What you’ll learn to do: discuss ways in which information is used in business
Traditionally we think about value in business in terms of assets—property, plants, equipment, inventory and even human resources. The explosion of technology over the last decade has made us re-think what is valuable. In fact, what many businesses today consider to be their most valuable asset cannot be held in your hand because it is the information generated by the collection of billions of bits of data. In fact, the data that businesses gather about their customers is, to the most progressive companies, invaluable! For example, when you visit a company’s website, data is captured about what you looked at: what colors you preferred, how long you remained on a page and yes, even your physical location.
Companies take that “data” and turn it into useful information. They can then use this information to push advertising to you, not just through their website but to your social media accounts, your email, and even your cell phone. As the collection of data becomes easier and more cost effective, businesses are constantly generating new and better information about the business environment. In this section you will learn the difference between data and information, the types of data that businesses collect, and, finally, how businesses use information.
- Define and distinguish between “data” and “information”
- Describe the different types of data businesses collect
- Explain the difference between data mining and data warehousing
- Explain how businesses use information
Information flows in and out of a business in many different direction. The type of data a business collects is informed by a business’s goals and objectives. Computing systems can collect a dizzying array of data about the world around us. Businesses must decide what type of data they need to inform their business decisions and then determine where and how that data can be collected. The types of data that businesses collect can be broken down into 5 broad categories: business process, physical world observations, biological data, public data and personal data. Let’s examine each of these categories of data in greater detail.
Business Process Data. In order to remain competitive businesses must find ways to increase efficiency while maintaining quality standards for their products, goods and services. In order to continuously improve their operations, businesses collect data regarding their business processes. This data can range from collecting data on the number of days it takes their customers to pay invoices to the tie it takes to assemble and package a product. In order to collect this type of data, many businesses employ enterprise resource planning systems. ERP systems track business resources—cash, raw materials, production capacity—and the status of business commitments: orders, purchase orders, and payroll. The applications that make up the system share data across various departments (manufacturing, purchasing, sales, accounting, etc.) that provide the data. Another source of process data is Point of Sale (POS) systems. We are all familiar with these – they are the systems that scan the barcodes on our purchases when we check out at the grocery. When a cashier scans the barcode on an item that scan collects data that can be used in inventory management, loyalty programs, supplier records, bookkeeping, issuing of purchase orders, quotations and stock transfers, sales reporting and in some cases networking to distribution centers. The more data a business has about its processes the more likely it will find opportunities to improve or enhance those processes.
Physical-world observations. Technology has made it possible for business to capture real-time data about the physical world. This data is collected by the use of devices such as radio frequency identification (RFID), wireless remote cameras, GPS, sensor technology and wireless access points. By inserting computer chips into almost any object companies are able to track the movements of that item and in some cases control the object. One of the early adopters of such technology was the On-Star system installed in millions of U.S. automobiles. Through the use of a combination of RFID, GPS and satellites if a car owner inadvertently locked their keys in the car one call to On-Star and like magic the doors to their vehicle would be unlocked. In another application of RFID technology, Delta Airlines is now able to send passengers real-time information about the location of their checked baggage. In fact, starting in 2016 Delta fliers who check bags can receive mobile notifications as bags are loaded onto and off of airplanes and when they reach carousels for pickup. By embedding RFID chips in each luggage tag, Delta has achieved an eye-popping 99.9% tracking success rate, according to the company. “In the same way that customers want information at their fingertips about flight changes, we know our customers want clear visibility to their checked bags,” says Tim Mapes, Delta’s chief marketing officer.
Biological Data. If you have a newer smart phone it is possible that you can unlock your phone by simply looking at the screen. This is made possible by facial recognition software. Unlocking your laptop with your fingerprint is another example of biological data available to businesses. Although things like voice and face recognition, retinal scans and biometric signatures are currently used primarily for security purposes, it may be possible in the future for this type of data to allow for product and service customization.
Public Data. Businesses have an almost endless source of data available to them free from public sources. Whenever you log onto the Internet, use instant messaging, send emails an electronic footprint is left behind. For now this data is considered to be “public” and businesses collect, share and even sell this type of data every day. This has become a very controversial topic in the past several years and recent legislation by the EU regarding this type of data may be the first step in limiting the collection and use of this type of public data. For additional information on this groundbreaking legislation follow this link to the European Commission: European Commission and Data Protection
Personal Data. Much like data that is considered to be “public” data, as we use technology we provide a wealth of personal data that businesses can use to reveal much about our personal preferences, habits, pastimes, likes and dislikes. For example, Facebook uses information people provide — such as their age, gender and interests — to target ads to a specific audience. Advertisers tell Facebook which demographics they want to reach, and then the social media giant places the ads on related accounts. How businesses collect and use this data is also highly controversial as exemplified by recent disclosures that Facebook has been collecting and selling personal information gathered from subscribers’ activities on the social network. Much like the controversy surrounding publicly available data, what rights an individual has to his or her data is currently being debated globally.
The volume of data available to businesses continues to increase exponentially and as more and more data becomes available collecting, storing and analyzing that data becomes increasingly complex. This data explosion has made data warehousing and data mining of greater importance to business as we will see in the next section.
Data vs. Information
Many people are under the impression that the terms “data” and “information” are interchangeable and mean the same thing. However, there is a distinct difference between the two words. Data can be any character, text, word, number, and, if not put into context, means little or nothing to a human. However, information is data formatted in a manner that allows it to be utilized by human beings in some significant way. An individual has an almost unlimited amount of data associated with him or herself. This data is of little use to business in it’s raw, unorganized form. It is not until the data is formatted or compiled into something meaningful that business has information about the individual. For example, suppose the department store Big Box is collecting data about its customers from a loyalty card program and online customer surveys. If collects the following data about a particular customer:
- Age: 34
- Big Box Account #: 123456
- Gender: Female
- Zip Code: 22322
- Children: 2
- Marital Status: Married
- Last Purchase: Jogging Pants
These pieces of data alone are not particularly useful to Big Box. It is not until the data is compiled that Big Box begins to get a “picture” of the customer behind account #123456. Transforming this data into information, Big Box is able to know that this customer is a married female who has 2 children and enjoys jogging. They also know that because she lives in zip code 22322 that she is most likely to shop at their store at Halifax Mall since the mall is in the same zip code as the customer’s home address. If Big Box wants to market to her successfully, then they will use this information to include her in an upcoming active wear promotion. Also, since she has children they will also include her in promotions that include children’s wear. The key to collecting data and turning it into useful information for Big Box is that it is a continual process.
So, Big Box includes Customer #123456 in a future mailing and when she comes into the store and makes a purchase her loyalty card records that she purchased several items in the toddler clothing department. This data can be useful information when Big Box sends out information about their annual “Santa Comes to Town” promotion. They can use the purchase data to inform them that Customer #123456 has a toddler and toddlers love to come see Santa!
Later in the year, Customer #123456 makes an online purchase of a pair of men’s work boots and a men’s heavyweight coat. The data that comes into Big Box may look like this:
- Customer #123456
- Date: 10/5/2018
- Item #56-9876 Cougar Work Boots, Size 11
- Item #43-2341 Men’s Heavyweight Denim Coat, Size XL
Not very interesting data by itself. But, now Big Box can use this data to have even better information about Customer #123456. They know that Mr. #123456 probably works outdoors, possibly in a skilled trade; hence the need for work boots and a heavy weight coat. When Big Box spends their promotion dollars on a men’s suit sale they will not target Customer #123456 because they have “information” about them, gathered from these individual pieces of data. As Customer #123456 makes additional purchases, visits the company’s web site and responds to special offers they will collect more and more data. Every piece of data collected will be useful in giving Big Box more and more information about this particular customer. Now, imagine this data is collected on every customer for every purchase over a period of years. The quantity of raw data collected is staggering and the challenge for Big Box is to store this data in a manner that allows it to be turned into information. This is where data warehousing and data mining come into play.
Data Mining and Warehousing
Billions and billions of bits of data flood into an organization’s information system, but how does that data get utilized effectively? The challenge lies not so much with the collection or storage of the data: today, it is possible to collect and even store vast amounts of information relatively cheaply. The main difficulty is figuring out the best and most efficient way to extract and manage the relevant data. In this section you will learn how organizations not only warehouse but then mine the data they collect.
Did you ever think about how much data you yourself generate? Just remember what you went through to start college. First, you had to fill out application forms asking you about test scores, high school grades, extracurricular activities, and finances, plus demographic data about you and your family. Once you’d picked a college, you had to supply data on your housing preferences, the curriculum you wanted to follow, and the party who’d be responsible for paying your tuition. When you registered for classes, you gave more data to the registrar’s office. When you arrived on campus, you gave out still more data to have your ID picture taken, to get your computer and phone hooked up, to open a bookstore account, and to buy an on-campus food-charge card. Once you started classes, data generation continued on a daily basis: your food card and bookstore account, for example, tracked your various purchases, and your ID tracked your coming and going all over campus. And you generated grades.
And all these data apply to just one aspect of your life. You also generated data every time you used your credit card and your cell phone. Who uses all these data? How are they collected, stored, analyzed, and distributed in organizations that have various reasons for keeping track of you?
Warehousing and Mining Data
How do businesses organize all of this data so that they can transform it into useful information? For most businesses this is where data warehousing comes into play. A data warehouse collects data from multiple sources (both internal and external) and stores the data to later be used in an analysis. The primary purpose of a data warehouse is to store the data in a way that it can later be retrieved for use by the business. Despite the name, Data Mining is not the process of getting specific pieces of data out of the data warehouse, but rather the goal of data mining is the identification of patterns and knowledge from large amounts of data. Large retailers such as WalMart and Target track sales on a minute-by-minute basis and data mining allows these large retailers to recognize changes in purchasing behavior in an extremely short amount of time. They can quickly make adjustments to inventory levels based on the information gathered from thousands of individual transactions as a result of data mining. Clearly understanding consumer behavior is a primary goal of data mining. The following video explains just how businesses use data mining to understand and predict consumer behavior.
Today businesses are treating the Internet as a massive data warehouse and are using data mining techniques to gather data about not just existing customers, but potential customers. Data mining tools such as Scrapy, Nutch and Splash allow businesses to learn more about customers, competitors, compare prices and even find new customers and sales targets. As the quantity of data businesses can collect continues to grow, having an effective data warehousing system that can be easily mined has become increasingly critical to business success.
Information and Business
We can summarize how businesses use information by saying, “businesses use information to gain a competitive advantage.” Simply put a competitive advantage is what makes a business’s goods or services superior to all of a customer’s other choices. Internally; however, we can examine closer how information is used in both primary and support activities within the business.
Information and Primary Business Activities
The primary activities are the functions that directly impact the creation of a product or service. The goal of the primary activities is to add more value than they cost. The primary activities are:
- Inbound logistics: These are the functions performed to bring in raw materials and other needed inputs. Information can be used here to make these processes more efficient, such as with supply-chain management systems, which allow the suppliers to manage their own inventory.
- Operations: Any part of a business that is involved in converting the raw materials into the final products or services is part of operations. From manufacturing to business process management, information can be used to provide more efficient processes and increase innovation through flows of information.
- Outbound logistics: These are the functions required to get the product out to the customer. As with inbound logistics, information can be used here to improve processes, such as allowing for real-time inventory checks.
- Sales/Marketing: The functions that will entice buyers to purchase the products are part of sales and marketing. Information is critical to every aspect of sales and marketing. From online advertising to online surveys, information can be used to innovate product design and reach customers like never before. The company website can be a sales channel itself as we have seen with Amazon.
- Service: The functions a business performs after the product has been purchased to maintain and enhance the product’s value are part of the service activity. Service can be enhanced via technology as well, including support services through websites and mobile apps.
Information and Support Activities
The support activities are the functions in an organization that support, and cut across, all of the primary activities. The support activities are:
- Firm infrastructure: This includes organizational functions such as finance, accounting, and quality control, all of which depend on information; the use of ERP systems is a good example of the impact that information can have on these functions.
- Human resource management: This activity consists of recruiting, hiring, and other services needed to attract and retain employees. Using the Internet, HR departments can increase their reach when looking for candidates. There is also the possibility of allowing employees to use technology for a more flexible work environment.
- Procurement: The activities involved in acquiring the raw materials used in the creation of products and services are called procurement. Business-to-business e-commerce can be used to improve the acquisition of materials.
This brief analysis sheds some light onto how businesses can use information to gain a competitive advantage. As you can see, the use of information cuts across the entire organization. Although the uses may vary from area to area one thing that is consistent is that the use of accurate, timely information can improve business processes and thereby enhance the customer experience. When the customer experience is enhanced, revenues rise, profits rise and business flourishes. Information is quickly becoming the lifeblood of business and its importance in the long-term success of an organization cannot be overstated.
- Kang, Ashton. "Delta Introduces Innovative Baggage Tracking Process." Delta News Hub. April 28, 2016. Accessed June 25, 2019. https://news.delta.com/delta-introduces-innovative-baggage-tracking-process-0. ↵