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Stephen Dale

Displaying Visual Information - 0 views

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    "Visual displays are extremely powerful tools, which means manipulation of these tools can spread inaccurate information and influence public perception. The sheer volume of images making their way through the Internet requires viewers to have a higher level of visual literacy than in years before in order to prevent manipulation.

    In this article you'll learn

    The types of displays that can be misleading
    What can be done to make visual displays less misleading"
Stephen Dale

Paper: How Deceptive Are Deceptive Visualizations? - Fell in Love with Data - 1 views

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    "How easy is it to deceive people with visualization?"
Stephen Dale

SharePoint is Back, Yammer... Not So Much - 0 views

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    As Yammer integrates more with Office 365 there seems little point, and little desire from Microsoft, to keep it as a separate product. This isn't to put Yammer down - it's a good tool, has many thankful customers and fulfills a real need for many. But it's clear that Microsoft sees Yammer features (or features inspired and powered by Yammer technology) as parts of Office 365.
Stephen Dale

How much can technology actually improve collaboration? | ZDNet - 0 views

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    Collaboration is a mindset and set of skills. It is also a messy and occasionally frustrating activity, and in the short term can even take longer than not collaborating. But long term, effective collaboration provides far stronger results. But to get there, we must first take a look at ourselves.
Stephen Dale

Top tips on developing your Employee Social Network strategy | simply communicate - 0 views

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    How do you meet the needs of your business and create a social intranet that people actually want to use? Read our 5 stage process to help you simply succeed.
Gary Colet

The Power of Quiet | Ideapod - 0 views

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    The ying and yang of introversion and extroversion
Gary Colet

Predictive analytics for sales and marketing - 0 views

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    Predictive analytics for sales and marketing. Transforming big data into customer knowledge
Stephen Dale

Amazon to Sell Predictions in Cloud Race Against Google and Microsoft - NYTimes.com - 0 views

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    Amazon Web Services announced that it was selling to the public the same kind of software it uses to figure out what products Amazon puts in front of a shopper, when to stage a sale or who to target with an email offer.

    The techniques, called machine learning, are applicable for technology development, finance, bioscience or pretty much anything else that is getting counted and stored online these days. In other words, almost everything.
Stephen Dale

Setting the stage to effectively visualize data - 0 views

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    Worth downloading and reading this paper. One abstract: "The ultimate goal is to enable data scientists,business analysts and other users "to extract the most information they can out of data as quickly as possible....For the business, we need answers now. The market is fixing the pace, so we have to give the best answer we can at the right time."
Gary Colet

http://www.vrg.cf.ac.uk/Files/2014_JPS_What_Works.pdf - 0 views

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    How to achieve more effective services - the evidence ecosystem
Stephen Dale

How Michigan State University Calculates Likelihood of Philanthropic Engagement - 0 views

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    Michigan State University has over 450,000 alumni around the world. The school's University Advancement department sought to create a representation of alumni and donor sentiment and likelihood of philanthropic engagement based on data gathered from social media. However, these analyses often took weeks to process, limiting the school's ability to gather valuable insights in a timely manner.

    This case study describes how MSU leveraged business intelligence and predictive analytics to gain deep insight into an individual alum's potential to give, resulting in the following positive results:

    -An annual ROI of 55%
    -An average annual benefit of $34,434
    -And more

    The case study purports to show how organisations can identify new opportunities for revenue generation by embracing a BI and predictive analytics strategy.
Stephen Dale

Digital hives: Creating a surge around change | McKinsey & Company - 0 views

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    "Here we present four specific approaches to the creation of what we call digital "hives"-electronic hubs bristling with collective activity and designed to solve a particular problem or set of problems, to drive new habits, and to encourage organizational change (exhibit). Digital tools to facilitate networking and collaboration propel these "horizontal" cascades, which at their best can weave new patterns of engagement across geographic and other organizational boundaries. In this way, they make it possible to have new conversations around problem solving, unlock previously tacit knowledge, and speed up execution.
    "
Stephen Dale

Power to the new people analytics | McKinsey & Company - 1 views

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    McKinsey have developed an approach to retention: to detect previously unobserved behavioural patterns, they combine various data sources with machine-learning algorithms. Workshops and interviews are used to generate ideas and a set of hypotheses. Over time they collected hundreds of data points to test. Then ran different algorithms to get insights at a broad organisational level, to identify specific employee clusters, and to make individual predictions. Finally they held a series of workshops and focus groups to validate the insights from our models and to develop a series of concrete interventions.

    The insights were surprising and at times counterintuitive. They expected factors such as an individual's performance rating or compensation to be the top predictors of unwanted attrition. But analysis revealed that a lack of mentoring and coaching and of "affiliation" with people who have similar interests were actually top of list. More specifically, "flight risk" across the firm fell by 20 to 40 percent when coaching and mentoring were deemed satisfying.
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    McKinsey have developed an approach to retention: to detect previously unobserved behavioural patterns, they combine various data sources with machine-learning algorithms. Workshops and interviews are used to generate ideas and a set of hypotheses. Over time they collected hundreds of data points to test. Then ran different algorithms to get insights at a broad organisational level, to identify specific employee clusters, and to make individual predictions. Finally they held a series of workshops and focus groups to validate the insights from our models and to develop a series of concrete interventions.

    The insights were surprising and at times counterintuitive. They expected factors such as an individual's performance rating or compensation to be the top predictors of unwanted attrition. But analysis revealed that a lack of mentoring and coaching and of "affiliation" with people who have similar interests were actually top of list. More specifically, "flight risk" across the firm fell by 20 to 40 percent when coaching and mentoring were deemed satisfying.
Gary Colet

Getting big impact from big data | McKinsey & Company - 0 views

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    Data analytics will no yield results if the output is mistrusted, or if the organisation is not geared-up to respond. 
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