The strategy behind Data Analytics.
If you’ve been reading my post, then you’d know that data analytics is the most disruptive technology impacting all the organizations. Everywhere around the world, Businesses are trying to become data-driven. That is, they are using the data to improve their performance.
For a new business trying to adopt data analytics, a strategy must be created before delving into it. Without a strategy, a variety of things could go wrong implementing the data analytics. Companies could get stuck in one phase of the analytic process, or they could get drowned in the overwhelming amount of data, or they may choose a wrong algorithm for their use case. To avoid these scenarios, a business must have a data analytics strategy in place to govern the process.
Necessities required before developing an analytics strategy.
Before developing a strategy, an organization should assess if they have the following capabilities.
The business needs to make sure that they have the analytic capabilities to do the analytic process. Capabilities like tools, analyst team, data, etc should be present in the business. The infrastructure within the organization should support the analytic process so that every person in the organization gets access to the analytic tools. The culture within the organization also should enable the employees to know the value of analytics and to contribute to it.
After a company verifies that it has the necessities required for developing a data analytics strategy, it can start forming the strategy. A good way to develop a strategy is to answer the following questions.
What problem are you trying to solve?
A company should clearly identify the problem before starting to collect the data. Everything in data analytics from data selection to algorithm selection depends upon it. Data analytics can improve a business in a number of ways like identifying potential customers, predicting performance, etc. It may look silly but a company should have a clear goal in their objectives and set their priorities right.
What data do you need?
After identifying the goal, determine the data that you need for achieving your goal. It is one of the daunting tasks in the analytics process. Identifying data and make it cleansed is not easy even for a big analytic team. This task should be done carefully as it affects the further process if not done right.
Wrong data or noisy data significantly affects the quality of the results you get. However good maybe your algorithm or analytic process, if the data is not good then your result will be not.
How will you analyze the data?
Once you identify your goal and the data to achieve the goal, you need to define how you are going to convert the data into valuable insights. You should define the tools, algorithms, and necessary process. This is the core part of the strategy build and an easy part too.
The analytic process may seem daunting but there are various tools and software that abstracts the complexities present in the analysis. The only difficulty here is to choose the right algorithm and tool for analyzing the data you have to meet your goal.
How will you present the result?
Getting the required result is only half the story. The rest is how you present them. Mostly the results from the analytic process will be in mathematical form. This cannot be easily understood by the management team. So, you need to pick a visualization technique to present your result.
There are lots of tools available for this step. These tools are mostly integrated with analytic tools itself. So, this process will be easy once you identify the way you should present your results.
The Strategy building task is the reverse of the analytics process. You identify the goal first and work your strategy upon that. After creating the strategy for your analytic process, you need to create an action plan and execute it. In addition to forming your strategy, keep key decision-makers of your organization involved in the critical stages of the analytic process. It helps them make a better decision.
Every organization implementing an analytic task should have a strategy. It lets them execute the analytic process seamlessly. Keep in mind that the action may not go as planned in the strategy. You may not meet your goal, or the result may lead you to a different path. If that happens, examine your strategy again to get the desired result.