Business Intelligence: Data Analytics
As technology progresses businesses will move forward to take advantage of these advances in technology. Nowhere is this as prevalent as it is in the sciences of data analytics and business intelligence, known collectively as business analytics. As both of these are relatively new concepts that not every business owner will be familiar with, it would do to start with a brief outline of both of these technologies.
Data analytics is at it's simplest a process of examining data to the end of finding new information and drawing conclusions about that information. Data analytics is utilized in a variety of industries for making business decisions and to confirm or refute proposed courses of action.
Business intelligence refers primarily to using computers to identify, extract, and analyze business data. The kinds of data used in business intelligence include sales data, advertising effectiveness, and market penetration. Business intelligence can be used as the basis of a decision support system.
Utilizing business analytics can have a significant impact on your bottom line. By taking advantage of this advanced technology your business can identify not only circumstances that increase revenue but also ones where wastage and inefficiency can be removed.
Business analytics can identify situations that may not be apparent to the naked eye. While is falls into the category of obvious that an incoming hurricane means an increase in sales of bottled water and toilet paper, very few people know that the status of nearby waffle houses is actually an excellent measure of the emergency impact to an area. That information was discovered not by someone driving through an obliterated section of Iowa after a tornado and saying to themselves "Well, it looks like every single waffle house is closed", but through careful analysis of data using data analytics.
Data analytics can also process data faster than any human being ever could. By leveraging business analytics technology you could analyze the entire sales and advertising data across a worldwide organization in a matter of minutes. Examining that same data by hand would take a team of analysts years and by the time the information was available chances are it would no longer be relevant.
By making effective use of data analytics technologies, even the largest businesses can be agile and respond to market pressures and changes as effectively as smaller businesses. In this fast paced technologically saturated world the old ways of doing business where it may take months to get through all of the bureaucracy and red tape to make a decision as to how market a product will simply result in a business going under. However data analytics excel as a decision support system. Being able to walk up to a panel of executives or a board of directors and point directly to a data set supporting your point can cut a tremendous amount of time out of any business decision making process.
However, this is not to say that business analytics can solve all of your problems. Sometimes information and correlations that are discovered during data analysis are simple coincidences. While your business analytics software may be being fed all of your sales, demographic, production, and advertising data, what it can't know is that the reason one of your stores is selling three times as much mustard as usual is because someone opened a hot dog stand nearby.
This is unfortunately the one major weakness of any predictive computer system. A computer model of your business is only going to be as good as the data being fed into it. While you can always feed your data models any data you have, there are going to be factors that simply cannot be accounted for. A popular cooking show presents a new recipe and you sell out of the ingredients. While this might mean stocking a bit more of them, if nobody can manage to cook that new recipe or nobody likes it then you've order a lot of product you're going to have trouble moving. The old adage of "garbage in, garbage out" still applies.
Computers and data modeling techniques are not magic bullets to solve any problem, but instead should be viewed as tools in your arsenal of problem solving. Much as you do not only keep a hammer around the house as your only tool, data analytics should not be your only tool for solving business problems. Both of them are terrible for fixing a broken sink, for instance, and you should probably keep a pipe wrench around.
All of that being said, by utilizing business analytics technologies and other decision support system processes, your business stands to reap huge rewards. Just keep in mind what your business does and what your needs are and you'll stand to do better than the competition. Remember, good software is not a substitute for good business sense, and you know your business better than anybody.