologies like interactive BI tools. Additionally, it advises using data discovery techniques to uncover patterns and find opportunities. Industry-specific applications and machine learning can also simplify advanced analytics. Developing an data-driven culture and talent is important for ensuring an effective analytics strategy.
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Simplify Your Analytics Strategy
- 2. • Analytics are increasingly getting popular due to the benefits they bring in. Some businesses are challenged by the complexity and confusion that analytics can generate. • Some businesses avoid analytics due to the confusion they generate or they are unable to find success in determining the right strategy for their business model. The uncertainty of Analytics
- 4. Following are steps that simplify their analytics strategy and generate insight that leads to real outcomes: •Accelerate the data: Liberate and accelerate data by creating a data supply chain built on a hybrid technology environment — a data service platform combined with emerging big data technologies The tips that work
- 5. •Delegate the work to your analytics technologies: An interactive BI and visualization solution can help companies improve and optimize their decision-making and organizational performance. The insight-driven decisions derived from them could benefit the business. The tips that work
- 6. •Through the use of data discovery techniques, companies can test and play with their data to uncover data patterns that aren’t clearly evident. When more insights and patterns are discovered, more opportunities to drive value for the business can be found. The tips that work
- 7. •Industry- specific and tailored Applications can simplify advanced analytics as they put the power of analytics easily and elegantly into the hands of the business user to make data-driven business decisions. The tips that work
- 8. •Advanced Analytics is not the only thing that works, Machine Learning and Cognitive Computing also play a major role. Machine learning is an evolution of analytics that removes much of the human element from the data modelling process to produce predictions of customer behaviour and enterprise performance. The tips that work
- 9. •Each path to insight for analysis is unique. Many different and ever-changing elements come to play such as business goals, technologies, data types, data sources, and then some are in a state of flux. Another main component of a company’s analytics journey depends on the company’s culture itself. The company can be more conservative or more willing to take chances. The tips that work
- 10. •The article mentions that there is a chance a company’s culture might be conservative. Hence, more hesitant to accept a change. There is a chance that this might be a disadvantage as it might bring setbacks in making the company data-driven. Insight
- 11. Hence, the company needs to actively try and bring in a data driven culture by methods such a developing insightful, consultive research led by strong methodlogy. Insight
- 12. •Developing talent by recruiting, training and retaining employees for analytics is another way to ensure your analytics strategy is getting a great foundation. Insight
- 13. •An Indian manager needs to understand the new development, i.e., analytics and machine learning change by constantly trying to be as data literate as possible. He is needs to help create a culture of trust where anyone who is honest and contributes is rewarded. Managerial Relevance