Organizations are becoming more and more fast-paced every single day with the competition rising in each industry segment. With the advent of startups challenging the supremacy of big corporate, leaders are no longer making decisions based on gut feelings. Nowadays all executions and strategies need to have good data analytics for business. Moreover, accurate reasoning behind them which is supported by some facts and figures.
Data Analytics For Business
Analytics for decisions Insights relies upon datasets and to what extent they have sorted through for the greatest benefit of the company. Whether you are doing this via automation or sifting through terabytes of data. The goal is the same and that is to draw some conclusion based upon a set problem statement. According to McKinsey Global Institute, Data-driven institutes are 23 times more likely to get new customers and this is an astounding stat for companies of all sizes. This alone is sound reasoning for CEOs of companies of all sizes to use data to increase their revenues.
Data Analytics For Decision Making
Let us see how CEOs can use Big Data to their advantage in regards to decision making.
Predictive Analysis For Goal Setting
An arduous task for a CEO is to outline quarterly and yearly goals in line with the vision of the company. However, one has to define goals and tasks which are not ambitious but also not underwhelming to make sure that the teams are working to their full potential. These goals are the basis for the organization’s growth and revenue and should have greater consideration.
Big Data presents the opportunity of backing up each quarterly goal with a statistic supporting it. Additionally, outlining previous experience about why achieving the goal will help improve the company’s performance. Artificial Intelligence is capable of making these predictions for us. If, we have defined the scenarios and have a large enough dataset from which it can provide an outcome.
Automated Assessments Of Teams
Sales and Marketing Teams can assess based on predefined criteria. The KPIs for these teams are generally the same provided the company has one core product. Based on these indicators, one can check the performance of individual team members. In similar terms, teams using the Agile model of working and having sprints with goals outlined could check using AI techniques. These assessments are impartial and can help managers make important decisions on shifting members from one department to another. Furthermore, giving bonuses or even firing some employees, etc.
Revenue Predictions Of Each Vertical Of The Company
For large organizations working on different projects, Big Data presents a massive opportunity to predict the success and failure of these projects. Each vertical is working on a different project, taking into account the company’s previous experience. Also, CEOs can make predictions on the forecast revenue of each division of the company.
These discuss metrics serve as a measure for performance evaluation of the division of the companies as a whole. For instance, Microsoft’s revenues these days are reliant on the cloud computing segment. Before, they scraped off the mobile division (Nokia) because it wasn’t keeping up with revenue expectations. However, this is one example of how data becomes a basis for decisions within a company.