Analytics makes full use of mathematics, statistics, computerscience and so on. In the business environment, there are three popularanalytic methods: the descriptive analytics, predictive analytics, andprescriptive analytics. These three methods support organization to make rightdecisions. According to the survey of the Emarketer, 49.
3% people consider thatthe predictive analytics and models do conducive to collect more relevant data,which provides the help in making the decision. In the process, people arerequired to identify the problem and make the preparation of the data firstly.Then they transform data into information and create the model. At last,testing the validate models repeatedly is needed.
I would like to use criticalthinking to consider whether the analytics is People’ s business. It isabsolutely right that the analytics cannot leave human considering the processof making the decision. The people establish the database and develop many dataanalytics tools. The data-driven thinking is prevalent in business. On thecontrast, the result of analytics must follow the truth and data itself, notpeople’ subjective view. The employees need to conduct the analytics based onthe data.On the one hand, analytics is aPeople’ s business. People start to utilize the analytic methods which make itbecome an increasingly important role in decision-making.
At firstly, employerscollect data from a variety of sources which includes the financial statement,social media, sales trends, marketing trends and so on. And they set up thedatabase to store a large amount of data. Transforming data into usefulinformation is the data visualization. Machine learning and many analyticstools like Hadoop, Python, SAS and so on is extensively used in the process. Inmodern society, since the purple people emerge in the recent year and theyextensively utilize the data analytics. The purple people are the analyticsleaders who perfectly combine the business and technology. Besides, thepurple people have the strong background in business analytics. They help theorganization to recognize and analyze the problem and manage the whole teams.
The information technology teams and computer science teams build the model tosolve the problems. They make the decision based on data analytics and play avital role in their organization. I would like to take the Tim Leonard, the chiefat Xpress, for example. He possesses the strong technical background and businessanalysis skills. His teams dominant established the real-time businessintelligence system which is utilized for monitoring data from trucks. Thesystem collects a large amount of data as well as the real-time data.
Inprocess of transportation, the system collects real-time data which includeshow petrol usages, tires, brakes, engine operations affect the trucks. Thepurpose of collecting these real-time data is recording the capacity of trucks.In addition to this, their team council the trucks and improve the speed ofdelivery by recording 900 to 970 data elements of the engine data. TheGeospatial analytic team in Xpress puts data into Hadoop database and all the datais prepared to be processed and analyzed. They monitor the idle time of trucks.Then the enterprise is able to know when the truck is running and it canutilize the idle trucks. The Xpress makes full use of existing resources toimprove the efficiency and speed of delivery.
The system saves $20 million inone year and makes success in the transportation industry.On theother hand, analytics is not a People’s business. Analytics is based on thedata and fact and it won’t change due to the subjective factors. It is truethat the analytics is relevant to data. Althoughpeople lead the analytic in business, the use of analytics is not a subjectivething.
“The great thing about fact-baseddecisions is that they overrule the hierarchy.” Jeff Bezos said. Inthe organization, the junior people may deem that the superior and experiencedpeople always make the right decision.
However, in the organization, the juniorpeople neglect to analyze the data itself. If so, the decision may be wrong andthis will have the negative influence on the organization. For example, insophomore year, I practiced as a beverage salesman in a supermarket.
When Ientered the supermarket, I found that the sale of the beverage was declining. Istarted to look for some of the problems. By analyzing the monthly sales dataand the questionnaires, I found that there are too few variety of drinkscompared with other supermarkets. So, I suggest the manager increase thevariety of beverage. The manager said that ex-salesmen are experienced andchoose these varieties before.
He is afraid that the too many varieties ofbeverage are unsalable and my analysis lacks evidence. Later I talked to themanager several times and present the sale data, then he agrees that I can tryin three months. At last, by increasing the variety of beverages, thesupermarket increases sales of beverages. In the organization, the employeeshould give own suggestion based on the data, not just follow the experiencespeople. Allin all, it is significant for the organization to utilize data analytics. Notonly is it based on the data but also the analytics is people’ business. Peopledevelop the data-driven thinking and data analytics tools.
Moreover, peoplecollect more data than before and store it. The decision-making gets more andmore support. The employees don’t bring the huge change in the Xpress bymonitor the real-time data, but it achieves success in saving cost.
Making fulluse of the data analyticsmay contribute to data-driven enterprise thinking. In the long run, theorganization will keep competitive. At the same time, the analytics shouldsupport the fact-based decision, we cannot deny the fact due to people factors.All conclusions we draw needs to conduct data analytics.
For all organizations,they are required to utilize data analytics to make the decision moreaccurately. They also need to focus on the suggestion from the employees.Analytics is complex files, we should learn to use it correctly.