Oct 26, 2015 | Big Data, Business Analytics, Business Forecasting, Business Planning, Data Analysis, Predictive Analytics, Technology and Trends |
One thing is certain, if you want to run a successful business, you need to hire the right people to help you get there. Who is in charge of recruiting and hiring your team members? “DING, DING, DING!” you guessed it, Human Resources. Human Resources is beginning to pull ahead in the Business Analytics world. In a “Big Data” world, HR can use “People Data” to their advantage and help businesses develop strategy when it comes to hiring the best candidates. As David Klobucher writes in his article, “Data-driven confidence will help HR professionals identify behaviors and interview styles that attract better employees, as well as qualities that make effective workers – and lead to faster promotions.”
I agree with Klobucher, this is a great time to be in HR. There are big opportunities that may be presented to anyone working in HR. Executives within businesses are looking to their Human Resources department to help build the strategy to success. Of course this all depends on if HR professionals “welcome” the technology with warm arms. As stated in the article, many individuals working with Human Resources are not completely comfortable using data just yet. In today’s world, Big Data surrounds all of us, but for HR, this can lead to big success from analyzing data of past successes and past failures.
In some HR departments, to take on this scope of technology could be intimidating, however like one of my favorite sayings goes, “I never said it would be easy, I only said it would be worth it.”
Read original article here.
Oct 13, 2015 | BI Solutions, Big Data, Business Analytics, Business Budgeting, Business Forecasting, Business Planning, Data Analysis, Predictive Analytics |
Do you agree with the phrase, “less is more?”
We hear that phrase a lot, but what does it actually mean in the Business Intelligence/Big Data world? In the article, Big Data Breakdown: Use the Right Analytics for the Business Problem, the author gives a great example of how that phrase, “less is more,” stands true. Meta (great name!) S. Brown points out that in today’s business world, many are wrapped up in the thought of, “the more data the better.” But in actuality, to gain the most return on your investment, the key is to have just the “right” amount of data to solve your problem. Interesting that Brown states that many businesses actually need only between 1%-10% of the amount of data they are currently collecting. Maybe this is something that businesses need to start taking a closer look at, namely, “can collecting too much data be doing more harm than good?”
Check out the original article here.
Jul 13, 2015 | BI Solutions, BI Strategy, BI Studies, BI System, Big Data, Business Analytics, Business Budgeting, Business Forecasting, Business Planning, Business Reporting, Data Analysis, Predictive Analytics, Technology and Trends |
“Top Technology Trends for Today’s CFO’s” is another insightful post from a blogger we frequently feature, Timo Elliott. In it he admits that the CFO relationship with the CEO and other business executives leaves something to be desired. He recommends that CFOs invest in the latest technology, which will increase productivity with real-time updates and continuous forecasting.
{Image from Timo’s post, link to http://timoelliott.com/blog/2015/07/top-technology-trends-for-todays-cfos.html}
Elliott mentions a combination of new technology including: in-memory computing, big data, the cloud, and mobile.
He homes in on a key point—that finance staff at large companies are extremely bogged down with just the basics of maintaining their financial reports. As Elliott puts it, “Staff have to spend too much time on basic duties and have no time to improve their understanding of the operational measures that drive and impact financial measures.” This lack of insight or understanding of how the operational measures drive and impact financial measures is the root of the relationship problem between CFOs and other business executives.
Elliott suggests new in-memory computing technology because, “they reduce complexity by combining real-time actuals with budgeting and analysis in a single, integrated system. Financial data is stored just once, making almost every aspect of financial operations faster, simpler, cheaper, and more effective.” We couldn’t agree more, as developers of a new in-memory technology ourselves.
The result of improved systems, improved speed, and better data is ultimately a better working relationship between business executives, and a more productive, effective workplace.
Read Timo Elliott’s post here
May 14, 2015 | Data Analysis, Predictive Analytics |
“No matter what, you still need business intelligence to know what really happened in the past, but you also need predictive analytics to optimize your resources as you look to make decisions and take actions for the future.”
The blog clearly explains the complementary nature of Business Intelligence (a.k.a. descriptive analytics) and Predictive Analytics despite the various differences between the two. See excerpt below.
Business intelligence looks for trends at the macro or aggregated levels of the business, and then drills up, down, or across the data to identify areas of under- and over-performance. Areas may include: geography, time, products, customers, stores, partners, campaigns, or other business dimensions.
Business Intelligence is about descriptive analytics (or looking at what happened), slicing-and-dicing across dimensional models with massive dissemination to all business users.
Predictive analytics, on the other hand, builds analytic models at the lowest levels of the business—at the individual customer, product, campaign, store, and device levels—and looks for predictable behaviors, propensities, and business rules (as can be expressed by an analytic or mathematical formula) that can be used to predict the likelihood of certain behaviors and actions[2].
Predictive analytics is about finding and quantifying hidden patterns in the data using complex mathematical models that can be used to predict future outcomes.
View Full Post – Business Analytics: Moving From Descriptive To Predictive Analytics
Source – EMC
Dec 18, 2014 | BI Solutions, BI Strategy, Business Analytics, Data Analysis, Predictive Analytics, Spreadsheets |
From Forbes.com, this article sparked a lot of interaction on our social media outlets, and we think it is an important one: Business Intelligence (BI) Isn’t Very Intelligent, Yet. Yes, big companies talk about BI like they know what is going on. Fact is, very few companies are doing predictive analytics, and most are focusing only on department-specific initiatives. When it comes down to what is actually happening in big companies–they are looking at reports that are produced manually and that represent data from the past.
Our personal favorite quote from this article is, “So companies use middleware and analytical tools like Tableau, Business Objects, Microstrategy and Cognos. They get results, but with a price in time and manpower. When different groups are on different spreadsheets, they spend a lot of meeting time debating who has the real version of the truth.”
Read the full article
Oct 21, 2014 | Application/Data Integration, BI Solutions, BI Strategy, BI Studies, BI System, Business Analytics, Business Budgeting, Business Intelligence Suite, Business Planning, Data Analysis, Infographic, Predictive Analytics, Technology and Trends |
A great infograhic from the Master of Science in Computer Information Systems program at Boston University. The BU researchers focused on: growth of business intelligence, management of data, decision-making and budgeting. Enjoy!
{Originally posted here}
