April 20, 2020No Comments

What will the world look like after the Corona crisis?

The Corona-pandemic has shaken the entire world and altered the way we live our lives, at least temporarily. The question is: how temporary is the current state we are in? Or rather how will our lives, society and world be altered and in what ways?

The immediate consequences we see so far are lockdowns, social distancing, an overwhelmed health care system, companies shifting to remote working models, gatherings being banned and borders closing.

The events caused by the pandemic are still unfolding and the many variables make it inherently complex to predict the outcomes. Will things go back to normal or will they forever change? Predicting the future is impossible but it is possible to see some early indications of trends that are emerging. In this blogpost, we will focus on three areas that we see will be impacted and present a couple of trends regarding each area:  

  • Globalization 
  • Healthcare  
  • Employment 

1. A changed perspective on globalization 

Since mid 20th century we´ve seen an increased interconnectedness thanks to the rapid advances in transportation and technology which have had a positive impact on global trade and cultural exchange. We live in a society where it’s easy to ship goods across the world and where it’s possible, and even considered natural, to work, move and travel abroad.

While globalization indeed has helped raise incomes, rapidly develop economies and increase production of goods and services – it has also helped increase the risks of contagion, both medical and financial. The spread of Covid-19 has been accelerated by the global interconnectedness, and our reliance on globalized value chains makes us vulnerable to the effects of the crisis. Will these downsides start to change our previously positive view of the free global movement?

1.1 Monitoring and controlling the free movement 

In order to prevent future pandemics, traveling will likely come with further safety measures using methods that could have implications on traveller's privacy. We have already seen examples of nations using technology to monitor and track contagion within the population. One example is China that has used monitoring systems to identify suspected coronavirus carriers but also to reinforce quarantine behaviours, using e.g. smartphone location, face-recognition, reporting of body-temperature and medical conditions. Other countries that have used similar solutions are Taiwan, Israel and Hungary.

We may see an upcoming increase in implementation of such solutions after the crisis, in efforts to try to avoid further pandemics. For instance, Apple and Google recently announced a collaboration with purpose of providing tools that will help track the spread of coronavirus. In the future we might start seeing tech solutions for checking medical health at airport security checkpoints, or we may need to verify our “health status” using biometric bracelets or medical apps on our smartphone, before we enter a country or a public space.

1.2 From lean and globalized value-chains to buffers and backups

Companies have become more and more efficient in their production processes and many have perfected decentralized global value-chains. A lot of companies rely on collaborations and partnerships with a network of global suppliers and these setups have in many ways been greatly beneficial for companies. Notable examples are Apple that has over 200 suppliers around the world and several car manufacturers, like Volvo, Hyundai and Fiat that are dependent on components that are made in China – all companies that now have suffered from halted production. China represents 16% of the global GDP and US represents 23%, making the whole world dependent on what happens in the Chinese and American economy.

We will probably see different production setups arising with an increase in safety buffers and a greater diversification of the supply chain.

We have recently experienced the downsides and risks of global supply chains and it has become quite evident that many organisations lack backup solutions and don’t have storage or buffers to rely upon to help them overcome temporary issues in the value chain. It is likely that we will see altered strategies after the Corona crisis, where organisations will begin to plan for handling another crisis or pandemic. It is not likely that we will see companies completely abandoning global value chains, since the benefits are still there, but we will probably see different production setups arising with an increase in safety buffers and a greater diversification of the supply chain.

1.3 Increased international collaboration and cooperation

The effects of the Covid-19 outbreak demonstrate how unprepared we are to handle such a pandemic on the international level. To successfully contain the spread of the virus, international collaboration and cooperation is necessary. Previous outbreaks such as Ebola in West Africa, or SARS and MERS have served as warnings, but did not result in enough international action. This time, things are different.

Although we have seen increased protectionism during the last years, it’s possible that this pandemic will acknowledge our interconnectedness and spur efforts to work together more closely.

We can learn from our collective experiences and use that knowledge to increase our preparedness for future crises. Isolation is a key component in containing the spread of a virus, but it’s not the best way forward when preparing for future, global events.

 

2. Shifting societal priorities and strengthening the healthcare system

This pandemic has revealed how vulnerable our societies are and the importance of robust healthcare systems with sufficient resources. The fast spread of the Corona virus has forced nations to put everyday life on pause and is putting increased stress on our societal abilities to cope with the spread of the virus.

2.1 A strengthened healthcare system

The pandemic has put our fundamental societal structures to a test, and in the aftermath, we may see a re-prioritization of resources. How can we make sure that we are better prepared for a global crisis such as Covid-19? And how can governments guarantee an effective health care?

Preparedness for crisis

It’s now obvious that most countries have not prepared for a pandemic such as Covid-19. The prime minister of Sweden – Stefan Löfven - recently acknowledged that our preparations have not been adequate. During the last thirty years, Sweden has deliberately disposed of medical supplies and equipment which would have been valuable today. We believe that this pandemic offers a rapid awakening regarding the consequences of the unexpected. Hopefully, we will learn from this experience and make sure that we prepare for future crises, not least within the healthcare system.

Resources and management

Our healthcare systems have been put under great stress for many years. We believe that after the crisis there will be a healthy and necessary discussion in Sweden regarding the resources allocated to the healthcare system. There is much to be done, not least ensuring that there are sufficient medical personnel available also in times of crisis. Hopefully, we will also see a shift in how the healthcare system is managed with less politicization.

2.2 The rise of self-help health care tech

We have already begun to see an accelerated adoption of “digital doctor” services since the pandemic started. The Swedish telehealth solution Doktor.se reports that the number of cases has doubled as a result of covid-19, a trend that other telehealth solution providers note as well. The increased adoption is seen largely in the older age groups as they, due to safety reasons, should avoid visiting hospitals.

The limitations in the traditional physical health care forces an increased adoption of new digital solutions and it empowers people to take personal control of their own health care. This drives up the demand for effective home diagnostics tools, telehealth solutions and other solutions that extend the reach of the healthcare professionals. We will likely see an increase in innovation and adoption of such solutions that will enable the individual to take a greater role in their own health care, even after the pandemic.

2.3 Healthcare efficiency enabled through AI and faster innovation

AI is already having a big impact within the healthcare sector, and it will likely play an even greater role in transforming medical procedures after the Corona crisis.

AI could support in making more accurate diagnoses, mass diagnosing conditions and be used to speed up the development of pharmaceuticals. AI can also help improve the patient experience and automate hospital processes.

We therefore see an increased demand of AI solutions as they enable efficient healthcare and improves nations capability to battle future virus outbreaks. The health care sector has, compared to other industries, been slow atembracing tech innovation and entrepreneurship. A possible result of this crisis could be that technological development, innovation and entrepreneurship within the health-care sector could be boosted and receive more resources going forward.

3. The future of employment

With the spread of covid-19, came also an economic crisis resulting in bankruptcies and mass unemployment. According to Forbes, the number of layoffs in USA could reach 47 million in June 2020, which would lead to an unemployment rate of 32.1%, higher than the great depression´s worst rate of 24.9%. In Sweden, 36,800 people have been laid-off during March 2020 which is 10 times the numbers from March 2019. The Swedish minister of finance Magdalena Andersson recently presented a report estimating that unemployment would reach 9-13.5%. We can also see how lockdowns and recommended social distancing, to battle the spread of the virus, has impacted schools and workplaces where many are nowadays working from home if possible. We see these events as important change indicators for the future of employment.

3.1 Gig-Economy providing the job opportunities

The gig-economy has during the past years emerged and grown more common thanks to the larger number of freelance- and gig-platforms available in a wider area of industries. The overall shift to a more gig-oriented job market has not yet been fully carried out, where one of the main challenges for the gig-movement is the perceived lack of employment security that the work form entails.

Due to the coronavirus we are unfortunately seeing unemployment rates reaching record numbers and finding a permanent position during these times can be difficult. It is quite possible that many, whom prior to the mass-unemployment rate have been unwilling to take gig-jobs, will need or even prefer to make the move into gig-economy. The shift to gig-work may either be of necessity, opportunity or due to a shifted perception of job security and the trend will likely be more common with younger professionals, within tech and consulting professions.

Short term we will see an increase in the number of job seekers, but eventually employers will slowly be able to engage in lighter investments again, resulting in more job-opportunities. The immediate resource needs in society due to lock-down are within delivery, health sector and e-commerce, however the future might create new job opportunities, as we will need to increase our crisis-mode capabilities both within organisations but also on a governmental level.

3.2 Will the entrepreneurship trend die out?

We have during some years been able to observe a growing trend of entrepreneurship, where an increased number of people have sought out to start their own ventures. The small businesses owners are badly hit by lockdowns and shops and restaurants are as a result going out of business. What will happen with them after the crisis, and will this result in the end of entrepreneurship?

We believe that entrepreneurship is a state of mind and this pandemic will bring creativity out of people. Entrepreneurship will not die, it will evolve.

A crisis tends to fuel entrepreneurship and innovation, and a disruption of current magnitude in the market will create new opportunities. Many digital tech entrepreneurs are currently flourishing, and we will most likely see many more enter the growing market sectors. In fact, opportunities even lie in the market of providing support to struggling small businesses during the crisis, where entrepreneurs can provide smart solutions within paytech, enabling home delivery and much more.

3.3 Digital workers and shifting work-life priorities

Due to lockdowns many companies shift to working remotely and digitally assisted. The “work from home” setup has presented organisations with some immediate challenges needed to be quickly addressed in order to increase efficiency and employee satisfaction. Even if many might initially be struggling with the new setup, there are also quite some benefits of remote work if you learn to manage it (and yourself) correctly. The increased flexibility and undisturbed working hours could enhance productivity and improve private life priorities.

We therefore strongly believe that the remote working model is here to stay, and organisations will need to manage the daily work-life differently and more consciously design the employee experience. The big move has already happened unwillingly due to the coronavirus, and now that many more have experienced the value of remote work it will become a necessity when moving forward.

Cartina recently posted an article about the topic of remote working – becoming the new normal, where a deep dive of our point of view is presented along with some recommendations for success. You find it here: When working from home becomes the new normal

What do you think the world will look like after the corona crisis? We would be interested in hearing your thoughts and ideas!

Please comment or contact us for further discussions.

December 11, 2018No Comments

Getting started with advanced analytics by finding the right use case

Analytics is basically using data for different applications. Applications are often called use cases: the most difficult part with getting started with analytics, from a strategic perspective, is to identify relevant use cases that relate to a specific business need or to a future business opportunity.

In the analytical world, a use case is a demarcated area where data can be used to rebuild an analysis model, i.e. populated with new data as it is collected, for example, by sensors, from customer data, etc. As new data is collected, the model is continuously refined. If the refinement is done automatically, it is called machine learning.

Examples of use cases for different companies

Company A - Personalized online shopping

The company wants to create a personalized online shopping experience to increase conversion. A use case for analytics can then be:

How can we predict what every customer visiting the website is most likely to be interested in?

Company B - Optimize customer service staffing

The company wants to optimize customer service staffing to save costs and increase customer satisfaction. A use case for analytics can then be:

How can we predict how much calls come into the customer service due to different external factors?

Company C - Optimize inventory

The company wants to optimize its inventory to save costs and reduce the loss of sales opportunities. A use case for analytics can then be:

How can we predict how much demand there will be for our different products at a given time?

Company D - Reduce maintenance costs

The company wants to reduce its maintenance costs by getting early warnings of potential equipment failure. A use case for analytics can then be:

How can we predict which components are likely to develop a fault based on known behavior patterns shown before breaking apart?

 

Real-time data allows for real-time insights

Previously, historical data has been used to produce forecasts that form the basis for traditional planning. Now it is possible to work with real-time data that runs against different predictive models, which in turn can be linked to a dashboard or against different triggers.

This increases the accuracy of the models drastically. A trigger may be that if a signal exceeds a certain value, an alert should be sent to a technician who can act directly, instead of making maintenance rounds at fixed time intervals.

Another trigger may be to highlight a particular offer to a specific customer, based on his/her earlier searches on a website instead of giving all customers the same generic information.

A third trigger may be information sent to a staff manager about how many employee hours are needed for the next period of customer service, based on real-time demand instead of following regular forecasts based on historical data.

 

Normally, there are two distinct phases in analytics:

1) Prototype phase (or proof-of-concept)

The goal of this phase is to create predictive model(s) based on historical data to validate if it is possible to solve the identified problem(s)

There is almost no barrier to starting the prototype phase. However, there are some common obstacles that limit the ability of a company to go to a production phase, such as lack of sufficiently high-resolution data or lack of an easy way to retrieve and restore data between data warehouse and analytics tools.

 

2) Production phase

This phase is when the predictive model is put into a production environment, which usually involves activating triggers, but may also consist of continuously presenting insights into a dashboard.

But before taking the step towards production, one needs to have overcome the prototype phase and truly achieved a good “buy-in” from the rest of the organization.

In many companies we work with management teams who want to see a business case at this stage before they are willing to make a bigger investment.

The prototypes luckily provide a good indication of the business potential of a full-scale implementation and any system changes that will be required to reach it.

 

Do you want to get better and faster insights by finding the right use case for your business or need help to drive through the initial prototype phase? If so, please contact us by clicking the button

Send email to Johan Wrang

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October 1, 2018No Comments

Data Prototyping – Ett bra sätt att börja skapa värde av din data!

Under en längre tid har det pratats om att data är den nya oljan, men vad innebär det egentligen?

Vi träffar på många klienter och bolag som känner att de inte riktigt vet hur de ska jobba med data för att skapa affärsvärde samt vad detta innebär för deras organisation och arbetssätt.

Som svar på detta har vi utvecklat ett arbetssätt som vi kallar Data Prototyping där vi hjälper företag att snabbt och effektivt skapa värde av sin data.

 

Tycker du att ni inte får ut värdet av er data? Låt oss presentera Data Prototyping!

I en digital organisation kan man skapa enorma mängder data. För många är detta positivt då det öppnar upp möjligheter att förstå och analysera sin verksamhet på sätt man inte tidigare kunnat. För andra kan det bli tidsförödande och förvirrande då man inte vet i vilken ände man ska börja eller hur man ska ta sig an problem.

Att kunna utgöra vad som skiljer de två scenariona åt och vad man bör göra för att hamna i det första läget är inte självklart, men att kunna säkerställa det är något man behöver för att vara konkurrenskraftig.

Att ta välinformerade och faktabaserade beslut är den uppenbara fördelen med att arbeta datadrivet.

Det finns såklart många fler fördelar som exempelvis

  • kostnadsbesparingar
  • ny produkt- och tjänstinnovation
  • snabbare, mer enhetliga beslut

 

Vad innebär det att vara datadriven och varför är det viktigt?

”As business leaders we need to understand that lack of data is not the issue. Most businesses have more than enough data to use constructively; we just don’t know how to use it. The reality is that most businesses are already data rich, but insight poor.“

 – Bernard Marr. Författare av bla. ”Big Data in practice” samt KPI & Big Data guru

Att vara datadriven är för oss att man använder data för att förstå sådant som vi som människor inte klarar på egen hand - en datamodell kan betydligt snabbare och mer precist processa stora mängder information.

För oss handlar dock det datadrivna inte enbart att hantera stora mängder information utan även att se till att man jobbar med "liten" data där den skapar värde.  Att arbeta på ett datadrivet sätt ser vi som ett måste för alla moderna företag och som kan vara helt avgörande på en snabbföränderlig marknad.

Det finns ingen formulering eller aktivitet som definierar ett företag som datadrivet eller inte datadrivet och i mångt och mycket är det värdet som skapas som är målet. En datadriven process utgörs av (åtminstone) fem beståndsdelar:

  1. Vilken värdeökning vill man ha
  2. Samla relevant data
  3. Modellera (vad, hur mycket och var)
  4. Analys (får fram insikter kring varför man ser det man ser)
  5. Konkreta handlingar och prioritering

Data prototyping loop

En välutformad loop inleds med att definiera vilken typ av fråga man vill ha svar på och utifrån detta samla relevant data. Detta leder till att modelleringen (där man besvarar frågor som vad, hur mycket och var) och analysen (där man drar insikter kring varför man ser det man ser) får ett tydligare syfte. Detta kan sedermera leda till mer konkreta handlingar och prioriteringar av dessa som genererar en värdeökning för företaget.

Baserat på denna kan man sedan gå tillbaka och omformulera frågan man vill besvara och vilken data som behövs för detta. En datadriven organisation innebär inte att det är ett fåtal personer som gör superavancerad analys utan en organisation där alla förstår värdet av data och kontinuerligt vill skapa förbättring med hjälp av den. I en sådan organisation används de fem stegen av samtliga i organisationen och i allt från små individuella frågeställningar till organisationsvida beslutstaganden. Ett kriterium för att bli datadriven är att inbygga tillit och acceptans kring värdet av att arbeta på ett datadrivet sätt.

 

Detta är så stort och komplext, hur blir vi datadrivna?

Detta är oftare lättare sagt än gjort och många organisationer som vi pratar med vet inte hur de ska börja och har svårigheter att skapa värde ur den data man har.

  • Ska man göra ett big-bang projekt där man implementerar nya arbetsprocesser, organisationsdelar och system?
  • Eller ska man börja i ett hörn och successivt arbeta sig utåt?
  • Ska man ta fram en strategi, ska man börja implementera analysverktyg, ska man fokusera på datainsamling och datalagring osv?

Självklart måste man förstå att bli datadriven inte är något enkelt eller något som sker över natten. I slutändan är det hur väl data används och skapar värde som definierar ett datadrivet företag.

Vi tror stenhårt på att för att bli framgångsrik i sin data-användning så måste man jobba iterativt och testa sig fram. Vi är också övertygade om att en bra väg för att börja resan med att bli mer datadriven är genom Data Prototyping.

 

Vad är en Data Prototype?

För oss är Data Prototyping ett snabbt sätt att påvisa värdet av data genom att man bygger en avgränsad prototyp som använder data och analyslösningar för att lösa ett specifikt affärsproblem.

Tanken är inte att det ska vara den perfekta lösningen direkt utan ett redskap för att få en djupare förståelse för vad man kan och behöver göra inom området.

Med en Data Prototype kan man testa om det är möjligt att genomföra en föreslagen lösning, vilket antingen skulle kunna leda till storskalig implementation, en småskalig ”beta”-tjänst eller som input i en strategi kring hur man ska jobba med data. 

En Data Prototype bygger i grunden på intern och/eller extern data som på olika sätt samlas in, bearbetas och levereras så att det i slutändan kan leda till någon form av handling och värdeökning för företaget. Exempel på Data Prototype är churn prediction, dashboard eller insikter kring kundbeteenden.

Dessa kan anpassas och se ut på många sätt och kan ta användning av en rad olika mjukvaror, beroende på hur frågeställningen lyder och vilka övriga specifikationskrav som finns. Genomgående i arbetet med en prototype är affärsförståelsen grundläggande, varför det är ett hypotesdrivet arbetssätt.

 

Varför bör man bygga en Data Prototype?

Med en förståelse av vad en Data Prototype kan vara, är det viktigt att lyfta fram de fördelar och nyttor som processen för med sig:

  • Att ta fram prototyper är ett sätt att snabbt bli konkret om idéer och behov och utvärdera dess potentiella värde
  • Det är ett sätt att lära sig att arbeta med data och analys på ett mer smidigt sätt med en flexibel men konkret metodik
  • Det är ett pedagogiskt och överskådligt sätt att testa / bevisa en hypotes och visa potentiella effekter för hela organisationen
  • Man kan lätt ta det ut till organisationen för att förstå hur mottagliga dem är för denna typ av beslutsunderlag och analyser och om detta inte är fallet, kan man förbereda organisationen innan storskalig investering görs

Genom möjligheten att snabbt kunna testa och validera idéer och initiativ kan företag ha ett snabbare, precisare och mer iterativt arbetssätt. Om man kan kvantitativt testa sina hypoteser på en grundläggande nivå i ett tidigt stadie undviker man stora, tidskrävande och riskfyllda projekt och kan istället omvärdera sina initiativ.

Denna mer iterativa och kortsiktiga strategi gör att man kan prioritera rätt initiativ, bygga mer relevant kompetens och hela tiden arbeta närmare sina kunder. Det gör också att en data prototype passar alla typer av bolag.

 

Hur bygger man en Data Prototype?

I arbetet att ta fram en Data Prototype tycker vi att man ska jobba efter tre huvudsakliga steg som byggts för att på bästa sätt möjliggöra för de fördelar nämnda ovan, att slå igenom.

  • Börja från slutet
    • Inled med att skapa en bild av vilket eller vilka affärsproblem du försöker lösa
    • Definiera vem som är målanvändaren och vem som kommer att få resultatet och anpassa arbetet framåt efter detta
    • Försök att visualisera och konkretisera vad slutprodukten är och hur ser det ut – något så enkelt som att rita upp på ett tomt papper är superbra!
  • Rita upp och bryt ner
    • Skapa en övergripande arkitektur för din Data Prototype – både hur du ska hantera information och teknik (nu låter det väldigt svårt och komplext, men håll det enkelt och rita upp de övergripande system och informationsmängderna du behöver)
    • Bryt ner det i dess beståndsdelar och förstå vad du behöver
    • Man kommer förmodligen behöva repetera vilka datapunkter man behöver, så bara börja! och försök inte göra det perfekt direkt
    • Gå ut i organisationen och försök få tag på data – det tar alltid lång tid
  • Bygg och visa, bygg och visa, bygg och visa
    • Gör första v0.1 så fort du får tag på vissa data, gör det ibland innan du får data!
    • Förstå data och datakvalitet och anpassa modellen utefter detta
    • Rengör data manuellt (men notera ner det). Om du försöker automatisera allt tar det väldigt lång tid att nå resultat
    • Visa ditt jobb snabbt för att få feedback från mottagaren eller någon annan tidigt

Detta är det övergripande arbetssättet vi tycker man ska ha när man bygger en Data Prototype, vi kommer i ett senare blogg-inlägg vara lite mer konkreta kring verktyg och teknik som man kan använda när man bygger en Data Protoype.

Vår uppmaning är dock att det viktiga är att man börjar skapa en förståelse för vad man vill åstadkomma så blir teknikvalen mycket lättare.  Tänk att det i detta skede inte behöver vara perfekt, så jobba i verktyg som är lättarbetade. 

 

Nästa steg med en Data Prototype

Genom möjligheten att snabbt kunna testa och validera idéer och initiativ kan företag ha ett snabbare, precisare och mer iterativt arbetssätt. Om man kvantitativt kan testa sina hypoteser på en grundläggande nivå i ett tidigt stadie undviker man stora, tidskrävande och riskfyllda projekt och kan istället omvärdera sina initiativ.

Denna mer iterativa och kortsiktiga strategi gör att man kan prioritera rätt initiativ, bygga mer relevant kompetens och hela tiden arbeta närmare sina kunder. Det gör också att en Data Prototype passar alla typer av bolag.

Hur en Data Prototype används eller tas vidare i organisationen är ett beslut som kan tas först när man har testat och varierar mellan alla tänkbara situationer. Det som står säkert är att man kommer kunna ta ett mer välgrundat beslut med en Data Prototype att luta sig mot.

Lycka till med era datasatsningar!

 

Vill du veta mer om Data Prototyping så tveka inte att höra av dig. Ta kontakt genom att klicka på knappen nedan så kan vi inleda en förutsättningslös diskussion.

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July 23, 2018No Comments

Rules for giants – Trend #4 of 8 from SXSW

Evolving economies mean evolving regulations

A popular subject during SXSW was the discussion around politics and responsibility. The Mayor of London, Sadiq Khan was one of the proponents of new types of regulations to meet challenges we face in the digital era of today. “Evolving economies must mean evolving regulations” he said. He talked about the importance of handling fake news and protecting people online. Discussions on policymakers and governments’ roles in society, and their need to be more proactive than reactive, was also a clear message from Austin.

America needs to figure out the principles that we need to operate under. Other countries already have

- Mark Zuckerberg – Founder of Facebook

Tech to create benefits for all people

The ongoing technology development is beneficial of everyone and we are experiencing a historical change and uncertainty. For example the speed of change, especially change driven by technology is affecting our economies and the society. Technology is disrupting and shifting the way we do everything, our economy, the jobs available, the way we travel, the way we read news, how we communicate and interact with each other. It strikes across so many layers of modern citizens. But how do we utilize technology to better for everyone in the society? Khan argues that the public also have a right to be heard, and that this is something he believe has been absent in recent years.

 

The impact of social media

Social media is an enormous driver to share information. The largest digital players have brought huge value to the society, such as an easier access to people we love. However, there are growing concerns about how the biggest companies on our planet are impacting our lives. Khan means that the impact is profound and should worry democracies around the world. Religious hatred, fake news, algorithms blinking us to different point of views – putting us to extreme, terrorists using social media to mobilise and radicalise others.

 

The responsibility of social media giants

Mayor Khan read out loud some of the tweets that has been directed to him. “I don’t read this out to be portrayed as a victim or someone looking for sympathy. But rather to raise the question – what happens when people see these things in their timelines, or experience it themselves? Or becoming politicians themselves in the end?” His point of view is that we simply must do more to protect people online. Social media platforms have legal obligation to look for people that break the law, and this is happening quickly. The German government has changed the law so that social media companies get heavy fines if they do not report and remove this kind of content quickly enough.

 

Proactively shape the future of tech

Our economies have always needed new regulations when the environment changes. Evolving economies must be equal to evolving regulations. Rather than blaming companies for being too innovative, focus should be on proactively change regulations. Khan argues that it is our generation’s turn to match the scale of challenges today. We need to make sure to embrace the enhancement of tech and proactively shape the future of it and how it can help us create a better society. We are just at the beginning of this journey – companies, and politicians and tech can work together. “I’m optimistic – that we will be able to create a better, more inclusive future for us all.”

Evolving economies must mean evolving regulations. Rather than blaming companies of being more innovative than regulation, politics should keep up with regulation

- Sadiq Khan – Mayor of London

Rules for everyone

There are rules that should be obeyed by everyone. Stand up for yourself and stand up for the regulations. How is it that rules apply differently to small and big companies? Individuals always pay taxes whereas big companies do everything they can to find loop holes.

 

Governments should be more digital

In a discussion with James Barbour, spokesperson and Head of Press Diplomacy at the EU Delegation to the US and Shawn Powers, Executive Director at US Advisory Commission on Public Diplomacy, among others – they talked about artificial intelligence inside the US government, that the focus of AI is always negative – the “dark side”. They requested more discussions on productive ways of using these tools and the power of these technologies. For example how to interact with the public and communicate the information about policies in a better way? A digital ID can get a refugee the ability to vote. Estonia is an example of a country that has come a long way when it comes to digitalization of government practices, for example with Digital passports.

 

Proactive governments

Governments are being reactive to the challenges of today. So how can we become more proactive? When issuing visas and passports – we are spending a lot of human resources to answer questions – we could instead use a sophisticated chatbot for this. We also need to initiate conversations between governments and the private sector. If they will bridge the gap between each other, it will be easier to be more proactive, both when it comes to legislation but also when it comes to new technology and the development of society.

 

Verification will become important

We need to be able to own our truth. Therefore, it will become increasingly important with verification of news and other communication, to make it trustworthy and eliminate fake news. “This is a verified message from the EU or the US” that will be standard in the near future. Today you can put anyone’s face out and say anything. Museums and library’s content is the most trustworthy source of information.

 

 


 

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SXSW is one of the biggest digital conferences in the world, and a global meeting place for the world’s most innovative technology companies and people interested in how disruption can transform their business and everyday lives. The event takes place during during 10 days each year and this year Cartina had the chance to be part of it.

This series consists of 8 global mega trends that business leaders, experts, innovators and disruptors talked about during the days in Austin. If you want to read the full report, click the button above and we will email it to you.

 

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July 17, 2018No Comments

Digital changes beliefs – Trend #3 of 8 from SXSW

The world is becoming infused with digital. The idea that a company should focus on its core competence doesn’t belong in the digital world. We need to look at how to solve problems in a completely different way, based on the capabilities that technology enables. Tim O’Reilly, the Founder and CEO of OReillyMedia explained this by making examples from five false “truths” of today:

 

In 2018, we are still trying to revive the old economy

...rather than inventing the future that is now possible

We need to start understanding the purpose and power of AI and algorithms since their scalability can help us create a better world. We are stuck in the old way of doing things and do not recognize the possibilities of shaping the future the way we want it with the help from new technology.

The idea that a company should focus on its core competence doesn’t belong in the digital world

- Tim O'Reilly – CEO and Founder of OReilleyMedia

 

In 2018, we are afraid that tech will put people out of work

...but in fact it will create millions of new ones.

Amazon automated warehouses with 45 000 robots – and created 250 000 new jobs due to a new business model with radically lower prices, creating demand for something that didn’t really exist and opening a platform for other to provide their services. Ecommerce today employs more people than the physical retail. We need to give people new superpowers – and put them to work, instead of competing with robots over the same kind of jobs.

 

In 2018, people still believe that tech is a magic bullet

...but it takes a massive amount of shots to be successful.

It’s the organization around that makes it work. Companies need to focus much more on aligning ways-of-working to realize technology potentials. We need to develop entire new business models, but we cannot do anything with just one shot, and we cannot only rely on the technology – the ecosystem around it also needs to work.

 

In 2018, we still think that companies should maximize profits

...instead they should maximize sharing and building an ecosystem with open source solutions.

We need to work together to create greater things and broaden our perspectives.

 

In 2018, we still don’t understand the value of humans

...technology can augment our capacity but we need to focus more on educating each other, creating networks of collaboration and learning and create partnerships between machines and humans.

We need to look at the world from a new perspective, where the notion of physical and digital is blurring into each other and where the eco system thinking prevails. Quarterly profits must be translated into yearly and decennial costs that are effects of short-term, unsustainable solutions filling the pockets of shortsighted shareholders. A business will always need to deliver profits, but in a responsible way. As Tim O’Reilly’s caption said “What’s the future? It’s up to us.”


 

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SXSW is one of the biggest digital conferences in the world, and a global meeting place for the world’s most innovative technology companies and people interested in how disruption can transform their business and everyday lives. The event takes place during during 10 days each year and this year Cartina had the chance to be part of it.

This series consists of 8 global mega trends that business leaders, experts, innovators and disruptors talked about during the days in Austin. If you want to read the full report, click the button above and we will email it to you.

 

Visst borde fler läsa detta? glöm inte att dela!
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Cartina has since 2013 helped both multinationals and startups translate digital opportunities into lasting and profitable business. We have since the start mainly worked with management services but are now expanding our offering with tech & design.

With a desire to develop oneself, clients and colleagues, our team of several senior digital experts take pride in delivering sustainable solutions that matters for our clients and society. 
Cartina is founded and owned by the investment firm Acacia Asset Management AB together with partners in the firm.


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