How data, automation and AI are transforming Business Process Outsourcing into a competitive advantage

When IBM Consulting’s Neeraj Manik spoke recently with a large pharmaceutical client about how to streamline and improve its front-office and back-office financial processes, he pointed to a web of interconnected business challenges the organization was facing: “too many invoices, too many suppliers, too much money being paid to suppliers,” as Manik put it.

Manik, VP and senior partner for IBM Consulting, outlined a massive opportunity to strategically redesign the client’s finance operations and payment processing by leveraging AI, data analytics, metrics and automation. Ultimately, modernizing these processes could save hundreds of millions of dollars, improve the employee experience and make the company more agile and competitive, he says. Manik sees leveraging this technology as a fundamental change from years past, when a company might outsource business processes to save as little as 30% without considering how outsourcing might affect organizational efficiencies, job accuracy, and employee and client experience.

Technologies such as AI and automation have transformed the outsourcing market and BPO services, giving companies the ability to create efficiencies while also modernizing processes rather than relying on offshore outsourcing.

Labor arbitrage, or outsourcing labor to the lowest-cost workforce, has been the central strategy associated with business process outsourcing (BPO) for years. It often meant sourcing customer support, information technology and other office operations from countries with lower costs of labor. Today, though, technologies such as AI and automation have transformed the outsourcing market and BPO services, giving companies the ability to create efficiencies while also modernizing processes rather than relying on offshore outsourcing.

Technology-enabled business process operations, the new BPO, can significantly create new value, improve data quality, free precious employee resources, and deliver higher customer satisfaction, but it requires a holistic approach. Tapping into AI and automation helps businesses streamline and strengthen their operations, while providing rich information that helps enterprises quickly predict and respond to trends and threats alike.

Not only do companies that work with IBM Consulting get IBM’s experience in process design and business strategy; they also get the added bonus of IBM’s deep partnerships with companies like ServiceNow, Celonis and Salesforce. Ultimately, instead of being forced to focus on a single solution or technology, organizations can partner with IBM Consulting to invest in broad, transformational business initiatives and outcomes.

The new BPO is no longer just about cutting operational costs. When done right, it can make a business flexible, smarter and able to quickly scale to meet shifting market conditions. “Modern BPO is a creator of growth, differentiation and competitive advantage,” Manik says.

Spotting hidden opportunities

At a time of rising costs, talent constraints and economic uncertainty, technologically enabled BPO offers an opportunity for companies to build intelligent workflows and leaner processes across finance, human resources, procurement, supply chain and customer operations. According to organizational consulting firm Korn Ferry, more than 85 million jobs could go unfilled by 2030 because there aren’t enough skilled workers to take them. The new BPO enables companies to quickly access more expert, technical, functional and industry specific talent than they can assemble in-house, driving new levels of efficiency across their business functions.

When working with clients, Manik looks for business opportunities that might be hidden under the surface: How can an organization’s BPO capabilities and methods enable a larger business transformation?

“What we can see is sometimes just the tip of the iceberg. There’s so much underneath this that can be unlocked in terms of business value.” Neeraj Manik

“It is our role as IBM Consulting to say, ‘how do we help you connect the dots?’” Manik says. “‘What we can see is sometimes just the tip of the iceberg. There’s so much underneath this that can be unlocked in terms of business value, that can improve how you go to market, how efficiently you run your supply chains, and how you can raise your margin profile.’”

For IBM Consulting, it’s not only about producing a list of recommendations for action, Manik says, but about following through and helping companies implement process automation and manage change, ensure adoption and get results.

The results can be apparent quickly. In the case of insurance giant Generali, for example, IBM Consulting rolled out two new AI assistants in France—one that helped upskill employees and another that interfaced directly with customers. Generali also became one of the first insurance companies to use AI to tackle the complex task of escheatment, or returning unclaimed assets and property. The new tools augmented the work of thousands of insurance agents, saving $1million in the first year of deployment, and increasing productivity by 5%. The program’s success in France led Generali to scale AI solutions internationally.

Seeing the bigger picture

As companies plot their investments in various transformation projects, Manik has one central piece of advice: “Make sure every decision you make about technology starts with and has a clear and direct link to business outcomes,” he says. “It sounds obvious, but it’s something that many C-suite leaders tend to forget as they get excited about new technology or a specific upgrade,” Manik says. It’s his role to help leaders take a step back and look at the big picture: “Don’t focus solely on what to adopt next,” he says, “but ask yourself why you need it in your operating model.”

One car manufacturer, for example, opened up a conversation by asking about an upgrade to its data servers. Manik reframed the question. “Hang on — we recognize your need to modernize, but to what end?” he told them. “How will this technology decision deliver the business impact you need?”

That question sparked a conversation about the carmaker’s larger goals, including its push to produce more autonomous vehicles. “Once we really understood that they are trying to change how quickly they can produce cars and different types of vehicles, we realized they needed a different supply chain design,” Manik says. “We are now on a path with them around supply chain transformation.

“Many times the conversation starts with technology, but migrates somewhere else,” Manik says. “Ultimately, it’s not about adopting new technology for technology’s sake, it’s about rethinking business processes and core competencies to uncover new business opportunities and areas to optimize — sometimes in ways that customers aren’t expecting.”

Source: ibm.com

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Experience personalization, the new enterprise mandate

Consumers continue to demand personalized experiences that deliver on their needs and preferences. Driven by key industry changes, this mandate is more important than ever.

Cookies are crumbling

The rise of the “platform economy” is exponentially increasing the life time value of customers and a cookie-less world is going to make targeting more challenging. Consumer privacy regulations are also continuing to challenge the ability for brands to drive marketing ROI. We think the battle ground for consumer mindshare will accelerate its shift from personalizing media platforms, to personalizing a brand’s customer experience platforms.  

Investment priorities are shifting

There’s a persuasive case for CMOs to start rethinking how they deploy their working dollars to drive ROI. There is also plenty of evidence to demonstrate how investing in the improvement of holistic customer experience delivers better ROI than investing in low performing media or advertising outlets. Organizations that have elevated the customer experience transformation to a formal business priority report a 3x higher revenue growth.  

Synchronization is what matters 

Driving personalized customer experiences is not a strategic challenge, it’s an operational challenge that brands have struggled to address. It requires process, data and technology synchronization and integration across the entire value chain — marketing, sales, manufacturing, logistics, finance and more. Fundamentally, companies lack the proper operating model that cuts across, and integrates across, enterprise functions in order to deliver customer personalization at scale.     

Implementing enterprise-wide customer experience 

We believe CMO’s must rise to own the enterprise-wide customer experience and not just the omni channel communication engagement. Key enabling pillars must be implemented to enable a personalization operating model within companies. This includes:  

◉ Moving customer ownership out of the front office and into the back office where it is a business operations priority and focus for every employee

◉ Creating a unique and persistent customer ID across the enterprise including demand platforms, supply chain and finance 

◉ Embracing new ways of working including agile and cross-functional teams 

◉ Integrating technology across platforms and business units

◉ Maximizing the value of analytics to drive personalization, automate processes and uncover deeper customer insights visible to all  

Next steps

In this experience era, organizations must pivot from one-to-one messaging to one-to-one experiences. They must shift from media outlets, to experience platforms. And they must structure operations to move from a focus on customer acquisition, to a strategy around lifetime-value growth. In this new world, companies and CMOs will come to rely  not only advertising agencies, but on a new breed of strategic partners to help them navigate new personalization imperatives. Strategic partners that can support the synthesizing of design, analytics, data, complex technology integration and business-transformation capabilities to drive industry-transforming customer experiences. They will use their experience and capabilities to unite organizations behind this collective effort.

IBM combines experience design, data and analytics and platform-implementation capabilities with Adobe Experience Platform and Adobe Experience Cloud solutions. Start your personalization journey.

Source: ibm.com

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7 steps to bridge user experience and business value

Defining “value” in agile product development is a challenge for organizations of all sizes. The definition is often framed and answered from an operational perspective, focusing on metrics like on-time delivery, productivity or predictability. Enterprises also define value from an outcome perspective focusing on financial benefit, user satisfaction or product scope delivery.

Numerous challenges arise when defining value from these perspectives. When looking at value from an operational perspective, it is possible to optimize metrics without actually realizing business or user value. From an outcomes perspective, it is not always apparent how the metrics relate to one another and they can even be at cross purposes. Furthermore, it is often unclear how to combine distinct values to prioritize or improve a process or outcome.

IBM Garage has developed a sequence of steps and versatile tools to align business and user value and we refer to this as value orchestration. We use value orchestration to guide product UX strategy and experience transformation and continuously deliver value in an agile environment. This methodology has been deployed and refined across multiple industries and Fortune 500 clients. Detailed below are the methods and findings:

Step one: Understand business value through user behavior

Value orchestration begins with the understanding that business value is rooted in user behavior. We define users as any internal or external end-user of a process or tool. A business owner realizes value when their users behave in a certain way. For example, if the business owner is running an e-commerce site, they recognize value when users (new or existing customers) visit the site, purchase products and respond to advertisements. If the owner creates a workplace optimization tool, they might realize value when their employees complete tasks, do so quickly and don’t make mistakes.  

In the cases above, it is straightforward to understand the business value of  visiting a site, viewing an advertisement, completing a task or making an error. It is equally straightforward to imagine how the business might measure changes in these behaviors and quantify the value of those changes.  

And so, the process begins with asking product stakeholders to specify how they would like their users’ behaviors to change. A business owner might say, “I would like my users to not abandon their carts so often.” Reviewing shopping data, the business owner can settle on a goal to reduce the cart abandonment rate from 75 percent to a more modest 50 percent.  

Having a goal and a measure of success provides several advantages to the effort. We can answer three essential questions to which we can align any number of individuals or teams: 

1. What are we trying to achieve? A reduction in cart abandonment from 75 percent to 50 percent.   

2. How will we know if our solutions are working? When cart abandonment goes down. 

3. When will we be “done?” When the cart abandonment rate hits 50 percent. 

Once we’ve arrived at our goal, the next thing we need to do is answer, “Why are users abandoning their carts 75 percent of the time?” 

Step two: Create a value model

With a goal behavior and measure identified, we build a value model that links the behavior changes to financial impacts. These formulas take the measures of user behavior as inputs and produce an implied financial impact. This financial impact will allow the team to compare the value of changes in user behaviors against one another. The value model also enables the product owner to establish a consistent benefit calculation, through which the ROI of future solutions can be assessed. 

Step three: Identify root causes

Step three in our process is to identify the drivers of the user behaviors we are trying to change. We call these behavioral drivers, root cause pain points.  

In the cart abandonment example we can start by conducting dedicated research through interviews and reviews of existing data to determine why customers abandon their carts. We will likely identify many pain points with varying degrees of significance. For this reason, we design our research and analysis protocols to sort root causes in order of priority. In this example, users might struggle to edit their order, access the “check out” page or enter payment information. By prioritizing these pain points in terms of impact on cart abandonment, we can prioritize the root causes to mitigate with solutions in the next step. 

Click to see prioritized root causes

Step four: Solutioning

Step four of our process is solutioning for the prioritized root causes. At this juncture, a design team receives a design brief which details:

1. What the solution is supposed to do: Reduce user cart abandonment.

2. How it is supposed to do it: Make it easier to edit an order, enter payment information, etc.

3. Applicable technical constraints: Functionality must be enabled for iOS and Android.

The team will select the root causes that they feel are the most readily solvable, and ideate solutions to those root causes. In our example, by reviewing the user’s pains with editing an order, the designers might re-create the editing experience to make it easier, faster and more intuitive. 

With a design drafted, it is time to validate. 

Step five: User testing

The fifth step of the process is to test our solution with users. We first create a testing protocol where we present users with the original pain point and ask them to describe and rate the pain quantitatively. We then walk through the new experience, asking questions to gauge ease, speed of use, intuitiveness and other measures relevant to our goal behavior. Finally, we ask the user to rate whether we resolved the pain quantitatively. If the output of our user testing indicates a high degree of resolution, we can prioritize the design for development. 

Detailed below is use testing conducted in the IBM Garage work with Frito-Lay. 

Click to see results of user testing

Step six: Development

At this stage, developers will be on the lookout for any adverse impacts of the prioritized design. The solution documentation includes the business goal, its intended impact on users and how the solution is meant to influence user behavior. For example, the business goal is to reduce cart abandonment by 25 percent and the solution is intended to generate a 5 percent reduction through simplified order-editing. If the developed solution produces an experience that might negatively impact the intended user behavior, such as slow load times, developers are empowered to engage the product owner and design team. 

Step seven: Monitor impact

Our final step is monitoring for the expected impact on user behavior using our measures of success. By plugging real-world data into our value model and assessing progress towards our goals, we can quickly calculate the incremental value realized so far and estimate the expected value of addressing the remaining root causes. 

Real world benefits of agile value methodology

The distinguishing feature of value orchestration is that user and business value are directly linked. Business value is a function of user behavior and user value is a means of changing that behavior. As we’ve shown through the process above, we can estimate, translate and measure user behaviors, allowing us to calculate and predict business value. 

This approach lends itself directly to agile delivery by incorporating value assessment into the product development lifecycle. Getting started only requires a goal expressed as a change in user behavior. With a root cause analysis of user behavior, product teams can pull new user pain points into the backlog while working towards the same business goal. This enables a feedback loop of experience improvements linked to business benefits, accelerating time to value.  

Click to see summary of process

Source: ibm.com

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Transforming the retail experience with frictionless supply chain

As the retail industry continues to navigate fallout from the pandemic, many organizations have turned to digital transformation to support the challenges of supply, demand and logistics. This has been critical to help navigate the unprecedented volatility and has accelerated the vision of supply chain executives by 5 to 10 years. We can no longer depend on historical data to make supply chain decisions and looking forward we are not certain how consumer behavior will continue to change over the next few years as we adjust to a post-COVID life. Recent IBM Institute for Business Value research shows just how much has changed in the last two years alone. That’s why it’s critical to look to real-time data and insights to uncover patterns so we can anticipate and take action on what’s needed to best serve retailers and their customers.

Challenge and opportunity

For Party City, the global celebrations category leader, the pandemic presented a unique challenge and opportunity. With the scaling back of large social gatherings, consumers switched to decorating their homes and having smaller-scale events to celebrate momentous occasions and brighten their days. The way in which people shopped also changed. The usual in-store foot traffic was temporarily modified. Party City quickly pivoted to offer safer shopping experiences like home delivery, curbside pickup and buy online, pickup in store (BOPIS). To continue driving sales while still meeting customer and employee satisfaction, Party City needed to simplify their ordering and purchasing processes to provide seamless services to its online and in-store customers.

“The pandemic presented many unique business challenges for retailers and just as consumers have needed to adapt to new ways of shopping, it was imperative that we improve inventory turns, increase speed and reliability of order fulfillment by removing supply chain friction to help deliver on Party City’s customer promise.

By revamping our end-to-end omnichannel capabilities with seamless integration of our Salesforce commerce platform and IBM Sterling Order Management systems we’re able to power a highly-scalable order orchestration and inventory visibility solution that is helping us continue to successfully pivot towards our next-generation retail format and deliver a blended digital experience.”  —Mark Miller, Party City CTO

Seeing results

To achieve the desired level of success, Party City maintained their business operations by rapidly deploying and scaling new fulfillment capabilities using IBM Sterling Order Management solution, IBM Sterling Inventory Visibility, to meet shifting shopper demands and expectations in real time. This included adding curbside pickup, same day delivery and ship-from-store as well as evolving their retail locations to operate as decentralized fulfillment centers to quickly, and cost effectively, serve customers as part of their omnichannel strategy and customer experience strategy. Though none of these fulfillment options were available pre-pandemic, by the beginning of phased retail re-openings, these new channels became critical to their integrated fulfillment strategy and helped covert customers at a rate 75% higher than the previous year.

Along with making ship-from-store and curbside pickup available, Party City also created a first for the retail industry with the introduction of self-checkout through the Party City app. This allows customers to shop via the app, complete their order transaction and pick up their items without ever having to transact in-store.

Additionally, to become more agile, responsive, and resilient in their back-office processes, Party City partnered with IBM Consulting to transform its finance and supply chain operations with technologies like AI and automation. The finance transformation roadmap and organizational design, along with the warehouse management strategy, is designed to deliver solutions that improve productivity, reduce overhead cost, and improve service levels to Party City’s suppliers and customers, on resilient and integrated platforms.

Adapting and differentiating with innovative technology

Leading retailers have turned to technology to support a new agile way of working responding to the pandemic-related uncertainty in supply and demand. The resulting intelligent workflows help make retail supply chains predictive, automated, agile and transparent. By modernizing critical supply chain processes with open platforms that take advantage of advanced technologies including AI, blockchain, IoT and hybrid cloud, retailers can quickly deploy new and differentiated fulfillment capabilities that help drive revenue growth and customer acquisition.

As retail clients evolve their digital strategy and shift to integrated, resilient and scalable platforms, it will help them improve productivity, reduce overhead cost and respond to increasing priorities around sustainability. All of this allows leading retailers to provide excellent service to their trading partners and, most importantly, to their customers.

Source: ibm.com

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To help plan for a return to work, businesses should consider leveraging IoT insights at the edge

In the current climate, many businesses have pivoted to a remote workforce, but this option may not be equally accessible across industries. Organizations that operate by serving customers and citizens – like manufacturing, retail, healthcare, and government – are less likely to be able to maintain full operations remotely.

Businesses in these industries are likely to be eager to quickly and, above all else, safely plan for employees to return to the workplace following the guidance from national and local governments. In 2018, An estimated 12.7 million workers were employed in the US manufacturing sector, and, about 1.14M workers in the US warehouse & storage industry, with more employed across retail, healthcare, and government.

How can organizations support a return to the workplace given the COVID-19 crisis?

In addition to following the return to work guidelines issued by CDC and federal, state, and local governments, to help support a return to the workplace, businesses should consider leveraging technology solutions – like edge computing, 5G and IoT –  to gain insights that can help protect employee health and promote workplace safety. Edge computing can be a strong alternative to cloud processing for near real-time data access.

Employee Health

◉ Employers will need to rethink their strategy to help protect their employees’ health and safety while at work.  One option to consider is to leverage technology and systems, such as:

◉ Infra-red (IR) cameras set up at key entry points can screen individuals with higher basal body- temperature in order to quickly detect possible fevers.
Connected wearable devices can monitor employee health factors such as oxygen level, heart rate, blood pressure changes, and respiration rate.

Workplace Environment Safety

Operations-intensive areas such as manufacturing shop floor, warehouses, distribution centers, and commercial office spaces can often be congested, so leveraging technology to glean insights about the status of the work environment can be helpful.

◉ Optical cameras can help identify increases in the crowd density of certain areas, and notify if there is a breach of preset business rules such as the number of people limited to each zone.

◉ Bluetooth beacons can help detect proximity of employees to one another based on social distancing norms in the company premises.

◉ Leveraging the insights from multiple locations can help identify areas of needed focus as well as leverage best practices back across the enterprise.

Edge computing is a strong option

Real-time data access is key in order to quickly identify potential safety concerns in the workplace. In this scenario, edge computing can potentially be a stronger option than cloud processing. If data must be sent to a central cloud, analyzed there and returned to the edge, there can be a lag in data processing, high data cost, and need for always-on internet connection. If businesses utilize edge computing there can be potential advantages –

◉ Businesses can capture and analyze data locally

◉ Eliminates the need for storing a lot of data on cloud, which can potentially result in lower operating costs

◉ Reduces the need for huge real-time event processing on cloud

◉ Sensor data is continuously monitored, not stored, and the system triggers an alarm only if it detects an anomaly

For organizations where remote operations is not an option and are planning to bring workers back under the proper guidance, consider technology when developing your strategy.

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Six recommendations for launching or expanding your virtual agent in this crisis

As we work together to respond to our current crisis, artificial intelligence (AI) is a force multiplier, helping us effectively and efficiently navigate this overwhelming storm.

Artificial intelligence (AI) virtual agents are not new news. Today they are being reimagined to help citizens and workers access trusted data sources and to help get the answers they need. How many infectious cases are in my area? How do I get tested? What should I do if someone in my household is sick? When should I go to the hospital?

Both public sector agencies and private sector organizations are building on these capabilities to rapidly train AI on policy. What is my organization doing to respond to this crisis? What happens if I need to take an unscheduled day off? How much sick leave can I take? Organizational policy is rapidly evolving, each week is a new frontier as we learn, together, how to navigate an unprecedented global pandemic. As organizations amend their business policy, the AI can be quickly updated to reflect these new changes, becoming the single true source of data for an organization and its entire workforce.

AI virtual agents are simple yet powerful solutions. In early deployments around the world, we are seeing a significant decline in the volume inbound inquires to call centers, which means shorter waiting times for those critical cases. When workers get answers from AI, this means more time connecting with managers and colleagues on mission-critical initiatives. By analyzing the AI interactions, leaders have deeper insight into their workforce and use the data to help prioritize their crisis response strategy.

Whether you are launching a new virtual agent or expanding the capabilities an existing one, here are six recommendations:

1. Keep your employee personas at the heart of your design. Understand the needs of your employees and prioritize those when building AI capabilities.

2. Balance security requirements with access and leverage the cloud. Take a hard look at the need to access confidential information and balance that with the need for the AI to be available anytime, anywhere, on any device.

3. Start small and iterate quickly. Consider a prototype with limited functionality, deployed to a smaller group of users. Scale quickly to a broader set of users and expand the AI’s capabilities through frequent updates.

4. Consider integrating publicly available data from trusted sources. Public health organizations, government agencies, and educational institutions are making large amounts of information available. Train your AI to use these data sources or provide links to additional sources of information.

5. Make one of your senior leaders the solution owner. Your chatbot team needs near-real-time insight into the changing organizational policies, in order to adapt quickly. Select someone who is a focal part of the leadership team as solution owner, helping minimize the real-time between policy decisions and training the virtual agent.

6. Use the AI data. Take your cues from your workforce. The questions asked are the topics of most interest or concern. Adjust your crisis response strategy accordingly.

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