When businesses attempt to harness Big Data, they’re looking to obtain actionable intelligence that can influence key business decisions. A variety of tools to do so are now available, but executives often get lost in the process of selecting which program would best suit their requirements. If a company needs to determine how a specific action will affect a particular industry, predictive analytics is probably the right choice for them. If a merchandiser wants to figure out how a single customer interacts with its brand, then descriptive tools may be the best option.
Know what you’re working with
Trying to draw conclusions from raw data aggregated onto is both inefficient and ineffective. A company could collect all the data it wants, but if there’s no way of managing and segregating the information, then hastily made conclusions could send the company in the wrong direction. In addition, how professionals perceive the intelligence should not be manipulated by how they want to interpret it.
When it comes to understanding data, an open mind is mandatory. If tailored data displays a slight or entirely different angle on a particular situation, it’s better for management to adjust their plans according to the information as opposed to distorting the meaning of the digital information so that it better coincides with an original business strategy.
Ultimately, data analytics gives C-suite professionals the ability to navigate through previously undecipherable patterns. ITWeb contributor Goran Dragosavac stated that there are three primary kinds of intelligence scrutiny platforms that draw considerably different conclusions from a single marketplace. Depending on what kind of business a particular company is in, the usefulness of each platform may vary significantly.
1. Predictive analytics examines the events of the past and present to determine which events will most likely transpire in the future. How can the current actions of a company manipulate the outcome? What should the business do to change the end result?
2. A descriptive program detects both favorable and undesirable patterns across organizations and regional economies. For example, a health care organization may use such a solution to discern what actions a certain hospital is taking to effectively eradicate diseases. How do its practices differ from other facilities in the same area?
3. Sequencing software allows enterprises to scrutinize individual aspects of a particular operation, such as warehouse management processes. How will sensors placed on individual packages affect database capacity? Wouldbe more preferable?
Determining the actions of individuals
To deliver better service to customers, retailers worldwide are attempting to unify the data they aggregate from brick-and-mortar stores and e-commerce outlets. Caroline Baldwin, a contributor to ComputerWeekly, claimed that Big Data has incited a wave of personalization through the merchandising industry. However, controlling the information as it flows through servers remains a challenge to many.
Harvey Bierman, vice president of global e-commerce for foot apparel brand Crocs, noted that correlating the online data and in-store information pertaining to a single customer is much easier thanks to loyalty programs. Every time a consumer purchases an item through a website or a brick-and-mortar store, the information is entered into awhere an analytics program can differentiate the individual’s shopping habits. In addition, frequent-buyer initiatives can help customer relationship management (CRM) tools develop personalized marketing campaigns. Whenever a customer visits a website, relevant advertisements will then pop up, indirectly influencing the visitor’s purchasing decisions.
There isn’t a single, comprehensive solution that will produce the kind of intelligence different organizations require. Oil manufacturers may use one analytics tool while an environmental protection group may use another, for example. It all depends on what kind of conclusions their leaders are attempting to draw from the data.
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