Data Analytics refers to the processes of gathering and analyzing various sets of data that are used for making informed decisions in businesses using AI & ML.
If you gathered a group of prominent business leaders and asked them to describe the difference between doing business in the 20th century and 21st centuries, they would respond with a single word: Data.
When one enters a meeting with a conflicting viewpoint and data to back it up, he will be influential. Organizations generate vast amounts of data, and they are desperate to extract value from it.
According to MicroStrategy’s 2018 Global State of Enterprise Analytics Report, 52 percent of enterprises are using advanced and predictive analytics to provide more insights and contextual intelligence into operations today, and 57 percent of global enterprises have a leader who is helping to standardise data and analytics use across the organisation.
Data analytics, according to the report, is one of the most powerful tools on the market today and will be in the future.
An excellent example is the story of Oberweis Dairy.
In 1915, an Illinois farmer began selling his surplus milk to his neighbours. The company now has 3 distribution channels
The company’s standard decision-making procedure is to ask executives to determine the best configuration for future changes.
When a data analytics executive was asked to join the strategy table as the company attempted to expand geographically in 2012, the predicated about customers were challenged.
According to data analysis, a significant sum of money is being spent to acquire customers who should not have been approached in the first place.
Data from customer sales showed that “the so-called Beamer and Birkenstock group—liberal, high-income, BMW-driving, established couples living leisurely lifestyles” was not a good fit for the dairy farm, contrary to the company’s conventional wisdom.
As a result, the meeting shifted from a tactical discussion about “how many trucks and transfer centres would be required” to a strategic discussion about “defining the target market.” The shift is cultural, and it has progressed to the point where people want to learn more about analytics tools because they see the value in doing so.
Another success story!
The American multinational consumer goods corporation Procter & Gamble (P&G) has done so.
P&G is using simulation analytics to design new products, including disposable diapers. P&G uses predictive and simulation analytics to ensure that product performance is optimal.
Customer-centric marketing campaigns are also created by P&G using analytics.
Analytics has helped people in all types of businesses make better decisions. The advantages of business analytics are felt throughout an organisation. Data from various departments is consolidated into a single source, which keeps everyone in the organisation in sync and eliminates communication gaps.
We provide analytics services to the FMCG sector that can help them make more informed decisions.