Data aids, not replace judgement
Data is a tool and means to help build a consensus to facilitate human decision-making but not replace it. Analysis converts data into information, information via context leads to insight. Insights lead to decision making which ultimately leads to outcomes that brings value. So, data is just the start, context and intuition plays a role.
[ DATA SCIENCE Q&A]
Q:What is POC (proof of concept)?
A: * A realization of a certain method to demonstrate its feasibility
* In engineering: a rough prototype of a new idea is often constructed as a proof of concept
Even in the age of big data, some numbers pertaining to women are glaringly missing: numbers on global maternal mortality rates are incomplete, statistics regarding women and unpaid work are flawed and conflict-related gender-based violence figures are lacking.
To begin tackling this problem from the bottom up, Data2Xâa joint project of the Clinton Foundation, the United Nations Foundation, the William and Flora Hewlett Foundation and the Bill & Melinda Gates Foundation that was first introduced in 2012âannounced new regional and topical partnerships at a press event in New York City Monday. By partnering with a multitude of organizations, the Data2X platform says it hopes to start a âgender data revolution,â which will allow policymakers to recognize problems more clearly and better create informed policy.
âI have been championing the rights of women and girls around the world and here at home for many years,â former Secretary of State Hillary Clinton said at the event, âand I got tired of seeing…foreign leaders, business executives, even senior officials in our own government…smile and nod when I raised these issuesâ¦ âOh right, I knew she was going to raise women and girls, I will just sit here and smile, it will pass, and then weâll talk about really important things.ââ
Clinton said this scenario played out countless times over the years and inspired her involvement in the Data2X project. âYou canât understand what the problem is if you donât have a good grasp of what the facts and figures are,â she said.
The new partnerships will focus on six categories of data:
Civil Registration and Vital Statistics (CRVS)
Civil registration, which is the continuous recording of vital life events like birth, marriage and death, is incomplete around the world. To address missing records, Data2X is teaming up with organizations in Africa and Asia, like the United Nations Economic Commission for Africa and U.N. Economic and Social Commission for Asia and the Pacific.
Though the births of girls and boys are almost equally registered globally, ensuring women an individual legal identity by maintaining a quality CRVS system could provide a better account of early and forced marriages and help women retain their share of assets in the event of a divorce.
Womenâs Work and Employment
In partnership with the International Labour Organization, Data2X is redefining what is considered work to include unpaid work, including work for the home. Expanding the work framework will give the global community a better idea of how women contribute to the economy.
For example, Clinton said that data collection and analysis in India showed that women spend an average of six hours per day doing unpaid labor. If these women were to participate in the formal workforce at the same rate as men, she contended, Indiaâs gross domestic product would increase by $1.7 trillion.
Supply Side Data on Financial Services
Women face both financial service access and service gaps globallyâthey have trouble proving their business case and struggle to get the resources they need. But data pertaining to these experiences with financial services is not kept. âIf you canât measure it, you canât manage it,â former New York City mayor Michael Bloomberg told the audience.
Now, the Global Banking Alliance for Women and the Inter-American Development Bank are teaming up to incentivize collection of this data as a first step to close the gender gap in financial services. Proposals for how to support this venture will be presented at the Global Data Symposium in September 2015.
Womenâs Subjective Well-Being and Poverty
The lack of gender-segregated data has clumped womenâs poverty with household poverty, meaning the exact poverty numbers for women and girls is unknown. Data2X is joining with the Government of Mexicoâs National Institute of Statistics and Geography (INEGI), which already has a comprehensive approach to discovering gender differences in well-being. One of INEGIâs tactics to understanding womenâs subjective well-being is analyzing Twitter feeds to determine who and where posts with positive sentiments are coming from.
Big Data and Gender
Data2X is collaborating with U.N. Global Pulse, U.N. Women and academic researchers to analyze cell phone data usage patterns to infer womenâs socioeconomic welfare, mobility patterns and financial activity. The project also plans to use remote sensors to reveal epidemiological trends and provide information on womenâs access to services.
Improved Gender Data on U.S. Foreign Assistance Programs
Not only does Data2X want more complete data to be included when setting the global agenda, but the project aims to inform U.S. development policy and investment. In conjunction with the U.S. Presidentâs Emergency Plan for AIDS Relief and Millennium Challenge Corporation, sex and age specific data will be released to ensure those most in need of aid are reached and to assess the impact of current U.S. assistance programs.
Data collection, Clinton said, could âbuild a case strong enough to convince the skeptics, based on hard data and clear-eyed analysis, that creating opportunities for women and girls across the globe directly supports everyoneâs security and prosperity, and therefore should be an enduring part of our diplomacy and development work.
Ever cared to know what it takes to be fortune 100 CEO? What it took, how their career path progressed? If yes, thanks to N2Growth for an amazing infographics. It spreads some lights on how these CEOs grew up and what differentiates them and put them almost in the similar silos among themselves. Take a peak at the infographics and see what it will require to be a CEO, how you could set your path to such progression. Surely, a good place to start if you are not running already.
Explore more infographics like this one on the web’s largest information design community – Visually.
Hospitals are focusing on improving the patient experience. Â The Centers for Medicare & Medicaid Services (CMS) will be usingÂ patient feedback about their care as part of their reimbursement plan for Acute Care Hospitals.Â Under theÂ Hospital Value-Based Purchasing ProgramÂ (beginning in FY 2013 for discharges occuring on or after October 1, 2012),Â CMS will make value-based incentive payments to acute care hospitals, based either on how well the hospitals perform on certain quality measures or how much the hospitals’ performance improves on certain quality measures from their performance during a baseline period. Â The higher the score/greater the improvement, the higher the hospital’s incentive payment for that fiscal year.
Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS)
Patient feedback is being collected using a survey known asÂ HCAHPSÂ (Hospital Consumer Assessment of Healthcare Providers and Systems).Â HCAHPS (pronounced “H-caps“)Â is a national, standardized survey of hospital patients and was developed by a partnership of public and private organizations. I recently wrote about HCAHPS in a prior post.Â The survey asks a random sample of recently discharged patients about important aspects of their hospital experience.Â The data set includes patient survey results for over 3800 US hospitalsÂ onÂ ten measures of patients’ perspectives of care.
Map of US Hospitals and their Patient Experience Ratings
As consumers of healthcare, you need to understand how well hospitals are delivering a good patient experience. Using the HCAHPS data, I developed a map to help you easily identify and understand how your hospital ranks in patient experience. In the map below (see Figure 1), the colors are based on the patient advocacy index I created (average of top box scores for two questions: Overall hospital quality rating and Recommend hospital.Â In my prior analysis, this Patient Advocacy Index (PAI) had a reliability estimate (Cronbach’s alpha) of .95, suggesting that it is a reliable measure.
The colors for each hospital are based on their PAI (red = 0 – 20; purple = 21-40; yellow = 41-60; blue = 61-80; green = 81-100). If you click on one of the buttons, you will see detailed information about the patient experience metrics (if survey data were collected for that hospital) as well as response rates, sample sizes and other notes (if available). NOTE: Some hospitals do not have any ratings (those are typically red).
Telcos need to find ways to process and analyse large amounts of customer data quickly and in real-time in order to create new revenue streams and engage with customers effectively.
So said Rams Srinivasan, telco industry value engineer at SAP Middle East and North Africa, speaking yesterday at the SAP Forum in Sandton.
According to Srinivasan, telecommunications companies are struggling to break through and engage with their customers because of legacy systems that make it difficult to have a complete view of customers and deliver efficient service across multiple channels.
He explains telcos must adapt in order to attract and retain a new generation of customers who are highly informed, socially connected and very mobile.
Telcos can track conversations on social media to understand what customers are saying about their products and services, and take proactive measures to defend their brand image and reputation in real-time using analytics, said Srinivasan.
Operators are looking for new ways to increase revenues and profits â but few have shown the know-how needed to make the most of new digital channels, said Srinivasan.
According to a Frost & Sullivan report, with an increasingly saturated market, and declining traditional mobile voice and SMS revenues, operators are exploring new business models as part of their growth strategy.
Also, the declining cost of devices is driving the ecosystem to explore new possibilities through connected devices, adds Frost & Sullivan.
By analysing varied and unformatted digital data from digital channels like social media and through mobile phones, telcos can reveal new sources of business economic value and provide fresh insights into customer behaviour, said Srinivasan.
He pointed out operators need a strategy to accurately mine and analyse both structured and unstructured data. This will give them an opportunity to get deeper insights into customer behaviour, their service usage patterns and preferences in real-time.
“To be able to remain relevant and competitive in a world where technology giants like Google, Facebook and Apple are causing disruption, telcos need to engage with the customer in a better way by improving operational efficiency through data analytics.”
Today’s lifestyle demands continuous connectivity and excellence of service, leading to a highly competitive and diverse market, said Srinivasan. There are more digital connected devices than human beings and the numbers are growing.
Another new source of revenue for telcos is selling insights about customers to third parties, said Sherif Hamoudah, industry head, telecom, at SAP Africa, Middle East and Pakistan.
By leveraging the data stream, telecommunications companies can tailor their marketing campaigns to individual customers using location-based and social networking technologies, he said. Also, big data offers event-based marketing campaigns that use geolocation and social media, allowing differentiated response.
Big data offers telecom operators a real opportunity to gain a much more complete picture of their operations and customers, and to further their innovation efforts, he said.
It suggests that 97,000 apps are on sale in the mobile health sector, which includes tracking apps but also apps that help patients make appointments and keep track of medication.
It predicts that by 2017 more than 1.5 billion people around the world will be using these apps, generating total revenues of Â£14.5bn ($23bn).
In the EU alone it is estimated that these apps and gadgets could reduce health costs by Â£77.5bn (99bn euros).
Most of the growth has come from start-ups that saw the potential early and now face a competitive onslaught from the big technology companies.
Five years ago French firm Withings launched its wireless scales – the device feeds data back to you, by plotting a graph of your weight over time.
“It started with the scales because we thought that was the one dimension that would make sense for people to track,” Julien De Preaumont, chief marketing officer at Withings, says.
“The first rule of data is to make people aware of their health to make them realise how their weight is evolving.
“The curve reveals the impact of life changes, it will show how a divorce, a diet or a new job will affect your weight.”
After the scales took off, Withings launched wearable gadgets that track your movement, heart rate, blood pressure and sleep.
The company maintains that the data it collects belongs to the user only.
But it has published reports revealing the most obese cities in France and the US, as well as another study showing sleep patterns across Europe.
Withings says this does not compromise the privacy of the individual user’s data because it is aggregated and anonymised.
While Withings has grown to be a global business, US firm Fitbit has also seen its business thrive beyond its borders.
Founded in 2007 Fitbit offers wireless scales, wearable devices that monitor movement, heart rate, sleep and blood pressure, and is evangelical about the motivating power of targets and data on our health.
Fitbit also offers companies its gadgets and software for corporate use.
Its “corporate wellness” scheme started in the US and companies can use the scheme to get a rebate on their taxes.
Clients so far include blue-chip multinationals such as BP and Time Warner.
Employees can sign up and different divisions can compete against each other over the number of steps taken or stairs climbed.
“The key is to make the product sticky,” says Gareth Jones from Fitbit, and the key to that is gamification.
“Our software incorporates challenges like daily showdowns and weekend warriors which motivate people and keep them coming back.”
But should employees be worried about sharing their every movement, 24 hours a day with a corporate scheme?
“We don’t have data about this, it’s very much a choice of the individual as to whether they sign in for the programme. We see the result of that as purely the people who agree to participate and the people who don’t,” says Mr Jones.
“We might share with the corporate administrator information that 50 people have been invited and 45 have said yes. How the company uses that information is up to the company.”
‘In the hands of the people’
The potential of all the data that is now being collected is huge, both for business and for public health bodies.
Imagine going to the doctor and being able to show them how much exercise you do, how much sleep you get and your blood pressure for the last year.
While the insurance industry is using mobile applications for arranging appointments and giving health information, they are yet to fully embrace the use of wearable devices and the data they collect, though it is a development that could completely change their business as many research papers suggest.
Meanwhile the use of the data for medical research is also a long way off.
Professor John Newton from Public Health England would like to see a more joined-up approach.
“We’ve got the world of apps, a huge investment from the technology companies, but the healthcare sector hasn’t made the link,” he says.
“If you were able to make the link between a hospital service like a diabetic clinic with a patient’s mobile phone data, they could tell immediately whether that person’s diabetes was going out of control.”
His message is clear: “Put the data into the hands of the people who can use it to make a difference.”
Like all the new data that is being recorded and analysed the possibilities are massive but the ethical and privacy issues surrounding our personal information will not go away quickly.
Originally posted via “Every step you take: Who owns our mobile health data?”
Customer feedback provides useful information about the health of the customer relationship. Relationship and transactional surveys, commonly used to capture customer feedback, are used to assess and improve that health. While customer feedback metrics provide great value in and of themselves, when used with other types of business data, they can address meaningful business questions:
Are the customer feedback metrics predictive of future financial performance and business growth?
Do customers who report higher loyalty spend more than customers who report lower levels of loyalty?
Where do we set operational goals to ensure we maximize customer satisfaction?
Does employee training help improve the customer experience?
To answer these questions, companies look to a process called business linkage analysis. Download the free paper here.
Fix the Culture, spread awareness to get awareness
Adoption of analytics tools and capabilities has not yet caught up to industry standards. Talent has always been the bottleneck towards achieving the comparative enterprise adoption. One of the primal reason is lack of understanding and knowledge within the stakeholders. To facilitate wider adoption, data analytics leaders, users, and community members needs to step up to create awareness within the organization. An aware organization goes a long way in helping get quick buy-ins and better funding which ultimately leads to faster adoption. So be the voice that you want to hear from leadership.
[ DATA SCIENCE Q&A]
Q:What is statistical power?
A: * sensitivity of a binary hypothesis test
* Probability that the test correctly rejects the null hypothesis H0H0 when the alternative is true H1H1
* Ability of a test to detect an effect, if the effect actually exists
* Power=P(reject H0|H1istrue)
* As power increases, chances of Type II error (false negative) decrease
* Used in the design of experiments, to calculate the minimum sample size required so that one can reasonably detects an effect. i.e: how many times do I need to flip a coin to conclude it is biased?
* Used to compare tests. Example: between a parametric and a non-parametric test of the same hypothesis