Consolidated information does provide a better picture of the company's direction and efficiency. In a study done by MIT Sloan School of Management, the results showed that businesses that make data-driven decisions are likely to have 4% higher productivity and 6% higher profits than the average. Analytics provide impactful insights and are the basis for data-driven decision-making practices.
thank you to all the people who have contributed providing lot of insight
Well Statistics points us to first establishing parameter of a given population, in other words what are looking for and how will it benefit our business whether it be Surveys and what are the reason for them, a measure for projected growth and development( Product or services, culture , other factors). Supply and Demand and is it needed or should you be "Lean".
Analytics IS business. We use analytics to predict business and then analytics to measure and track business. without analytics there is no business.
agriculture is the vast and broad sector so you can help us
You can use analytics in different ways. First is to improve your business decisions, basing them on data rather than on gut feeling. (Predictive) Analytics help you answer questions beyond 'what did happen'. It can help you with 'what could happen' and 'what should happen'. Secondly, analytics can also be directly integrated in your processes for improvement. Think of smart personalised websites that 'act' on the behavior of the visitors or processes that are managed by analytics in general. We support companies implementing both.
Analytics can give a company a view of consumer awareness, usage, satisfaction, attitude. They can also provide a handle on how much each campaign is affecting the market. Then they check the sales and at the end if all data is entered correctly and on time, one can use analytics in order to predict the near future.
Data and Statistical models also help in determining high risk clients and do cross sales. Pareto tables show which clients you need to focus on. The list can go on forever.
Countries in the third world develop Analytics for the West, but hardly use them themselves. It's a shame.
Decisions supported by (the appropriate) information tend to be better than those made on a whim. Businesses have to work out (hence the "analytics") what information is most helpful to making the right decision. In many cases, the right information or analytic processes do not have to be complicated. In a few cases, the information gained from a massive investment in data collection and analysis can create enough of a difference over one's competition that it makes the investment well worth while. The question is not whether a majority of businesses are using BA; the question is whether businesses are leaving so much money on the table that they should be using BA to help scoop it up.
Just like navigational data available before starting the car on a trip to improve the efficiency with which a trip is completed, analytic data can be an effective tool for business improvement. The data lead one to a path to draw better end results.
In a business environment you get 2 kinds of information (a) Qualitative (b) Quantitative. Analytic's refers to the latter- Quantitative information. If you are an engineer you will understand it better if mention probability theory, co-relation and regression analysis etc. Analytic's provides justifies Decision Support Systems ( DSS). i.e tangible evidence to support a hypothesis. However, I must caution that not always tangible evidence is enough to support a hypothesis because many variables such as " Emotions" haven't yet been quantified or are not quantifiable. So user discretion is needed :)
Wikipedia provides an excellent definition and purpose of Analytics, as follows:
"Analytics is the discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight.
Firms may commonly apply analytics to business data, to describe, predict, and improve business performance. Specifically, arenas within analytics include enterprise decision management, retail analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix analytics, web analytics, sales force sizing and optimization, price and promotion modeling, predictive science, credit risk analysis, and fraud analytics. ...."
Analytic discovery is definitive. Only with good numbers can positive predictive changes be made.
People make business decisions everyday based on analytics or business metrics. It can be as simple as pricing your product or service, such as 1 cent lower/above the competition (analytics being the customer’s price) with no charts required or a simple go/no go gauge to approve a product dimension. It can be as complex as an employee incentive system based the performance metrics of the business with enormous tracking systems in place or the geometric dimensioning of a product. Analytics should always be used to set goals and objectives or to benchmark the business, the degree and use depends on business needs. Using or not using analytics to make complex business decisions is setting a course of action based on facts compared to a feeling or hunch. I believe recording analytics as a tool to run a business is obvious; developing and implementing effective analytics is more difficult.
First, a bit of a disclaimer: I'm currently the CMO for RapidMiner, one of the leading tools for predictive analytics. I also worked for more than 7 years at Cognos, one of the leading companies in Business Intelligence until the company was acquired by IBM.
Every aspect of a business can be measured and improved upon. Traditional business intelligence tools can tell you much about what happened, and newer, more advanced analytics tools, as a category, can tell you more about what will be. Web analytics can give you a view to your website, what sites and actions are sending you relevant traffic. Different applications of predictive analytics can pinpoint your best prospects, problem areas in your products, or tell you who among your followers, friends and connections is most likely to help spread your message. The key is taking what you learn from analytics and actually implementing change.
Good analytics reduce guesswork and risk in the decision-making process. However, analytics are only as good as the supporting data and the objective manner in which that data is interpreted. The effectiveness of analytics requires a combination of science in their development and art in their communication.
Analytics can help a business in many areas, from marketing, to operations to financial and capital investing. Having a systematic business approach is critical to success no matter in what area of business you apply this analysis.
can you be more specific please, when you talk about Business Analytics, my area is call center and business developments in the industry
Not for SME. this required for Groups , International companies , should be matching with whole branches
They can't, only people can improve business.
Analytics are just a tool for people to use and they may only apply for situation that can be affected.
One is: How do you stack up with your competition using google analytics:?
Through the benchmarking screen you are able to compare your traffic stats with your competition. Of course, this data isn’t 100% accurate because all of your competitors may not be using Google Analytics, but it’s better than nothing.
You may already have a good understanding of whether your website receives more or less traffic than your competition, but do you know how engaged your visitors are compared to your competition? By comparing stats like average time on site you will get a better idea of how you stack up against your competition and where you need to make changes to start improving your website.