In recent times, my conversations with general managers have inevitably veered to the topic of Artificial Intelligence (AI) and Machine Learning (ML). What puzzled me was the lack of true understanding of these terms and the imprecision with which they were being used.
Automation is the most popular trend in today’s world of business. It is general consensus that automation increases productivity, leads to higher returns, and makes life better, but there are broader differences on how it will impact employment levels and society as a whole. The big question is: are we prepared to deal with its implications?
The spread of fake news is a common problem that online and social media are facing. There are different solutions that companies are applying to avoid this: Human fact-checking or artificial intelligence programs to solve the problem with technology. Both methods have failed so far. So what is a potential solution?
Generate Insights. Optimize Budget. Increase Revenue. Ensure Efficient Knowledge Management. Increase Productivity. Maximize Efficiency. Enhance Collaboration. Manage Timely deliverables and dissemination.
Practically every business today owns a website. Whatever industry you work in, and whether you’re selling direct to consumers in B2C or providing a knowledge portal for B2B clients, your website is probably your most important digital channel.
Knowledge management (KM) is the process of capturing, developing, sharing, and using organizational knowledge. Purposeful, concrete, and action-oriented knowledge management programs can yield impressive benefits for both individuals and organizations.
Cognitive technology is the next big cost saving initiative in the world of procurement. We have taken a look at various cognitive solutions that are being implemented across industries and how they constructively evolve the overall maturity of the procurement organizations. The infographic below details these industries we have covered and their specific applications
One of our clients invited our chief strategist to help them assess the proposal they had received from a prominent AI tool. See why he believes AI providers are not spending enough time on the analytics value chain before pitching their services.
Warren Bennis once said that the factory of the future will have only two employees – a man and a dog. The man will be there to feed the dog. The dog will be there to keep the man from touching the equipment. Are we in the vicinity of that future yet?
The world is generating data like never before and some companies have created very sophisticated big data use cases. Whether you consider this a violation of your privacy or an exciting sign of progress, these use cases exist. Law makers are playing catch up and the European Union is leading the field with its General Data Protection Regulation.
Our team attended this year’s GE’s Minds and Machines conference in San Francisco. Read more to find out why we believe the question is no longer if digitization leads to better customer experience and higher productivity, but about the how behind it.
Listen to Evalueserve CEO Marc Vollenweider’s second appearance on the Innovation Ecosystems podcast.
Big Data is the buzzword of the moment, but is it crucial for all organisations to invest in big data? Does it always make business sense to do so or are there alternatives that have potendial for much greater ROI?
Monitoring changing regulation environments can be a daunting task for global companies. In this post, we review how we helped a Fortune 500 client in dealing with this, by making use of our mind+machine approach to bring in efficiencies, data quality and granularity.
As data flows through the analytics value chain to be distilled into insight or even knowledge, it passes through several stages. Different stages require a different mix of mind+machine. We have codified the analytics value chain into 8 simple steps.
The Internet of Things (IoT) has been in the news over the last few days, because an estimated 100.000 internet connected devices fell victim to a cyber attack. Should we consider the Internet of Things as a blessing or a curse?
When it comes to analytics use cases, mind alone tends to be too expensive, too slow. Machine alone can’t deliver real insights or knowledge. Success lies in knowing how to mix the two. The key lies in knowing how to find the efficient frontier.
The number of incredible opportunities with great potential for mind+machine is large and growing. Many companies have already successfully begun leveraging this potential, building whole digital business models around smart minds and effective machines. However, despite the potential for remarkable return on investment, there are pitfalls.
The number of incredible opportunities with great potential for mind+machine is large and growing. Many companies have already successfully begun leveraging this potential, building whole digital business models around smart minds and effective machines. However, despite the potential for remarkable return on investment, there are pitfalls.
In his fifth video, Marc explains the five different building blocks that help us deliver solutions for our clients: analytics engine, productivity tools, workflow, dissemination, and knowledge management. Watch the full video to learn how these building blocks contribute to our work.
Do you think that Artificial Intelligence can do everything? In the Silicon Valley there is a firm belief in the power of machines. Marc Vollenweider (CEO, Evalueserve) doesn’t think so! Watch our fourth video to learn more.
Banking success hinges on continuous transformation, which is a truly herculean task. What is the best course in light of recent sector trends? ‘The Future of Banking’ seminar discussed critical problems facing the sector, the pros and cons of different banking approaches, and if technology will emerge as its backbone in the near future.
Think automation: will it make humans redundant or obsolete in their work environments? Will the increasing adoption of automation to remove manual effort lead to job cuts – especially in the knowledge services sector? We do not think so.
In his second video, our CEO Marc Vollenweider talks about the four benefits of our mind+machine strategy for our clients: 1) Productivity increases 2) Reduce time-to-market 3) Quality improvements 4) Provide new capabilities to give our clients an edge in the market.
See the list of 10 must-watch TED Talks on mind+machine™ in our latest blog entry.
By leveraging automation to allow our analysts to focus on more value-adding and challenging work, we enhanced our services, which resonates very well with our clients. It is great to see that we are not the only firm which is thinking along this line.
Evalueserve’s strategy is based on mind+machine. Now, what is mind+machine? Mind+machine is the optimum mix between the human mind, supported by a machine. Neither one of the two works on its own. Human only is too expensive, machines only simply doesn’t work.
How will automation impact work in the future? In contrast to the negative scenarios about large-scale job losses frequently portrayed in the media, findings from research by McKinsey paint differnt picture of how automation is likely to affect jobs.
It is more useful to think of automation’s impact at a task-level, rather than thinking about it at a job-level. For complex knowledge-based tasks and workflows in the enterprise, it is best to combine human and machine intelligence – mind+machine.
There has been a flood of books on this topic in the last year or two. We have compiled a reading list of the top business books on automation and the future of work.
In our modern, data-driven business environment, banks and other professional services firms place a premium on efficient and reliable information management. What can business information services do to meet those expectations?
Evalueserve has made great headway for our clients with our mind+machine™ approach. Our CEO Marc Vollenweider takes a look at the impact of our automations in this post, revealing just how many working hours we can “automate away”.
These days the media are full of articles about the age of the machines that can do almost everything using big data. Is this really the case or is human intervention still important? And what is the true meaning of ‘almost anything’?