Descriptive analytics is represented to provide inside descriptions in the past to know “What has happened?” by using data mining and data aggregation, and help the organization to analyze the source of main occurrence in its management. The used data sets are collected from the past historical data which are valid and accurate to understand the events that has happened in the past. The organization can learn from past performances to fix the problem and examine the past mistakes between its customers and products. These data sets can be helpful to classify the strength and weakness in their functional area so that they can emphasize on these points. Descriptive statistics assists to answer the problems like “What are the main reasons of declining sales and facing poor financial performance in the organization?” in which they can be compared by year to year, month to month or quarter to quarter to make any progresses. And then, the company can view if they are in the strong direction to be in trend or not. The analysis also equip some operational methods to deal with problems to reach its targets and goals. This analysis is used in almost every functional area, consisting of sale and marketing, finance, production and operational activities.
The analytics help the organization with insights based on historical data (descriptive analytics) to forecast the possible outcomes of future event; “What might happen?” or probability of future occurrence. There is one condition to aware that the statistics cannot be 100% exact since the sources of this analytics is come from probabilities. Mathematical modelling from various systems are unified to analyze patterns in historical and transactional data, and to catch relationships among data sets. Predictive statistics are used whenever the organizations want to forecast the future, estimating consumers’ behaviors to classify trends and sale activities as well as operational management and inventory. For example, the organization can use predictive analytics in analyzing customers’ data, including the capabilities of customers’ spending on its products, their preferences over current patterns or adding new products. The organization should have investments in this analytic project team with experts to find new strategy to solve the problem of declining sale and poor financial performance in the company
It is the analytics which play as a next stage to provide suggestions on possible outcomes by predicting the consequence of future decisions. Prescriptive analytics estimate not only “What will happen” but also “Why it will happen” by providing various options before making final decision to have benefits of the predictions. Moreover, these analytics can contribute many decision options to have advantage of future or reduce risks in the future. Furthermore, they also help to be specific in prediction, and better options or recommendation are provided. Many data sets might come from different sources which can be internally or externally. Combination of techniques and tools, consisting of computational modelling procedures, and business rules, are used in identifying to interpret, suggest, and determine possible decisions to influence one or more actions in the future. Anyway, most companies hardly ever use this analytics in daily processes. If this is used for any cases, the company might have great advantages in making decisions to progress its business. These statistics are literally used in large successful companies to enhance production and inventory of supply chain to ensure the products are delivered on time or analyze customers’ expectations.
If the H&M group is facing the problem of declining sales and poor financial performance, Marketing and sales functional area will tackle in making decision for declining sales when finance department handles the problem of poor financial performance. They have to be solved within 1 years (short term) as important problem for the company. The marketing team from operational level has to do some researches in sale activities to precise the current problem and communicate with the customer to know their preference. The financial problem is concerned with the communication with its suppliers and the valid information of costs in their productions. The relevant managers from managerial level are supposed to use historical data to prejudge the future. For marketing, they have to set goal for activities and make new plans for their multi-channel campaign in sales and advertising management. The financial manager is involving to create plans for budget development, products pricing and the spending over purchasing products from its suppliers. Apart from that, they analyze the main sources of this problem by using both external and internal factors, and suggest some decision options to CEO from strategic level. As final stage, CEO and shareholders centralize a final strategy to solve these problem.