Developing a Strategy for Analytics
Developing a strategy for analytics can help your organization make sense of the data it collects. With the explosion of internet-connected devices and the proliferation of data analytics tools, it is not difficult to deploy the analytics function within an organization. However, deploying analytics without a strategy is not the best approach. To gain the most benefit from your analytics investments, you need to identify problems, define your analytics goals, and identify which data sets are needed to solve them.
The foundation of any successful analytics strategy is a solid plan for the future. There are eight different possible determinations for these three items. The Strategy for Analytics solution you choose will guide your approach to collecting data, resource allocation, and initiative prioritization. Just because you own the data does not mean you should use it. Some people go overboard by correcting data, which leads to analysis paralysis. Similarly, sticking to the most basic data can lead to vanity metrics that don't address the issues you have identified.
While analytics tools are widely available and can help any business solve a problem, many organizations struggle with their adoption. As data volumes continue to grow and analytics applications become more sophisticated, many managers find it difficult to harness the data productively. In the absence of a data management strategy, organizations will experience frustration and slow adoption. As a result, organizations need a data management strategy for analytics that integrates all aspects of the analytics process.
The Modern Analytics must be supported by a sound analytical approach. It should include an actionable plan for implementing the results of the analytics. An analysis should be easy to digest and visually appealing. A clear analysis will result in greater buy-in and engagement from key stakeholders. And the plan must be backed by the execution. This is important because it is the foundation for your strategy. If it does not support the business goals, it won't be of any value to your organization.
A corporate analytics strategy must address the unsexy side of analytics. Most companies fail in this area and need to find a way to depoliticize data analysis to ensure that it is not used as a tool to censor executives. The results of analytics should be used to guide internal discussions and decisions, such as which data to report. For example, if sales are reporting numbers that contradict demand planning, the results of analytics can help them to understand how to adjust the business strategy to achieve the desired results.
The data landscape is increasingly complex, and the challenges retailers face when moving up the analytics maturity model are exacerbated by the proliferation of data sources and platforms and organizational culture. This new analytics paradigm is reminiscent of the complaints of business intelligence leaders about data silos and uncertified data. The knee-jerk reaction to this new analytics paradigm is to control data flows and make them fit into a governed process. Unfortunately, this is not a realistic option. You can get more enlightened on this topic by reading here: https://www.encyclopedia.com/science-and-technology/computers-and-electrical-engineering/computers-and-computing/artificial-intelligence.