How artificial intelligence will shape the future of business

From the boardroom at the office to your living room at home, artificial intelligence (AI) is nearly everywhere nowadays. Tipped as the most disruptive technology of all time, it has already transformed industries across the globe. And companies are racing to understand how to integrate it into their own business processes.

AI is not a new concept. The technology has been with us for a long time, but in the past, there were too many barriers to its use and applicability in our everyday lives. Now improvements in computing power and storage, increased data volumes and more advanced algorithms mean that AI is going mainstream. Businesses are harnessing its power to reinvent themselves and stay relevant in the digital age.

The technology makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. It does this by processing large amounts of data and recognising patterns. AI analyses much more data than humans at a much deeper level, and faster.

Most organisations can’t cope with the data they already have, let alone the data that is around the corner. So there’s a huge opportunity for organisations to use AI to turn all that data into knowledge to make faster and more accurate decisions.

Customer experience

Customer experience is becoming the new competitive battleground for all organisations. Over the next decade, businesses that dominate in this area will be the ones that survive and thrive. Analysing and interpreting the mountains of customer data within the organisation in real time and turning it into valuable insights and actions will be crucial.

Today most organisations are using data only to report on what their customers did in the past. SAS research reveals that 93% of businesses currently cannot use analytics to predict individual customer needs.

Over the next decade, we will see more organisations using machine learning to predict future customer behaviours and needs. Just as an AI machine can teach itself chess, organizations can use their existing massive volumes of customer data to teach AI what the next-best action for an individual customer should be. This could include what product to recommend next or which marketing activity is most likely to result in a positive response.

Automating decisions

In addition to improving insights and making accurate predictions, AI offers the potential to go one step further and automate business decision making entirely.

Front-line workers or dependent applications make thousands of operational decisions every day that AI can make faster, more accurately and more consistently. Ultimately this automation means improving KPIs for customer satisfaction, revenue growth, return on assets, production uptime, operational costs, meeting targets and more.

Take Shop Direct for example, which owns the Littlewoods and Very brands. This approach saw Shop Direct’s profits surge by 40%, driven by a 15.9% increase in sales from Very.co.uk. It uses AI from SAS to analyse customer data in real time and automate decisions to drive groundbreaking personalisation at an individual customer level.

AI is here. It’s already being adopted faster than the arrival of the internet. And it’s delivering business results across almost every industry today. In the next decade, every successful company will have AI. And the effects on skills, culture and structure will deliver superior customer experiences.

Author: Tiffany Carpenter

Source: SAS

How SAS uses analytics to help with the covid-19 vaccination process

The management of the COVID-19 vaccination program is one of the most complex tasks in modern history.  Even without the added complications of administering the vaccine during a pandemic, the race to vaccinate the populations who need it most all while maintaining the necessary cold-storage protocols, meeting double dose requirements, and still convincing populations of the vaccine safety, is daunting.

The vaccines available today are unlikely to be available in sufficient quantities to vaccinate the entire population in the near term, which creates the need for nimble, data-driven strategies to optimize limited supplies.

Analytics can be used to:

• Identify the location and concentration of priority populations.
• Monitor the relative adequacy of providers capable of vaccinating critical populations.
• Measure changes in need and demand patterns to optimize supply-chain strategies.
• Track community-based transmission and efficacy.

The storage and transportation of the vaccine is a complex logistical exercise, requiring coordination among governments and providers and the safe transport and storage of vaccines from manufacturers to vaccination sites.

Using analytics to shape strategy and execution

Since the pandemic’s beginning, SAS has partnered with customers in using analytics to:

• Monitor the spread of infection.
• Model future outbreaks.
• Uncover relevant scientific literature.
• Share real-time health insights.
• Optimize supply chains and medical resources.

These same analytical strategies can be used for vaccination programs. Why? Because analytics based on trusted data drives the best decisions. Below of some examples of what we mean.

Develop immediate and long-term vaccination strategies

SAS can help you create a data-driven strategy to identify and estimate critical populations that will benefit the most people. Governments have struggled to balance the need to create an orderly, risk-driven prioritization strategy while quickly administering all of the doses they have been allocated. Integrating data to calculate the size of prioritized populations in given geographic areas enables a data-driven vaccine allocation strategy that maximizes throughput and minimizes wasted dosages. Locating and estimating the size of these populations will be critical to developing an effective allocation strategy. This complex task can be fraught with technical challenges; for instance, creating an analytically valid estimation that identifies targeted populations across data sources.

To succeed, governments and health agencies will need to integrate data to identify critical populations, enable populations to be further subset to accommodate unknowns in vaccine supply, and model vaccination impact on priority outcomes. Given the variety of public and private organizations collaborating on this response, the best solution will drive open, transparent communication across diverse agencies.

Visual analytics is paramount because showing priority population data on maps can also speed strategy development. Using proximity clustering and hot-spotting technology, leaders can identify population densities to ensure adequate vaccine supply. Epidemiological models can help ensure continued situational awareness, so that prioritization and allocation approaches don’t become reliant on point-in-time data, but are instead part of a continuous-learning system that is responsive to on-the-ground changes in the pandemic.

Monitor vaccination capacity and adverse events

Identifying and recruiting enough providers to ensure sufficient access to COVID-19 vaccines (especially once supplies increase) will be crucial. SAS has experience working with government health agencies to monitor the adequacy of health care provider networks, a skill set and technology base that can provide agencies with an evidence-driven view of vaccine administration capacity and vaccination goals.

We work with commercial partners worldwide to augment the public health workforce to meet rising demand for vaccines. Related data such as storage capacity and throughput can be calculated and included for a fuller understanding of network adequacy.

As more data is collected regarding adverse events, SAS continues to help with health surveillance and research for many national health regulatory agencies today.

Optimize supply chain strategies

Health and human service agencies are being asked to allocate vaccine supply based on a range of complex, interrelated factors that include populations served and providers’ capability for storing and refrigeration. Optimizing these distribution strategies while facing fluctuating supplies, evolving need and changing provider enrollments will require a strong data and analytic approach.

SAS offers end-to-end supply chain analysis to assist agencies in an efficient, coordinated vaccine distribution response. By capturing inventory, demand, capacity and other related data across the distribution chain, you can create models that determine how agencies can optimize allocation strategies while accounting for the dynamic nature of pandemic outbreaks. The outcome is a set of flexible, adaptable plans for vaccination processing, inventory monitoring and distribution.

Dose administration analytics

Vaccination administrators must report certain data elements in near-real time (through electronic health records or directly via state immunization information systems). This information is a critical tool in creating rapid-response analytics that can guide decision making and future planning. Unfortunately, long-term underinvestment in our public health IT infrastructure has led to significant data quality challenges and weak reporting capabilities, which collectively prevent a data-driven vaccination strategy.

Our data management solutions can assist agencies in creating a trusted, consolidated vaccination record. This includes automating tedious and manual processes such as data preparation, data integration and entity resolution to provide analysts more time for treatment and vaccination efforts. With this reconciled vaccination data, SAS can provide analytics to help agencies:

• Predict evolving resource needs across jurisdictions such as states, regions and countries to optimize allocation strategies.
• Monitor uptake to help ensure alignment with anticipated need, provider requests and vaccine distributions.
• Analyze unexpected gaps in vaccination administration to guide outreach and engagement efforts.
• Anticipate barriers to delivering second doses.
• Gain insights on changes in susceptibility, rate of transmission, status population immunity, etc.

Managing a cold chain for biologics

In the US, the CDC has updated the Vaccine Storage and Handling Toolkit to outline the proper conditions for maintaining an effective COVID-19 vaccine under cold-chain processes. Cold chain is a logistics management process for products that require specific refrigerated temperatures from the point of manufacturing through distribution and storage until the vaccine is administered. But how do you collect data along the chain to ensure product safety? New internet-connected sensors now travel along with the vaccines. Collecting and analyzing data like that allows administrators to monitor, track and optimize distribution strategies in this multi-layered and complex vaccine rollout.

The path forward

As you read this, shipping and logistics companies are recording data on vaccine temperature and location.  Governments are rapidly transforming themselves into organizations capable of allocating, distributing and administering vaccines and their necessary components at massive scale. Retailers (pharmacies) are implementing customer contact programs to help track, administer and verify vaccinations.

The coordination across these various public and private companies is critical for a successful vaccination program. Even though the scale of this operation is historic, the sub-components of the process can be likened to other large, data-driven strategies.

Author: Steve Kearney

Source: SAS

Voor toekomstige en praktiserende data scientists zijn er weinig mogelijkheden om officiële papieren te halen voor hun werkveld. SAS introduceert daarom de SAS Academy for Data Science. Voor Europese deelnemers gaat deze opleiding in september van start in Nederland. In het programma van de SAS Academy for Data Science wordt kennisontwikkeling voor technologieën als big data, advanced analytics en machine learning gecombineerd met essentiële communicatieve vaardigheden voor data scientists.

“De sleutel om concurrentievoordeel te behalen uit de enorme hoeveelheden data zijn analytics en de mensen die ermee kunnen werken”, vertelt Pascal Lubbe, Manager Education bij SAS. “De Academy for Data Science biedt kansen aan professionals die starten op dit gebied of hun capaciteiten verder willen ontwikkelen. Ook kunnen bedrijven een speciaal in-house programma laten ontwikkelen voor hun medewerkers. De studenten werken voor de opleiding met SAS-software, maar zijn bij het afronden van de opleiding breed gekwalificeerd als data scientist.”

De tracks van de SAS Academy for Data Science bestaan uit verschillende elementen; een klassikale instructie, een hands-on case of team project, certificeringsexamens en coaching. Iedere track neemt zes weken in beslag. Door de examens succesvol af te leggen kunnen studenten een of twee diploma’s behalen: SAS Certified Big Data Professional en/of SAS Certified Data Scientist.

Krachtige mix

De SAS Academy for Data Science onderscheidt zich door de krachtige mix van praktische ervaring met analytics, computing, statistics en zakelijke kennis en presentatievaardigheden. De lessen worden geleid door experts, begeleid door een coach en studenten krijgen de beschikking tot de SAS-omgeving.

De opleiding kent twee levels: in het eerste level worden studenten opgeleid om de ‘SAS Certified Big Data Professional credential’ te behalen. Ze leren hoe ze big data kunnen beheren en opschonen en de data te visualiseren met SAS en Hadoop. Level 2 is de opleiding tot gecertificeerd SAS Data Scientist, met predictive modeling, machine learning, segmentatie en text analytics. Ook wordt ingegaan hoe SAS samenwerkt met open source programmeertalen. En minstens zo belangrijk: studenten leren hoe ze met onmisbare communicatieve capaciteiten betekenis geven aan data voor stakeholders.

Analytics-talent

“SAS is bijna 40 jaar actief in het data science-vakgebied waarbij we telkens hebben ingespeeld op de behoeften van klanten. Nu vragen onze klanten om analytics-talent”, zegt Jim Goodnight, CEO van SAS. “Werkgevers vertrouwen gecertificeerde SAS-professionals niet alleen voor het beheren en analyseren van de data, maar ook om de betekenis en gevolgen voor de business te begrijpen. Door de analyseresultaten duidelijk te communiceren kunnen betere beslissingen genomen worden.”

Source: Emerce

SAS: The importance of customer experience to keep improving as a company

Did you know the first SAS^® Users Group event took place before SAS was incorporated as a company? In 1976, hundreds of early SAS users gathered in sunny Kissimmee, FL to share tips and offer feedback before SAS was even officially a company. Our users have continued to influence the direction of our products ever since. And we continue to be keenly interested in the customer experience.

I’ve been reflecting on my time at SAS and how I’ve seen that commitment grow over the last few years. I remember my first SAS users group conference in 2001 when I was a new product manager at SAS. Attendees told me how much it meant to them that we were there to listen and learn about the ways they used SAS products and the value SAS had for their organizations. The peer interaction that happens in the SAS community continues to inspire me, and I consider that peer interaction to be an essential ingredient of the SAS customer experience, too.

Since that time, our customer experience program has grown roots and become a key driver in the decisions we make as a company. The feedback and input we receive from our users fuels our growth and allows us to focus on the products, services and overall experience that matter most to you.

Consider this example. Recently, our newer users told us that it can be overwhelming to get started with SAS and to find all the resources they needed to improve their SAS skills. We understand there can be a learning curve with any new software and we wanted to make it easier for anyone, from students to professional data scientists, to reap value from SAS immediately.

In response to this feedback, we created a SAS Starter Kit and a SAS Communities space just for new users. The starter kit makes it easy to access free training, support and services. And the communities space pairs new users with SAS pros who are business intelligence experts and enjoy sharing their experience and answering even the most basic questions.

Author: Randy Guard

Source: SAS