machine learning

Interview with Data Scientist Alexander Beck, PhD

Image of an interactive web of dots.

Alexander Beck, PhD, is a data scientist with a demonstrated history of utilizing machine learning and data science in the financial sector, especially asset management. Alexander has a 10-year track record in business applicable artificial intelligence research, including in the fields of financial markets and customer analytics.

Data scientists analyze and interpret mountains of complex digital data to inform decision-making and strategic processes. When it comes to digital procurement and supply chains, data scientists can automate workflows and employ predictive analytics to more accurately forecast demand or disruption.

IBM predicts that demand for data scientists will increase by 28 percent by 2020, with Finance and Insurance, Professional Services and IT generating the most demand. This role often requires an advanced degree, such as a master’s or PhD. For those who are looking to add data scientists to their teams or want to learn how to best work with data scientists, Alexander shares insight into his function, how he assists the business to make informed decisions and automate workflows, and highlights some common misconceptions about data scientists.

Stacy Mendoza, Digital Marketing Specialist

Information Needs Drive Cognitive RPA

A computer-generated image of documents and files.

Industry Challenges

When it comes to Robotic Process Automation (RPA) within a digital transformation project, the clear objective is to move all processes into a controllable, fully-automated workflow. This is achievable when processes need to use structured data. However, the most expensive and business-critical processes involve human workflows using complex, document-based information. Achieving the same levels of automation realized from structured RPA-enabled processes becomes much more challenging because the needed information isn’t always easy for a system to locate—much less successfully extract—from a document. Without a precise solution for getting access to document-based data, automation is adversely affected.

Finding the Right Solution

The answer is to approach cognitive RPA projects by understanding the level of “maturity” required with respect to the level of document automation your project requires and compare that with your peer’s experience within your industry.

This includes getting a solid foundation in what are current best practices regarding automation and understanding the various options for injecting document automation into RPA projects. Not all vendors approach a solution in the same way and not all capabilities are equal.

Greg Council, Vice President of Marketing and Product Management

Tips for Buyers and Providers to Build Stronger Business Relationships

Best practices and tips for strategic buyer-provider relationships.

The relationship between buyers and providers can be a tricky one, especially when operating across multiple continents. Speaking during a podcast interview with Dawn Tiura, Sean Delaney, Vice President of Sales for cloud platform Determine, draws on his experience as both a buyer and provider to share best practices for relationships that are sustainable and strategic.  

WORK ON YOUR SOFT SKILLS

Technical expertise is valuable, but your ability to establish a rapport with customers is important for sustainable relationships. “Candor is important because there's a large degree of personal credibility that buyers are putting on the line when selecting a vendor," says Delaney. "That needs to be understood as a seller and we need to make sure that we don't break that trust. That's our role.” 

Stacy Mendoza, Digital Marketing Specialist

Getting Smarter with RPA

Machine learning capabilities allow a bot to identify a mistake and apply a fix.

As the Robotic Process Automation (RPA) market matures, enterprises are taking stock of lessons learned and exploring ways to take existing RPA capabilities to the next level.

Early days were characterized by excitement over the dramatic productivity and cost-saving benefits enabled by RPA. Over time, however, the limitations of rules-based bots have emerged. For one thing, basic RPA tools can’t adjust to new conditions or changes in their environment. Even the slightest deviation from the process they’re trained to follow triggers an exception that requires a human to step in, thereby sapping the solution’s productivity.

Another issue is the complexity surrounding deployment of RPA bots. While instructing a bot to perform a task is relatively easy, it does involve a level of programming expertise. Most end users of RPA are on the business side and lack the requisite technical knowledge. That means that setting up a bot requires an RPA programmer. Demand for RPA skills, meanwhile, is through the roof.  (Witness the volume of urgent “we’re hiring” notices on LinkedIn pleading for people with Automation Anywhere, Blue Prism and UiPath certifications.) As a result, because the intervention of scarce technical resources is required, bottlenecks often occur when deploying a bot for a business user.

Alex Kozlov, Director of Content for Softtek US & Canada

Dropping the L in Machine Learning…is Machine Earning on the Horizon?

blockchain

At Singularity University’s Global Summit, keynote speaker David Roberts posed the question, “What if machines made more money than people?” Sounds crazy…but is it? With Blockchain, could that be the way of the future?

I confess that when he asked the question, I still didn’t feel comfortable enough with the concept of blockchain to have an informed opinion on the viability of it. So I did what 77% of people do when seeking information on the Web…I Googled it…and I kept Googling it until I found articles that dissected the concept well enough that it made sense. If you are equally confused by the term, hopefully this analysis will benefit you as well…because rest assured, you WILL need to understand it—especially if you work in sourcing, outsourcing or supply chain as the potential is unlimited.

Fundamentally, blockchain allows consumers to transact directly with one another without the need for an intermediary, like a bank. If you use Paypal and select “eCheck” as your payment method to reimburse a friend for say a concert ticket, it appears to go directly from you to them. In actuality it first has to clear your bank, which can take 3-5 business days, or up to 8 days if another country is involved. Blockchain removes the middleman by using digital currency (aka cryptocurrency) which can be spent with companies or people who are set up to accept it as a form of payment. The digital currency can be converted to cold, hard cash, but with thousands of companies now taking digital payments it is not really the norm.  

Sarah Holliman, Chief Marketing Officer, SIG