No digitalization without analytics!

There is a major push towards digitalization in the Nordic region and the healthcare sector is no exception. The Nordic Ministries responsible for healthcare run several large nationwide healthcare projects. I have experienced that the vendor industry challenge the digitalization approach because it limits opportunities offered by a wider healthcare ecosystem.

Industry growth through digitalization

Should Nordic Ministries aim at “end to end” system development of new nationwide healthcare systems or should the government enable industry development through a digitalization initiative?  The first approach is may be more straightforward and traditional, but it will limit new industry initiatives, innovation and industry development. The latter approach represents greater uncertainty, but it will most probably enable innovation, creativity and industry growth.

The birth of connected patients

We believe that the Nordic Ministries should focus on architecture, principles, standards and governance. This should in turn be communicated to a competitive and creative market of established companies and entrepreneurs. The exponential growth of data enabled by personal wearables with sensor technologies, networks and the processing power technology will give birth to the connected patient. Confidential information about patients must be analyzed and shared within a trusted network of healthcare professionals in order for digitalization to work, and the Nordic Ministries should facilitate a platform for connected patients.

Automation through analytics

One central component in an architecture that enables digitalization is analytics. Analytics enables the power to know which in turn enables correct decisions. I argue that analytics is the most important component for digitalization to work because analytics and analytical models enables process automation. With automation comes efficiency, speed and enormous savings compared to manual work. Analytics will increase patient safety because computers can process more variables than humans can. Some argue that it is unethical to rely only on doctors' opinions. These topics are to be addressed on our Health Analytics Conference taking place in Norway, September 2016.

Content is key

Content management was a hot topic some years ago within the media industry, and good content was key for companies and journalists to survive. This is no different in healthcare because good content about patients and the patients history is important for patients' treatments, research and industry development (equipment, procedures, medicine etc). The integrity of this information must be ensured and the information must be shared in a wide ecosystem of healthcare professionals. This requires a trusted platform, and the Nordic Ministries should have this focus when it comes to large healthcare investments.

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Analys för alla: analytisk coaching på olika nivåer

I det senaste numret av CFO World skrev jag en krönika om hur allt fler organisationer satsar på att utbilda sina medarbetare i analys. Både svenska och internationella företag har börjat inse värdet av att personalen har kunskap inom området. Framförallt handlar det om att se till att organisationen får ett analytiskt förhållningssätt till sin verksamhet och framtid. I takt med att många företag digitaliseras på alla nivåer och i alla funktioner är det viktigt att den analytiska förståelsen flyttas ut i hela organisationen och inte bara finns hos analytikerna.

Under den senaste tiden har det dykt upp allt fler verktyg och utbildningsfunktioner inom just analysområdet, allt från renodlade masterutbildningar till självhjälpskurser på nätet, eller workshops i specifika program. Med en rad utbildningsalternativ och en ökad efterfrågan på att utvecklas kan kunskapsnivån hos personalen se väldigt olika ut. Ett första steg mot en kompetenshöjning är därför att identifiera den nuvarande kunskapen hos medarbetarna och anpassa coachingen efter det. Stora företag paketerar exempelvis ofta sin analyscoachning för tre distinkta grupper:

Analytikerna

Analytikerna utgörs av de som redan idag använder olika analysverktyg och analysmodeller, men som kanske är nyfikna på hur man kan vidareutveckla sin kunskap och arbeta smartare, snabbare och med mer precision. Givetvis är det även här den högsta nivån av analytisk kompetens återfinns, utbildning och coaching för denna grupp handlar därför oftast om att ge handfasta råd och tips. Man tittar helt enkelt på nya tekniker, processer och hjälpmedel och annat som gör arbetet bättre. Analytisk coaching för analytikerna kan även handla om att förbättra förmågan att kommunicera och föra vidare resultaten av analysarbetet till andra funktioner i organisationen.

Analysmottagarna

Detta är oftast personal som är vana att få analytikernas analys. Det kan vara marknadsförare eller controllers. Viktigast för denna grupp är att få grundläggande kunskap inom området för att kunna samarbeta smidigt med analytikerna, men även att coachas i att efterfråga rätt material. Förutom den analys controllern själv gör får han eller hon rutinmässigt rapporterat ett antal nyckeltal. Ofta brukar kunskapen kring de analyser man är van vid att få vara god, det man kanske inte vet är det man inte frågat om! Beställaren av analys kan därför utvecklas genom att få coaching i hur man kan ställa nya frågor, efterfråga ny analys och be analytikern om annan information.

Beslutsfattare och affärsansvariga

Analys på den här nivån handlar egentligen främst om ledarskap. Det är beslutsfattarna och de affärsansvariga som tar de avgörande besluten om verksamhetens inriktning och utveckling. För att kunna göra det behövs bra beslutsunderlag. I en ledarroll är det även viktigt att vara tydlig med att man förväntar sig analytisk kompetens hos medarbetarna samt att dessa ständigt utvecklar ett faktabaserat sätt att arbeta. Det är även ledarna som ansvarar för att för att man investerar i rätt teknik och kunskap. För beslutsfattarna handlar coachingen därför främst om att förstå hur organisationen kan arbeta för att höja den analytiska kompetensen. Vet man inte vad man ska fråga efter är det svårt att veta vilken analytisk kompetens man redan sitter på i organisationen, samt hur man kan investera för att höja den nivån.

Analytisk coaching handlar alltså i grunden om att skapa en samsyn i organisationen och utveckla ett faktabaserat sätt att arbeta. Genom att se till att det finns analytisk kompetens på alla nivåer flyttas ansvaret från analysavdelningen närmare verksamheten. Behovet av analytisk kompetens ser dock olika ut på olika nivåer, alla kan inte kunna allt! Men om man istället kan erbjuda anpassad coaching för olika grupper av personal kan man se till att alla pratar samma språk och arbetar mot samma mål – att bättre förstå hur man kan använda sig av all den mängd data som finns tillgänglig idag.
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Instead of failing fast, how about learning quickly?

The term ‘fail fast’ always makes me cringe a bit. It sounds so negative. For most people, it is all about stopping things in their tracks, and not necessarily finding workarounds or solutions to problems.

I’m not alone in my dislike of this term, either. Jeffrey Hayzlett, the author of Think Big Act Bigger, is clear that you should never plan for business failure. He refuses to accept that there is any such thing as a ‘no win’ situation, and complains that failure has become something of a ‘badge of honour’. Yes, of course, anyone can fail, and it is important to get up and try again. But we don’t talk about the people who have continued to fail. You have to succeed eventually to be celebrated. Heroic and ongoing failure is not a good option.

There’s more. In his ‘Mythology of Fail fast’, Ved Sen asks “How many projects actually spend time defining failure, and if not, how would you know when you’ve failed? And what happens then? Is there clarity about the next steps? Of course, recognising failure requires that projects are instrumented, or that the data gathering is built into the prototypes or pilots. In fact, Eric Ries defines a start up as a learning machine. The reality is, most new projects aren't.” Ultimately, we all want success. Perhaps we need to change the conversation.

Learning quickly instead of failing fast

With the Internet of Things and Digitalisation changing and disrupting markets with an unprecedented pace, most companies feel the urge for quick and successful change. We can probably all agree that an organisation is likely to be more successful if its employees learn quicker, and implement and commercialise knowledge faster than the competition. Simply failing is actually neither fun nor any guarantee for future success.

So how can we make sure this happens? Each time we try something new, we need to extract the lessons. What went wrong? And what went right? Why? What new things do we now know? How can this knowledge be used more effectively by us than by anyone else?

Of course people need “permission to fail”. But this must be accompanied by the capacity to see what has happened, learn from it, and then shape alternatives. The essential skill to enable this is critical thinking. To my mind, this includes:

  • Root cause analysis. Why did something fail? It is important to dig down beyond the superficial reason (for example, not enough money) to the ‘root cause’. And here’s the crucial aspect of this: when you think you’ve found the root cause, you probably haven’t. It’s worth digging deeper again. Keep asking ‘but why?’ until you are satisfied you have found the real cause, not just the symptoms.
  • Integration and synergy. It is easy to test simple things. It’s much harder to deal with the complexity that comes from a wide range of stakeholders, broader capabilities and more moving parts. But it is important to try to do so, and particularly to think about how you can manage the challenges of doing so. It is also critical to explore if you can combine two or more things to do more than either in isolation.
  • Circumvention. Sometimes it may not be possible to tackle a problem head-on. Instead, you may need to find a way around it. Continually beating your head against a brick wall as a way of knocking it down is generally agreed to be less productive than finding a ladder.

This ‘critical thinking’ shifts the perspective towards insightful learning. It helps teams to develop genuinely thoughtful responses to a problem. But it will often demand more than simple mind-set changes from a team. At least as important is to establish a supporting technological environment. We live in project driven work cultures - where the actual "setting-it-up", "getting-to-work", and "what's happening after?" phases eat-up most of the total project time. Often months which companies simply won't have anymore in a digitised world.

How companies have gained from #bigdatalab

A Big Data Lab, respectively an IoT Analytics Lab, creates the necessary environment designed for experimentation. This sets the right expectation, both for ‘failure’ and for the necessary learning from it. We have now been working with customers for a year on their big data labs, and the results have far exceeded expectations. As Andreas Goedde indicated “Innovation requires experimentation. Experimentation requires enthusiasm. Enthusiasm is driven by speed, teamwork and fast results.” And the Lab provides even more than enabling teams to constantly experiment with data. It ensures that models are based on realistic data scenarios and provides a structured way to hand over and deploy models quickly.

Learning fast leads to success. With failing fast, there is no such guarantee. As IoT becomes more mainstream, and organisations have more need to test and trial ideas, we suggest that organisational learning needs to be faster. A lab, with its focus on experimentation and learning, is surely even more critical now.

 

 

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Real-time decisioning: adding the oomph to CX

Let’s talk a bit about what using real-time decisioning can do for the customer experience.

You know how some people seem to lack a filter between what happens in their brain and what comes out of their mouth? In Finnish there is a saying that more or less translates to speaking “whatever the spit brings to your mouth”. It can be entertaining for a while, but only spitting out nonsense quickly turns boring and often even embarrassing. Repetition and completely useless information usually dominate the monologue.

The situation above, in a marketing and customer communication environment, could be called real-time communication, but is totally lacking the decisioning-component of the interaction. Technology uses only a minuscule amount of information before spitting out reactions to whatever happens.

My grandfather.

Moving forward to the next analogy: my grandfather is 99 years old. He is fantastic. He was born the same year Finland gained independence. Just imagining what he has been through and how the world has changed during his life blows me away. Nowadays, however, speaking with him has become more difficult. He doesn’t hear too well, and his short term memory is not that good anymore. He does remember stuff from the 40’s to an astonishing detail, though.

This situation, again, depicts circumstances where there is a decisioning component involved in the interaction, as he talks about what he knows and remembers, but the real-time component is lacking since the hearing is not that good and he doesn’t really remember what I did yesterday or an hour ago.

What if you could combine the two?

All too often when interacting with companies today we encounter either one, or both, of the situations above. Communication from the company is either irrelevant, hence lacking in the decisioning part, or outdated, hence lacking in the real-time part. Both can be annoying and certainly do not improve the customer experience or customer satisfaction.

The fact is, real-time decisioning will improve many aspects of customer experience, and the range of application of the discipline is quite wide. The world today is revolving around online, mobile, and other digital channels where real-time is, or at least should be, the norm. Decisioning, however, is not always based on the whole range of information available, a bit like my grandfather. In the digital world decisioning is usually based on short-term memory, which revolves around the particular session and information gathered right then and there. Long-term memory, which can be translated into off-line data, is more difficult to apply to the digital interaction, because this demands a bit more from data, among other things. Applying this data in a real-time environment to the mix would, however, add a significant amount of value for both customer and company.

Real-world example

Let’s take remarketing (or retargeting) as an example. A commonly used tool for remarketing is Google AdWords. The tag associated with AdWords only allows companies to connect with website visitors who saw a specific page or product, which means the targeting options are limited. We use only part of our memory in the real-time decisioning. With real-time decisioning we can add information and analytics to the mix and make the retargeting much more sophisticated, using all available information, and relevant for each customer.

If we want to add an element of pricing to the interaction, the price can also be personalized based on the identified customer and offline data, so that each given price is optimal for the customer. We can also decide to retarget only customers belonging to a e.g. high-value group by inserting real-time decisoning into the remarketing campaigns. In the same manner real-time decisioning can be used in claims situations, fraud detection, credit applications, mobile package pricing and offering, and much more.

There are a number of companies out there in the world who already are reaping the benefits of real-time decisioning in their customer facing processes. Take a look at Telenor, and with a bit of a different flavor, VISA.

Previous blogs:
The What, Why and How of Customer Analytics and Marketing Analytics
Marketing today - easier or more difficult?
Roll up your sleeves: We are now venturing into the marketing analytics practice!

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Har noen sett Big Data i helse?

I media leser vi daglig om Big Data og hvordan dette vil påvirke oss på godt og vondt. Internasjonalt har Norge kommet relativt langt i digitaliseringen og helsesektoren er på full fart inn i denne gjennom sine moderniseringsprogrammer. Stort sett alle bransjer ønsker å digitalisere, men flere er usikre på hvordan dette arbeidet bør gjennomføres. Virksomheter som allerede er i gang har erfart at det handler mer om å endre forretningsprosessene enn å innføre nye system og teknologi.

Fra forvirring til innsikt
Hvor kommer Big Data fra og hvor vil vi finne disse i helse- og omsorgssektoren? Endringer i datamengder og karakteristikker vil i stor grad oppstå gjennom at fysiske objekter i økende grad blir knyttet til internett. Dette kalles IoT, dvs. «tingenes internett», der objektene kommuniserer med hverandre og genererer derved datatrafikk.

Innen helse kan dette være store objekter, slik som transportutstyr (ambulanser), bygninger (smarthus), utstyr på avdelingene (måleutstyr, senger, inventar) big-data-modernisering-helse-omsorgeller i hjemmesykepleien (trygghetsteknologi og hjelpemidler). Men den store bølgen vil komme i form av billige, masseproduserte produkter som vil friste helsevesenet både gjennom pris, kvalitet og sin enkelthet. Mye av dette utstyret vil være bransje- og virksomhetsuavhengig som for eksempel «på kroppen utstyr»; bekledning, sko, briller, eller kommunikasjonsutstyr og lyspærer.

Omfanget gir oss nye utfordringer, men Big Data handler ikke bare om volumer. Dette er det forsket mye på og det vi ser er at Big Data i enkleste form kan beskrives gjennom tre dimensjoner; volum, variasjon og hastighet. Det er endringer i kombinasjoner langs disse tre dimensjonene som skaper raske skifter, nye kombinasjoner og setter analysemodellene på prøve. Beregningene våre kan da møte utilsiktede utfordringer som skaper problemer og derved gi feil resultat. Dette kaller falske positiver og at estimatene er beregnet utenfor modellens gyldighetsområde. I pasientbehandling og gjennomføring av omsorgsplaner er dette svært uheldig.

Teknologien gir oss et mulighetsrom. Spørsmålet vil være om vi klarer å utnytte mulighetsrommet for å oppnå bedre livskvalitet til en lavere pris og risiko. Blir vi mer sårbare? Det siste handler mye om troverdighet og tiltro til sårbarhetsanalyser. Når det gjelder Big Data og sårbarhet må vi tenke nytt. Det hjelper ikke om risiko i egne prosesser er tilfredsstillende og håndterbare hvis hackere slår av strømmen på sykehuset eller kontrollsentralen for omsorgstjenestene og krever løsepenger.

Datareduksjonsteknikker og Big Data
I dag hører vi at globale datamengder dobles hver 18 måned og at 90% av informasjonen i dag ikke fantes for to år siden. For et par titalls år tilbake var vi 16 millioner internettbrukere, mens vi i dag er 3 milliarder. Tekstinformasjon eksploderer, det popper opp myriader av nye brukerfelleskap og foredlede helsedata er blitt verdifull handelsvare for kommersielle tilbydere. Hvor tar dine helsedata veien når du haker av på «share with other users» i helsenettverk, hva er de verdt og hva får du egentlig tilbake?

For at vi skal kunne oppnå god nytte av Big Data innen helsehjelpen eller som pasient/beboer må vi ha tilgang til teknologi og metoder som henter ut det substansielle innholdet. Vi må kunne kunne fjerne støy, irrelevant informasjon og data med tvilsom kvalitet/lav troverdighet. Det er dette vi i SAS Institute kaller dataproduksjonsteknikker og det er dette som vil være plattformen for å kunne utnytte Big Data på en hensiktsmessig måte. Avansert analyse er datareduksjon og Big Data trenger reduksjonsteknikker. Gjennom F&U og praktisk utprøving gjennom prosjekter har vi festet oss med fire teknikker som vi mener vil bidra til å løse Big Data utfordringene innen helse og omsorgssektoren:

  1. Flytte beregninger nær datakilden. Her blir analysene i størst mulig grad utført ute på målepunktet og vi unngår å overføre unødvendig informasjon
  2. Kvitter oss med tekst. Dette gjør vi med å benytte avansert tekstanalyse som sørger for at tekst blir til tall
  3. Utnytter i minnehåndtering. Her vil innsamling, kvalitetskontroll, harmonisering og analyse av Big Data bli utført i høyhastighetssystemer, det teknologer kaller «In memory» eller «In database» operasjoner. Foredlede resultat videreføres i forretningsprosessene
  4. Benytte maskinlæring. Her bytter vi ut statiske modeller med modeller basert på maskinlæring hvor etterprøving av validitet i eksisterende modellportefølje utføres løpende samtidig som det bygges nye dynamiske modeller som takler endringer og kvalitetskrav.

Big Data - mulighetsrom for et paradigmeskifte?
Helsevesenet må gjennom en modernisering for å møte både bemannings- og kostnadsutfordringene i tiden fremover mot 2025. Retningen for dette arbeidet er beskrevet i Meld. St. 27 «Digital agenda for Norge — IKT for en enklere hverdag og økt produktivitet». De digitaliseringsprogrammene som er igangsatt er svært viktige, men det ligger et ytterligere potensiale hvis helsesektoren klarer å integrere eksterne Big Data, bl.a. ved å ta i bruk innovative digitale teknologier og at pasient/beboer i større grad får rollen som dataleverandør og operatør. Dette gir økt grad av fleksibilitet i behandlingen og oppgavene kan organiseres på en effektiv måte noe som vil kunne redusere kostnadene.

God utnyttelse av Big Data reiser et omfattende opplæringsbehov både på helsearbeidersiden og på pasient-/beboersiden. Når dette er på plass får vi et mulighetsrom for få på plass bedre og mer effektive arbeidsprosesser. Vi kan redusere og forenkle manuell rutiner hvor gevinsten vil være mer tid til helhetlig pasientbehandling.

I parallell med dette må det foregå et systematisk arbeid for å avdekke risikobildet knyttet til Big Data og innføres tilfredsstillende sikkerhetsmekanismer og tiltak som ivaretar pasientsikkerheten og behandlingen.

Har du en datastrategi ift. utnyttelse av alle verdifulle data? Lær mer her: The 5 Essential Components of a Data Strategy

Big Data i praksis
I april 2009 fikk vi det første utbrudd på 90 år av svineinfluensa. Kilden var i Veracruz i Mexico. Her smittet en mutant versjon av H1N1 viruset raskt menneskene i lokalmiljøet, inkludert turistene. På grunn av omfattende turisttrafikk ble viruset deretter spredd til andre distrikter i Mexico og videre til andre land og kontinenter. Spredningen utviklet seg eksplosivt.

Først i august 2010 kunne WTO avblåse kampen mot epidemien. Offisielle anslag på døde var da 285-560 tusen. Spørsmålet som fortsatt diskuteres er hvor mange av disse liv kunne vært spart dersom de tidligste tilfellene i Veracruz hadde blitt anerkjent som selve kimen til utbruddet? Kunne de neste utbruddene være forutsett hvis helsemyndighetene hadde klart å koble sammen data om nye utbruddspunkter, dvs. gjennom analyse av Big Data?

I dag vet vi at informasjonsflyten under epidemien til dels var kaotisk og helsemyndighetene klarte først etter lang tid å bedre det substansielle innholdet i all innrapporteringen for å bygge tilstrekkelige tiltak.

Inge Krogstad var en av foredragsholderne under konferansen Pasientsikkerhet og teknologi, Lillehammer 19.-20. april 2016: klinIKT2016
Se hans presentasjon Big Data - pådriver for modernisering innen helse og omsorg

 

Link til helseeventet

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Modernization – Better, faster and cheaper!

Business oriented IT Managers must bring modernization to the table now because it will increase the value of IT and the value of using SAS.

Management will probably approve projects that are better (quality, aligned with strategy), faster (time) and cheaper (cost). Reaching all three parameters is difficult because higher quality usually implies increased costs and maybe delays. Faster implementation could imply worse quality or increased costs. Costs savings could imply delays and worse quality. Is it possible to have it all?

Could we have SAS running better, faster and cheaper?
Better means more robust, increased reliability, and solutions allowing for increased insight. Faster means that data can be accessible more quickly and that analysis takes less time. Cheaper relates to total cost of operation with lower hardware-, software- and maintenance costs as three examples.

Hadoop and SAS Grid
SAS customers have used the yearly user conference, SAS Global Forum, to share results after modernizing their SAS® platform, and they have proved that modernization projects can be both better, faster and cheaper.

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Download White Paper: SAS® Grid Computing – What They Didn’t Tell You

The main reasons for this is that modernization usually results in the introduction of clusters (Hadoop and SAS® Grid). Clusters allows for more data and increased insight, throughput and faster analysis. Hadoop and Grid runs on commodity hardware, which is more economical than a variety of servers. Fewer servers implies reduced costs.

SAS customers with old software and a variety of servers should put modernization on their agenda. I will argue that the business case is good, and that these kinds of projects will increase the value of deploying SAS within three distinct areas; It will be better, it will be faster and it will be cheaper.

Explore SAS® In-Memory Analytics, SAS® Solutions for Hadoop and SAS® Grid

Download White Paper: SAS® Grid Computing – What They Didn’t Tell You

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Impressions from SAS Global Forum 2016 – bigger, more connected and a strong Nordic turnout

The largest SAS Global Forum ever with more than 5000 attendees, 250 from the Nordics.

The largest SAS Global Forum ever with more than 5000 attendees, 250 from the Nordics.

 

Having just returned from a whirlwind week in sunny Las Vegas, Nevada, I want to share with you a few of the many news and impressions from our biggest event of the year.

First of all, we were excited to welcome customers, partners and SAS employees to the largest SAS Global Forum ever! More than 5000 attendees assembled at the impressive Venetian Hotel: It is one of the largest hotels in the world and we had a fantastic venue for the forum’s 350 hours of content, 550 sessions, and many opportunities to network.

The Nordics were strongly represented with the third largest group of 250 participants, falling behind only the American and Canadian delegations in numbers.

Participants from all over the world had the opportunity to hear cutting-edge cases from Nordic companies such as Danica Pension, Statistics Sweden, Telenor, The Norwegian Seafood Council and Veikkaus. Our Nordic delegation could participate in a sightseeing trip to the Hoover Dam and Lake Mead, in addition to participate in a Nordic dinner. It was great to see new connections made and old ones confirmed once again!

SAS® Viya – next generation of analytics

SAS® Viya – next generation of analytics

New, more customer-oriented and connected to the IoT
So, what were the big news, we were able to experience during this year’s SAS Global Forum? For me, there were three major new announcements:

 

  1. We are going live with a completely new architecture, SAS® Viya
  2. The new SAS® Customer Intelligence 360 solution
  3. SAS® Analytics for IoT

SAS® Viya is a big deal because it is the new SAS architecture built for the future for both cloud and on-premise deployments. SAS is building on our unique foundation of expertise to deliver the most powerful and adaptable analytics platform available anywhere. My impression is that there was really good reception from customers, and I see the move to SAS Viya as a logical step due to the rapid changes in technology we are experiencing. With SAS Viya, SAS is also opening up to more third party technologies, which is great news for customers who want to leverage existing skill-sets when using SAS analytics, including languages like Python, Lua and Java. Learn more about SAS Viya

SAS® Customer Intelligence 360: The new SAS® Customer Intelligence solution 6.5, launched along with SAS Customer Intelligence 360, is a completely new product. It builds on the Customer Decision Hub concept and allows marketers to guide the customer journey as it happens. It helps marketers create a complete profile from disparage data, serving digital departments and helps optimize customer messaging and offers. The CI solution will be a great leap in helping companies increase loyalty in a cloud-based solution. Learn more

SAS® Analytics for IoT: SAS is really bringing analytics offerings to the market: IoT creates a lot of data, and long before IoT became trendy, SAS was analyzing data from sensors and other devices. With the launch of SAS Analytics for IoT, we can collect data and analyze millions of events per second. An example is to look at the idea of Smart Cities – modern cities generate all kinds of services and related data within areas like public safety, healthcare and water. This allows you to organize the data and pick out the relevant information and understand which actions to take in order to improve a specific area.

Another wealth of exciting IoT possibilities come from the Intel collaboration. SAS brings the IoT analytics offerings to market as a strategic partner in Intel’s Internet of Things Solution Alliance. Intel’s slogan is “Intel inside, smart manufacturing outside”. For example, it will be possible to place an Intel card in cars and predict issues in the fleet before failures occur using SAS software on the device in the car and provide new value added services. When you need to analyze a situation, it will be analyzed right on the chip with SAS® Software. This is analytics close to the origin of the data; it is on the edge. Get inspired

The SAS® 9.4 platform you know – with more “bells and whistles”
However – most of our clients attending SAS Global Forum were there to hear about the existing products and services they have come to know and trust, within the SAS 9.4 software suite. Both within Analytics, BI, Data Management, Risk, and Customer Intelligence there were lots of new things to experience, and the majority of the 550 sessions were centered on these. Among the highlights from the existing products were:

Analytics: SAS continues to provide analytic innovation on the SAS 9.4 platform – improving scale and speed along the way. SAS® Studio, our web-based interface that comes with SAS® Base, continues to address the analytical needs of everyone. We are releasing SAS® Factory Miner 14.1 – this product provides modern machine learning algorithms and large-scale automation models, enabling clients to distribute models to a larger user group in the company. SAS® Enterprise Miner 14.1 brings new machine learning methods and open source integration (PMML 4.2, R, Python) with continued technology advancement (for Hadoop and MapR). SAS® Forecast Server 14.1 provides a more modern web-based interface with custom code, tracking, multi-stage modelling and segmentation via demand classification.

BI: SAS® Visual Analytics 7.3 includes the HTML5 report viewer, also known as the modern viewer. It provides an intuitive, self-service approach for data preparation, analysis and collaborative sharing of results. Visually explore and interact with both structured and text data – of any size from any source – to spot patterns and identify relationships.

Data Management: I think that the main new thing for SAS® Data management is the SAS® Event Stream Processing 3.2 as well as the SAS® Data Loader for Hadoop. It is important because it opens up for SAS accessing more data, including IoT data. SAS knows that clean and correct data is key to deriving good analytical insights. With our updates focused across all Data Management technologies, we continue to focus on the entire analytics lifecycle.

Risk Management: We have streamlined products and improved scalability across the product suite.

Product demo’s and cutting edge student projects
Between the many announcements and exciting plenary speakers at SAS Global Forum, there was time to visit the many workshops and also “The Quad”, the demo area where we can go ask developers and product managers, speak with real experts about the products and the future directions, and see the future product releases. The atmosphere was great and I met many attendees who came back excited and said “oh, I learned a lot about this specific code, how to do this installation”, and so on. It is a great feeling when you can see the shared knowledge of customers, partners and SAS employees growing in real time!

I also want to mention the academic forums, where students from around the world competed with their SAS solutions based on our free-of-cost SAS® University Edition software. The winning team was from the US. This year, we did not see Nordic participation and I really hope this will happen in the future.

Once again, I have come back full of inspiration and excitement about our great SAS community and if you were there, I hope you can recognize the sentiment. If you were not able to attend, I hope you will go here to find whitepapers, presentations and much more, and we will also soon be sharing these in the local Nordic SAS Forums and SAS user groups.

Whether or not we met in Vegas, there is another opportunity in the fall when the next line of SAS Nordic Forum events roll around. They are set for September 29 in Norway, October 4 in Sweden, October 5 and 6 in Finland, and October 13 in Denmark.

And for those of you that already want to start planning for the next SAS Global Forum, it will take place in Orlando, Florida from April 2 to April 5 2017.

Hope to see you there!

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Copy cats, gamblers or entrepreneurs?

Did you find that special card of diamonds in the card deck if you were gambling in Las Vegas? Did you find that golden egg? Did you manage to keep up with everything that was happening almost 24/7?

The program at SAS Global Forum was set from morning to late hours, 3 days in a row; Networking opportunities, sessions and keynotes, demos and Talking Points gave us the chance to hear other people´s experience in using SAS, and the ability to discuss with SAS Experts and be part of very exciting new SAS launches.

We also spent time to network and establish new relations, with Nordic and global colleagues, customers and partners, spending valuable hours socializing and sharing knowledge and inspiration, in and around the amazing Las Vegas.

I speak for myself when it comes to finding those golden nuggets. They were there. I learned a lot during the conference and got to know many new, great customers, which is very valuable for me personally.

Busy schedule at SAS Global Forum

Busy schedule at SAS Global Forum

Your experience - Inspiration from your colleagues
What did you experience at SAS Global Forum? What did the presentations and findings, and new ways of doing things mean to you? Moreover, to your manager and organization, that has invested in your presence at the conference? I believe one positive effect is that you will work differently when returning after SAS Global Forum. Do you agree?

Driving your business forward means challenging the normality’s and to adjust the governed way to do things. Understanding the way other people think, does that mean you are copying their work? Alternatively, does it prevent you from repeating their flaws and potentially doing things faster and more accurate using your new knowledge? I believe you will find this out yourself the next days, weeks and months, and that it will be much easier to convince your manager next year letting you go to Orlando, Florida and experience SAS Global Forum 2017, with the new insights and great work coming from you.

I guess you also learned to know new people that you will stay in contact with, both from SAS Institute, and other organizations. Without the opportunity to go to SAS Global Forum you would not had the same chance to network. Valuable to you personally and professionally, but also of high value to your organization in order to solve challenges in your daily work.

Presentations and recordings
One thing that troubled me during the conference, and probably some of you attending, was that many of the presentations I wanted to attend occurred in parallel. Well, I have great news for you. You can now download all proceedings and papers available from the conference, via the application on your phone or the SAS Global Forum web site. You can also see presentations and interviews on video. You will not miss out after all!

Nordic presenters at SAS Global Forum
SAS owes a huge thanks to everyone who contributed with presentations at this year’s conference. Without them sharing their knowledge there will not be a conference next year. Now we are building the program for SAS Forum and SAS Business Forum for all Nordic countries, taking place this fall. If you want to share your SAS knowledge and inspire others, submit your brief abstract (max 300 words) of your idea to Program Committee lead Georg Morsing: georg.morsing@sas.com before May 25.

Hoping to see you all this fall at our Nordic SAS Forums and next spring at SAS Global Forum 2017! Meanwhile, you could read more on our new, exciting launches:

SAS® Viya

SAS® Customer Intelligence 360

SAS® Analytics for IoT

 

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What happens in Vegas should not stay in Vegas?

SAS Institute has its annual user conference in Las Vegas, SAS® Global Forum, and it is the largest conference ever with more than 5 000 attendees. Users and analysts from all over the world hear about use cases from all industries - from customers, partners and SAS. The demo area displays new technology and solutions, and our important consulting partners are aligning their offerings with SAS. We also experience great opportunities to network with our peers worldwide.

What happens in Vegas is all about analytics, and how analytics in action creates value in business processes cross industries. Industries like banks and insurance companies have used analytics for years, but analytics is rapidly moving into other industries. It is happening now, it is happening fast. During the conference first day, we heard about real use cases that creates tangible business value. Not tomorrow, but today!

More emphasis on capabilities
 Lessons learned from my first day in Vegas is probably that we should emphasis less on technology but more on capabilities, and that we should use the right tool for the job. SAS Institute has a strong offering because SAS provided capabilities to succeed with analytics. However, an important new capability from

Presenting SAS® Viya – next generation of analytics

Presenting SAS® Viya – next generation of analytics

SAS is open API’s and support for Hadoop distributors. This enables innovation because developers can work outside SAS with other technologies and access capabilities provided by SAS, like third party applications calling SAS analytical models.

 

SAS in the market for 40 years and more to come
SAS celebrates its 40th year anniversary this year, and the company has grown profitability every year. Some analysts could argue that the era of SAS is over and that new entrants will take lead and influence the next 40 years. I am willing to take a real “Las Vegas bet” and bet my salary that they are wrong.

My argumentation for this is that the new capabilities in SAS will enable rapid innovation with better support for the analytical life cycle. SAS will continue to support the user community with necessary analytical capabilities and respond to requirements. SAS business- and technology partners will continue to deliver high value to our clients.

Presenting SAS® Viya – next generation of analytics
Today SAS announced a new modern architecture that is future ready, SAS® Viya. SAS solutions on Viya attract and retain the next generation of analysts and

enable everything from start-ups to large enterprises with actionable analytics.

Which competitor can catch up and compete with SAS? SAS is, without discussion, the market leader, and the company will continue to lead way for the next 40 years. Businesses that rely in SAS will get a competitive advantage over companies that struggles with their analytical strategy.

Interested in learning more about SAS® Viya?
SAS® Viya – a new, open architecture – built for analytics innovation

Press release on SAS® Viya

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How Sports should engage with Analytics

If you don’t believe Analytics and Sports go together you may want to stop reading here. Or you may want to start with validating my previous reasoning on "Why Sports should embrace analytics".  If you find you are past the “Why?” you may instead think that the title above doesn’t call for a page long article, that Nike’s slogan “Just do it” would be sufficient as a recommendation. I can see that point of view, I used to think that surfacing information that was previously unknown would be enough to trigger engagement, buy-in and action. However, more than once I’ve found that exposing a sports management team to information they never saw before based on data they didn’t realize existed leads to nothing following the meeting. Even though they clearly both see and express how these things would be valuable to them it doesn’t necessarily move forward from there. So, assuming that the question “Why?” is not an issue, let’s take a look at “How?”, how do you engage with analytics in order to make it operational and contribute to the team?

1. Be relevant.

Realizing this may at first sight qualify as a true “no-brainer”, it still can’t be pointed out often enough. Relevance is everything and it applies to information, communication as well as timing.

Let’s start with information relevance, what information are you presenting? In sports especially, there are so many things that you can do with statistics and analytics that are interesting, and maybe even entertaining, and they can lead to amusing discussions, but if you want people to truly engage it is essential that the information is relevant, something that clearly aligns with an agreed objective. For the sake of illustration, let’s use hockey face-offs as a very basic example.

Possessing the puck is important, therefore face-offs are important, hence measuring and knowing different players’ face-off percentages are valuable. 50% is good, higher is of course better, 60% is excellent, above that is rare and exceptional. But players’ faceoff percentages are not consistent around the rink, they typically vary considerably between different circles on the ice. So the detailed information below adds relevance since it more clearly indicates who to have or not have on the ice pending the situation.

Hockey2
Crucial face-off in your defensive left circle, you may want somebody else in there, right? As the British Rowing team phrased it, if it provides an answer to the question “Will it make the boat go faster?” the information is relevant.

Source: Twitter account @JonBlomqvist

 

Let’s move to Communication relevance. How to visualize your findings. The human brain remembers pictures. Look again at the image above, it takes a few seconds only for everyone in the room to grasp the context and it’s easy to recall from memory. And as you talk about the findings and the implication, make sure you use a language that is understood and keeps the listener on track, words like “odds” and “probability” will probably work while “standard deviation” and “r square value” will likely not.

Timing relevance relates to understanding when the information adds value. In connection with practice or with game? When evaluating, preparing or executing? Understand the process and add value to it by timing the information. If it’s not relevant to the situation it will become noise, no matter how correct and valuable it may seem to you. And insights not put into practice remain only insights, nothing more.

As you move forward from known areas and statistics to new and more advanced analysis, as long as you stick to relevance in information, communication and timing you can’t go wrong.

2. Form a team.

Engaging in Analytics is not something for one person to do in isolation. To be successful the whole staff needs to embrace analytics, from GM to assistant coaches, they have to be involved, one way or another. Even if one person has all the skills required, which is rare, you above all need collaboration and communication, validation of findings and different perspectives in order to achieve a joint trust of results and execution thereupon

A sports team that follows these guidelines on “How” will gain insights that will lead to actions that will make a difference.

And by the way, if you’re not involved in sports but work in business or public service, this same answer to “How?” when embracing Analytics applies in order to gain success. Be relevant with regards to Information, Communication and Timing and Form a Team.

At the Data Innovation Summit event I laid out some of these thoughts in my main stage presentation and in a wider context for a few minutes in this  video. Your feedback and thoughts are highly appreciated.

Previous blogs:
Why sports should embrace analytics

 

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