Welcome to the latest edition of Analytical Thinking, a newsletter from the UK Business Analytics community providing snippets of insight on what people have been saying and how organisations have been using our capability over the last 2 weeks.
Within this edition, we have two different sections: Big data and Analytics. In the Big Data section, 5 articles explain how Big Data can be link to other topics such as Business Intelligence and Predictive Analytics. In the Analytics section, you will discover different ways that analytics has been adopted by CIOs and to optimise supply chains.
How Big Data Brings Business Intelligence And Predictive Analytics Together
This article argues that Big data is about to move BI and predictive analytics away from statisticians and data scientists and into the everyday life of business decision makers; imagining the world where a customer service advisor can make an independent decision on whether a problem customer is worth keeping or not. This article explains how big data is enabling the ever-elusive single view of the customer.
In the following article, you will find out more about the growing need of Decision Management, and especially data 2 decisions which is about moving from insight to action and moving to fact based decisions making.
Data To Decisions: The Intersection Of Big Data, Semantic Web, And BI
Organizations have faced a constant technology arms race to achieve basic levels of decision management. From data warehousing, to data marts, to reporting tools to BI, and now Big Data, organizations and leaders have been inundated with technology fads. While the latest buzz in technology may come and go, Constellation Research believes organizations seek a path from data to information to insight to action. This path from Data to Decisions drives the science and discipline behind decision management. This article details the growing need for what it refers to as decision management.
In previous editions of Analytical Thinking, we were talking about Big Data and also Big Data Analytics, but can you tell the difference between those two? The next article might give you some insights about this question.
The Difference Between Big Data And Big Data Analytics
If you scan any other business innovation publication, you are sure to see “Big Data” thrown around incessantly. However, you will also find the term Big Data Analytics used as well. Sometimes the terms are used interchangeable, and in the same article. But they are not the same thing. Basically, the difference comes down to the term “Big Data” referring to the new techniques that have been developed to store enormous amounts of data and “Big Data Analytics” referring to the algorithms and programs that mine these massive data stores. Only when you combine them can you can tap the potential of all this data we are capturing and storing.
In the following article, you will discover how Big Data and Analytics are transforming Automotive and Machinery industries.
Big Data In Automotive And Machinery: Using Analytics To Deliver Better Products And A More Fulfilling Driver Experience
The automotive industry, including cars, trucks, buses, semi-trailers, farm equipment, and construction equipment, is on the cusp of a Big Data revolution. Automotive companies have the opportunity to leverage new sources of Big Data to accelerate product design, improve vehicle performance and enhance the driver experience. In this article, you will discover few examples of how Big Data is transforming the automotive industry thanks to new detailed data sources coupled with advanced analytics.
The last article of this Big Data section explains the Big Data challenge, which is to reveal the intelligence and causality across the business functions for strategic insight. This will allow companies to see a more comprehensive picture of their product and product variants based on actual customer-buying patterns.
The Big Value In Big Data: Seeing Customer Buying Patterns
According to Gartner, unstructured and structured data held by enterprises continues to grow at explosive rates. However, volume and velocity of data – what the business world is beginning to understand as the “Big Data Problem” – are becoming less of an issue than the variety of data. The core question is this: does big data actually solve real-world business problems? The short answer is yes – and in this article, here is a real world example of how leveraging Big Data can solve the complexity around product proliferation by helping companies align product offering and supply chain based on customer-buying patterns.
In the first article of this second section of this edition, Analytics, you will discover that supply chain officers definitely see advantages from the use of predictive software.
Supply Chain Execs See Benefits In Predictive Software
Seventy-five percent of the 191 top supply chain officers who took part in a June 2012 Aberdeen Group survey said their decision making could be improved with the use of proper analytics, defined as special software tools built to discern patterns or trends in supply chain and logistics operations. Respondents to the research firm's survey said predictive analytica software would help them to achieve cost savings, increase profitability, and differentiate their customer service from that of competitors. This article explains that supply chain executives believe they could make smarter decisions and increase profitability if they were armed with the right analytical software.
The last article of this edition will give you details and explanations about the need of analytics, cloud and mobile in order to be up to date regarding customer’s change of behaviour.
Why CIOs Are Quickly Prioritizing Analytics, Cloud And Mobile
Customers are quickly reinventing how they choose to learn about new products, keep current on existing ones, and stay loyal to those brands they most value. The best-run companies are all over this, orchestrating their IT strategies to be as responsive as possible. This article argues that CIOs need to be as strong at strategic planning and execution as they are at technology and that many are quickly prioritizing analytics, cloud and mobile strategies to stay in step with their rapidly changing customer bases.
We hope that you have enjoyed reading this fourteenth edition of Analytical Thinking and hope that it has provided you with a good insight into some of the value that is currently being realised through Business Analytics solutions. If you would like to find out more about our services and propositions then please contact Nigel Lewis or Jon Chadwick. If you have any suggestions on how we can improve this newsletter or if you have received it via a colleague and would like to subscribe then please contact Charlotte Skornik. If you spot an article that is Business Analytics related then we'd like to know about it, please submit it to Charlotte Skornik, and it may appear in the next edition of Analytical Thinking