Simplifying your analytics strategy
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The document provides insights on simplifying an analytics strategy. It suggests that companies accelerate data through a hybrid data supply chain to generate fast insights and outcomes. It also recommends delegating analytics work to technologies like business intelligence, data discovery, analytics applications, and machine learning. The document outlines two approaches for solving business problems - a hypothesis-based approach for known problems and a discovery-based approach for problems with unknown solutions. It notes that managers must decide on the nature of problems and choose the right framework to address them.
Simplifying your analytics strategy
- 1. SIMPLIFY YOUR ANALYTICS STRATEGY INSIGHTS BY - KUNAL BHATTACHARYA
- 2. While the interests in analytics and resulting benefits are increasing by the day, some businesses are challenged by the complexity and confusion that analytics can generate. Companies can get stuck trying to analyze all that’s possible and all that they could do through analytics. In the following slides, let's look at some of my insights on this topic and what is the managerial relevance of those insights. OVERVIEW
- 3. INSIGHT - 1 INSIGHT - 2 MANAGERIAL RELEVANCE
- 4. 1INSIGHT To simplify their analytics strategy and generate insights that lead to real outcomes, companies need to do the following: 1. Accelerate the data. 2. Delegate the work to analytics technologies.
- 5. 01ACCELERATE THE DATA Fast data = Fast insights = Fast outcomes Companies have to accelerate the data by creating a data supply chain built on hybrid technologies. This will enable businesses to move, manage, and mobilize the ever-increasing amount of data across the organization for consumption faster than previously possible.Real-time delivery of analytics speeds up the execution velocity and improves the service quality of an organization.
- 6. 01DELEGATE THE WORK TO ANALYTICS TECHNOLOGIES By letting analytics technologies do the work, companies can work on the results to uncover insights much more easily. The technologies involved are: 1. Next-gen business intelligence and data visualization 2. Data discovery 3. Analytics applications 4. Machine learning and cognitive computing
- 7. 2INSIGHT No matter what combination of culture and technology exists for a business, each path to analytics insight should be individually paved with an outcome-driven mindset. Companies can take two approaches depending on the nature of the business problem: 1. A hypothesis-based approach for a known problem with a known solution. 2. A discovery-based approach approach for a known problem with an unknown solution.
- 8. 02MANAGERIAL RELEVANCE These insights are of high relevance to a manager in India as he has to take decisions regarding how to setup the analytics strategies and integrate analytics into the company's day to day operations. The first insight demonstrates the steps to simplify the analytics strategy so that companies can take insights out of them with relative ease. The second insight tells us the two approaches companies can take to solve a business problem. Managers have to decide the nature and complexity of the problems to be addressed and proceed with the aforementioned frameworks in mind.
- 9. THANK YOU!