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New on the Anticipate Change Blog: Data Storytelling for Disruptors

"Disruptive innovations have become common in these 'postnormal' times. Organisations that seek to be disruptive are fusing big data analytics with storytelling to nurture better business cultures. Narratives and data stories encourage participation in innovation. We share our recent experience and insights into data storytelling and disruptive innovation."

#AnticipateChange   #BigData   #Storytelling   #DriveInnovation   #DisruptiveInnovation   #Analysts   #SelfService  

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

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How to Tell Stories with Data (Really)

Here's an interesting talk by Edward Segel at the January 2012 KDMC digital storytelling workshop. He shares insights from his paper (written in collaboration with Jeffrey Heer) entitled Narrative Visualization: Telling Stories with Data. See here: http://vis.stanford.edu/papers/narrative

He begins by explaining the growth of data and how no one knows what to do with it all because it's simply too much. Data visualisation is said to make patterns in the data "perceptively digestible." He mentions four motivations behind the creation of "interactive visualisations": 1) for displaying an extensive analysis; 2) for personalisation to increase user's emotional engagement with a data set; 3) for showing a wide array of social responses and opinions; 4) for storytelling that guides users through the data in ways he fully describes in his talk. He then delves into the findings of his paper.

#DataVisualisation   #Storytelling   #Analysts   #Social  

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Job hunting the big data way

Recruiting firms are looking beyond the CV to how their applicants write sentences. Through text analytics they are making a better fit between company cultures and applicant personalities. They can also predict how long an employee is likely to stay with a job before moving on!  / #HumanResources   #TextAnalytics   #DataMining  

Citation: Nearly half of new recruits turn out to be duds within 18 months, according to one study, while two-thirds of hiring managers admit they've often chosen the wrong people. / #TodaysChallenges  
. . . 
"[I]nnovative personality tests are supplements to, not replacements for, big data analytics, many recruiters believe. / #BigData  
. . . 
Analysis of historic data from tens of millions of job applicants, successful or otherwise, is helping employers predict which new candidates are likely to be the best based on a comparison with the career paths, personalities and qualifications of previously successful employees. / #Analysts  

"Now we're able to use our own data to track how long candidates stay in a role before seeking new opportunities," says Geoff Smith, managing director of recruitment consultancy Experis. / #PredictiveAnalytics  
. . . 
San Francisco-based company Evolv found that long-term unemployed people perform no worse than those who have had more regular work.

It also found that prior work experience and even education are not necessarily indicators of good performance in some roles. / #Education  
. . . 
Our blogs, websites, Twitter rants and LinkedIn profiles reveal as much - if not more - about us than a semi-fictionalised CV.

"The days of keeping your personal and professional profiles separate are over," warns Experis's Geoff Smith.

"Social media is a great platform for individuals to demonstrate their expertise, experience and enthusiasm for their field of specialism. However, candidates need to be conscious of the online reputation they are building and the data trail they are leaving behind." / #Social  

Posted by +Dan Durrant w/ +David Pidsley 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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From Sentiment Analysis to Enterprise Applications

“My advice is about WHO should be adopting the use of sentiment technologies.  Give it to the people that run real metrics in the company.  If you let market research people control this tool, you will move too slowly.  If you give it to the social media engagement group, you will get no strategic value from it.  Give it to the operations people, who have to create better forecasts and design real-time key performance indicators for the business.  This is where the real strategic and tactical value lies for sentiment analysis.” - Marshall Toplansky, president of “mass opinion business intelligence” vendor WiseWindow

#Social   #TextAnalytics   #Analysts  

Posted by +Dan Durrant 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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Using big data to make better pricing decisions

Citation: It’s hard to overstate the importance of getting pricing right. On average, a 1 percent price increase translates into an 8.7 percent increase in operating profits (assuming no loss of volume, of course). Yet we estimate that up to 30 percent of the thousands of pricing decisions companies make every year fail to deliver the best price. That’s a lot of lost revenue. And it’s particularly troubling considering that the flood of data now available provides companies with an opportunity to make significantly better pricing decisions. For those able to bring order to big data’s complexity, the value is substantial.
. . . 
The key to better pricing is understanding fully the data now at a company’s disposal. It requires not zooming out but zooming in. As Tom O’Brien, group vice president and general manager for marketing and sales at Sasol, said of this approach, “The [sales] teams knew their pricing, they may have known their volumes, but this was something more: extremely granular data, literally from each and every invoice, by product, by customer, by packaging.”
. . .
To get sufficiently granular, companies need to do four things.

Listen to the data. Setting the best prices is not a data challenge (companies generally already sit on a treasure trove of data); it’s an analysis challenge. The best B2C companies know how to interpret and act on the wealth of data they have, but B2B companies tend to manage data rather than use it to drive decisions. / #Analysts   #DecisionMaking  
. . . 
Automate. It’s too expensive and time-consuming to analyze thousands of products manually. Automated systems can identify narrow segments, determine what drives value for each one, and match that with historical transactional data. This allows companies to set prices for clusters of products and segments based on data. Automation also makes it much easier to replicate and tweak analyses so it’s not necessary to start from scratch every time. / #Automation  
. . .
Build skills and confidence. Implementing new prices is as much a communications challenge as an operational one. Successful companies overinvest in thoughtful change programs to help their sales forces understand and embrace new pricing approaches. Companies need to work closely with sales reps to explain the reasons for the price recommendations and how the system works so that they trust the prices enough to sell them to their customers. Equally important is developing a clear set of communications to provide a rationale for the prices in order to highlight value, and then tailoring those arguments to the customer. Intensive negotiation training is also critical for giving sales reps the confidence and tools to make convincing arguments when speaking with clients. / #Sales   #HumanResources  
. . . 
Actively manage performance. To improve performance management, companies need to support the sales force with useful targets. The greatest impact comes from ensuring that the front line has a transparent view of profitability by customer and that the sales and marketing organization has the right analytical skills to recognize and take advantage of the opportunity. The sales force also needs to be empowered to adjust prices itself rather than relying on a centralized team. This requires a degree of creativity in devising a customer-specific price strategy, as well as an entrepreneurial mind-set. Incentives may also need to be changed alongside pricing policies and performance measurements. / #Managers   #Enterpreneurs  

#GrowIncome   #BigData  

Posted by +Dan Durrant w/ +David Pidsley 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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AP is going to automate quarterly earnings stories

Citation: The Associated Press announced in an advisory to customers today that the majority of U.S. corporate earnings stories for our business news report will eventually be produced using automation technology.

Here, Lou Ferrara, the AP managing editor who oversees business news, explains how this leap forward takes advantage of new technologies to free journalists to spend more time on things like beat reporting and source development while increasing, by a factor of more than 10, the volume of earnings reports for customers.
. . . 
We discovered that automation technology, from a company called Automated Insights, paired with data from Zacks Investment Research, would allow us to automate short stories – 150 to 300 words — about the earnings of companies in roughly the same time that it took our reporters.

And instead of providing 300 stories manually, we can provide up to 4,400 automatically for companies throughout the United States each quarter.
. . . 
We are going to use our brains and time in more enterprising ways during earnings season.
. .
Instead, our journalists will focus on reporting and writing stories about what the numbers mean and what gets said in earnings calls on the day of the release, identifying trends and finding exclusive stories we can publish at the time of the earnings reports.

#ArtificialIntelligence   #Automation   #Finance #FutureTechnologies     #SaveTime   cc  #Analysts   #USA  

Posted by +Daniel Durrant w/ +David Pidsley 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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More News Is Being Written By Robots Than You Think

Citation: Software is writing news stories with increasing frequency. In a recent example, an LA Times writer-bot wrote and posted a snippet about an earthquake three minutes after the event. The LA Times claims they were first to publish anything on the quake, and outside the USGS, they probably were.

The LA Times example isn’t special because it’s the first algorithm to write a story on a major news site. With the help of Chicago startup and robot writing firm, Narrative Science, algorithms have basically been passing the Turing test online for the last few years.

This is possible because some kinds of reporting are formulaic. You take a publicly available source, crunch it down to the highlights, and translate it for readers using a few boiler plate connectors. 
. . . 
Narrative’s approach can be applied elsewhere too. The firm recently launched an app that works with Google Analytics to transform raw website metrics (traffic, sources, referrals, demographics) into accessible, natural language reports. These could be useful in any business, a kind of automated analyst to help make sense of big data sets.

#ArtificialIntelligence   #Automation   #BigData   #FutureTechnologies  cc #Analysts   

Posted by +Dan Durrant w/ +David Pidsley 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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Data scientists are in demand for #Logistics projects

James A. Cooke, a journalist covering logistics, writes:

Although computers and software are powerful tools for facilitating analysis, a human expert is still needed to make decisions about what data to examine and how. "Data science is not a one-size-fits-all approach," says Larry Snyder, an associate professor at Lehigh University and co-author of the book Fundamentals of Supply Chain Theory. "So you can't just throw terabytes of data into an off-the-shelf system and ask it, 'What should I do?' It takes data and decision-making experts to convert raw data into useable information and ultimately, to make decisions." / #DecisionMaking #SupplyChain 
. . . .
Because so much raw information abounds in logistics, the discipline is considered to be particularly well suited to big data analysis. Logistics, by its nature, involves numerous data exchanges between multiple partners to make the supply chain flow, and there are piles of raw data sitting in all of those partners' systems. But it's not just traditional data systems that provide fodder for analysis. Big data analysis can encompass information gathered by sensors—say, on trucks or on packages in the warehouse. / #Logistics   #BigData   #InternetofThings  

The premise behind big data analysis is that if correlations can be made between all that raw data, users can gain a better understanding of why things happen and parlay those insights into process improvements. "Getting to root causes often requires analyzing data to understand correlations—what is related to what," says John Hagerty, a program director for big data at IBM. / #Analysts  

Posted by +Dan Durrant 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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Social messes and super wicked problems

Horn and Weber have a paper entitled New Tools for Resolving Complex Problems, with subtitle Mess Mapping and Resolution Mapping Processes. From the Executive Summary:

"Wicked Problems (equivalently, Social Messes) are seemingly intractable problems. They are composed of inter-related dilemmas, issues, and other problems at multiple levels society, economy, and governance. These interconnections—systems of systems—make Wicked Problems so resilient to analysis and to resolution.

"Wicked Problems include issues such healthcare in the United States and elsewhere, the AIDS epidemic and perhaps other emerging diseases, global climate change, pandemic influenza, international drug trafficking, terrorism, homeland security, and nuclear energy and waste."

www.strategykinetics.com/files/New_Tools_For_Resolving_Wicked_Problems.pdf

#DecisionMaking #Systems #Analysts

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Quotes from A Practitioner's Guide to #Business #Analytics
by Randy Bartlett

“Most people use statistics the way a drunkard uses a lamp post, more for support than illumination.” 

“Speed is the thing. We prefer a team that has a relative speed advantage over other virtues.” 

“Innovation tends to come in two flavors: (1) sudden and unexpected, and (2) planned, yet doggedly obtained.” 

“Innovation comes from the producer—not from the customer.” 

“opinion-based decision making, statistical malfeasance, and counterfeit analysis are pandemic. We are swimming in make-believe analytics.” 

“Corporations will continue to be awash in dirty data and filthy information.” 

“All revolutions are impossible till they happen, then they become inevitable.” 

#DriveInnovation   #DecisionMaking   #Analysts   #Collaboration  

http://www.goodreads.com/work/quotes/22957433-a-practitioner-s-guide-to-business-analytics-using-data-analysis-tools

Posted by +Dan Durrant 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com
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