Before any organization can do business with an external vendor, it needs to examine its data privacy protocol against new legal requirements. Recent legislations like General Data Protection Regulation (GDPR) in the EU and the California Consumer Privacy Act (CCPA) in the U.S. has cast a spotlight on the handling of consumer data, especially the way it is shared among third parties. Organizations of all sizes in every industry are upgrading the vetting processes to make sure that new vendors don’t bring additional risks.
These risk assessment processes contain several moving parts, and a mistake at any point along the way can jeopardize the result. The easiest way to pinpoint the holes in your organization's vendor vetting workflow is to review the entire process from beginning to end and examine the opportunities for data privacy lapses. Here are four common pitfalls to look for:
1. Overlooking Contract-level Details
Amid all the changes happening to the regulatory landscape, it’s easy to overlook errors in the language of your contracts. In a short window of time, contract language—on old and new agreements—needs to be updated to provide consumers with new legal protections and redefine business-to-business relationships with any party that touches consumer data. If contracts are being negotiated in that window, some terms might slip through the cracks and expose you to new risks.
What is a simple definition of intelligent automation?
Canda Rozier: I think intelligent automation is a fully holistic approach for business transformation that lets companies start to analyze data, provide analytics on the data and deliver digital solutions to optimize business processes and tasks. I think one of the things that has really struck me as I've learned more about and become engaged with intelligent automation is that it's as important to understand what it's not as to understand what it is.
A lot of intelligent automation projects fail or don’t provide results – why?
Lawrence Kane: It's not a panacea, and it really needs to be implemented systemically because it's a program. It shouldn't be a one-off, because you have to look at your tools and processes and how the enterprise creates value and understand where are the places that you want to go and automate. Where are the places you want to stop doing things, where are the areas that you need to change doing something, right?
I recently went back to read an article that I bookmarked a while back on the predictions for 2020. Forget self-driving cars and flying cars; Popular Mechanics magazine predicted in 1951 that every family in the 21st century would have at least one helicopter in their garage. They also predicted in 1957 that every road and street would be “replaced by a network of pneumatic tubes,” and your car would only need enough power to get from your home to the newest tube.
Dave Evans, the chief futurist for Cisco Visual Networking, actually predicted in 2012 that he'd be out of a job by this time because, as he forecasted, everyone would be able to predict the future themselves.
Automating Everyday Tasks
I wasn’t alive when Popular Mechanics made its predictions, but I was alive for the statement by Dave Evans. What I know for sure is that while his prediction for companies to make data-informed decisions is slowly coming to fruition, we are far off from a world without futurists. What amazes me is that most automation predictions were in the form of self-driving cars rather than taking place in everyday life.
SIG University Certified Intelligent Automation Professional (CIAP) Program graduate Mike Morsch has led an RPA and IA journey before. He discusses the steps a company must address to ensure a successful Intelligent Automation journey to produce the best long term and sustainable outcomes.
In the CIAP program, students gain knowledge of automation technologies, learn how to identify the correct opportunities to build, run and sustain a successful automation program, and will understand the true potential of IPA technologies when adopted correctly.
I found the CIAP certification training to be an excellent baseline for anybody looking to embark on an intelligent automation (IA) journey. Senior leaders looking to sponsor a program really need to think through how they can best start the program to ensure both leadership and associates understand the focus of the program. It is easy to get caught up in “cost savings” and getting fast and visible results to justify a program. While quick wins are always a good way to show the value of any initiative, the long term benefits available in taking a broader view will pay the most dividends on investment over time. In thinking about my own experience and the lessons learned in the CIAP program, I would suggest to anyone considering IA the following areas of focus to create the best program.
Three major trends are reshaping the industry: a major rethinking of outsourcing vs. moving in-house, advanced handwriting recognition becoming mainstream and the increased need and reliance upon data science. This article explores these trends, as well as what they mean to enterprises and their service providers.
Rethinking the Benefits of Outsourcing
Just recently, HFS research published an article on the acceleration of insourcing operations that service providers currently provide. Why is this? One of the primary reasons is the renewed interest in automation. Also, it is the perspective that with automation, reliance upon manual labor is reduced, the outsourced version of which is still the primary business model of many service providers both large and small.
Historically, if an organization wanted to rid itself of low-value, but necessary tasks or processes, the best option was always to outsource these functions to a service provider that could provide the same capability at less cost through economies of scale. With automation, there is the promise of handing over the work to “bots” that can be deployed anywhere and whose costs are not sensitive to typical wage arbitration. A bot costs the same whether it is deployed onshore or in low-cost regions. HFS calls this “going straight to digital.”
Greg Council, Vice President of Marketing and Product Management
Excitement continues to grow around the capabilities of applying automation to various business processes, particularly using robotic process automation (RPA). The enthusiasm is appropriate because early initiatives to automate rote, low-level tasks have seen very positive results with high levels of automation achieved, which frees up staff to spend time on higher-value, more complex tasks.
Low variance, rote and simple tasks have been the primary focus for the majority of RPA projects because they are easy to define and the complexity related to handling different types of exceptions can be avoided. According to AIIM’s 2018 report titled, “Enhancing Your RPA Implementation with Intelligent Information,” the top processes across different functional areas include well-defined processes that operate on structured data. The report highlights processes such as inventory management, payroll, order management and records processing, all of which benefit from standardized data and straightforward tasks. The result is close to 100% automation.
Automating Key Activities
As most organizations become more adept at process automation using these tools, attention starts to turn to processes that involve key activities within an organization. Processes involving customers need to be sped-up and more convenient. Processes involving the delivery of products and services need to be better controlled and accelerated. It is not just about automating tasks to lower costs. In the same AIIM report, it found that organizations see RPA technologies as a way to deal with reducing errors within processes while at the same time, improving data quality and customer service.
Greg Council, Vice President of Marketing and Product Management
As more enterprises and service providers adopt cognitive automation to improve their manual processes, reading the tea leaves or better yet, examining case studies suggests a new job landscape with some fairly drastic improvements in efficiency.
Harvard Business Review (HBR) provides a useful summary article explaining how to deconstruct work into tasks that can be automated. Here three characteristics are used to assess our work:
Repetitive vs. variable work;
Dependent vs. interdependent work; and
Physical work vs. mental work.
Any automation assessment model should also take into consideration the nature and complexity of both the inputs and outputs onto which we can overlay these three characteristics to assess the impact of automation based upon the nature of work itself.
Basic automation has arguably had the highest level of impact so far. It is applied to rote, highly repeatable and low variance tasks. For example, basic automation supports the IT back office such as regular back-ups of data or automated provisioning of software resources (such as email accounts and CRM access).
These activities can be highly automated due to the nature of the work and low probability of exceptions to workflows. The inputs can be highly structured with very little variability while outputs are often binary. The result is either a successful completion or an exception. These tasks are very independent with interactions typically only with application interfaces. There is very little mental effort required.
Greg Council, Vice President of Marketing and Product Management
Negotiation is a fundamentally human act between two or more people. When it comes to vendor negotiations, this is driven by the prior (and future) relationship between human counterparties. While digital processes can support this mission, if a key decision maker involved in a vendor negotiation goes on vacation, changes jobs or gets hit by a bus, the negotiation will stall or scramble to reach a conclusion. It’s a good reminder that no matter what role artificial intelligence (AI) plays in a negotiation, the negotiation process and award decision are driven by humans.
For those participating in the vendor negotiations, it is likely that their companies book travel through a digital app that aggregates and discounts airline tickets. It is also likely that the hotel and ride to the meeting are also booked via digital apps. Thus, the technology stack that supports this “in-person meeting” is being mediated by a variety of digital apps (many of which already leverage AI), apps that support (rather than displace) the crucial in-person business negotiation by reducing the number of low-value transactional tasks and phone calls.
Artificial Intelligence (AI) is creating the next largest divide not only between people, but also between organizations. Taking full advantage of AI requires a two-pronged approach by any enterprise. First is to identify the business processes that can gain most from the introduction of AI. Second is to treat AI as a key component in any reengineering effort with quality data as one of the highest priorities.
Since one key beneficial attribute of AI is that it can replace tedious, low-value human tasks, it is important to target processes that enable staff to focus on other higher-value areas. The perspective of pragmatically tackling routine processes first is echoed in research presented by Harvard Business Review, which provides a useful construct by defining three types of AI: one applied for automation, another for delivering insight, and a third for customer engagement.
Data Science: the Key to Successful AI
Greg Council, Vice President of Product Management, Parascript
It was the very best one-day event I have attended in my life! The Midwestern Regional SIGnature Event, held on March 6 at the Minneapolis Central Library, was attended by 66 extraordinary third-party risk management and sourcing professionals. Not only was the agenda amazing, but every speaker delivered insightful content and engaged the audience. At the Executive Roundtable, we had thoughtful conversations about many issues. Tom Lutz from U.S. Bank led a “day in the life” discussion that lasted almost 45 minutes because so many people wanted to discuss what he was doing, and it prompted other conversations as well.
In our opening session, Linda Tuck Chapman, a Sourcing Supernova Hall of Fame inductee, knocked it out of the park by delivering an interactive workshop on third-party risk management. People said that their two hours of training FLEW BY. When the group joined back together, we had an incredible presentation by Rohan Ranadive from BB&T about building an AI-powered digital workforce which prompted so many questions, I had to stop them to stay on agenda! Then we had an absolutely inspiring one-hour talk by Nancy Brooks, the CPO of Best Buy. Nancy shared that she had declined previous invitations to speak, because she doesn’t care for speaking engagements, but she agreed to speak at SIG’s event because she had a story that needed to be shared about her team. We are thrilled that she joined us. She engaged everyone with Best Buy’s story the entire time and Nancy’s team was so proud to be there.