Delivering on the promise of exceptional client experiences

Ecosystem partnerships are a cornerstone of IBM’s growth strategy. More importantly, partnerships are an essential means of delivering IBM’s incremental value to customers on their Hybrid Cloud and application modernization journeys. 

In December of 2021, IBM and MuleSoft shared a vision of expanded partnership by bringing together Red Hat OpenShift, the industry’s leading enterprise Kubernetes platform, and MuleSoft, the world’s leading Integration and API management platform. We are making good on that promise, and more. 

Today, MuleSoft’s Anypoint Runtime Fabric (RTF) is now fully certified to run on Red Hat OpenShift. For organizations choosing Red Hat OpenShift for containerized platform orchestration, they can now run MuleSoft RTF on AWS, Azure, Google Cloud Platform (GCP), or IBM Cloud alongside on premises or bare metal deployments. 

For clients wishing to run MuleSoft on-premises, they can do so seamlessly with IBM Spectrum® Fusion HCI, a hyper-converged infrastructure platform built from the ground up to deliver an industry-leading set of highly scalable, robust, and enterprise-hardened OpenShift data services. 

“MuleSoft advances IBM Consulting clients’ application modernization, middleware integration and digital transformation across the hybrid cloud estate on-premise or any cloud platform,” said Shai Joshi, Managing Partner and Growth Platform Leader, IBM Global Hybrid Cloud Services. “You can’t achieve digital transformation without reliable access to data and transactional capabilities of back-end systems in a unified manner to deliver on that promise.” 

IBM Consulting has developed several hybrid cloud journeys to dramatically accelerate the migration of existing MuleSoft clients to Anypoint RTF on Red Hat OpenShift.  

“Our customers want real-time information to enable digital experiences,” said Dan McAllister, SVP Global Alliances & Channels at MuleSoft. “MuleSoft’s certification of Red Hat OpenShift provides our customers more choices than ever before to deploy RunTime Fabric faster and with less management overhead.” 

Adding the general availability of MuleSoft on OpenShift makes our partnership even stronger.  

This brings together the best of IBM’s Hybrid Cloud Strategy with our Strategic Partner, Salesforce.

Source: ibm.com

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Subscription centricity: 5 tips for designing diverse, recurring revenue models

In today’s subscription economy, businesses must take steps to stay ahead of the curve. Whether you’ve made an initial investment or have yet to get started, modern organizations must accelerate their subscription-based sales to remain competitive. This shift from more traditional pay-per-product models to those that prioritize recurring payments for goods and services has the potential to unlock value for your organization, including steadier, more predictable and more consistent revenue. But achieving these benefits is not as easy as simply tacking on a subscription model; it requires thoughtful planning and execution that focuses on your customers’ experience.

When adopted correctly, subscription-based models help organizations gain new customers and new revenue streams, while creating sticky, loyal customers. Your organization can seamlessly turn one-time shoppers into lifelong customers, which results in more predictable financials. And once your company has a model effectively in place, you’ll then be able to accelerate growth by introducing new features and services to existing customers. Regardless of your industry, shifting to subscription sales will help you remain agile and competitive in today’s economic landscape.

What are subscription-based sales, and how do they work?

The subscription market is best summarized as the shift from a traditional pay-per-product model to one where customers pay on a recurring basis for your products or services. While everyone is familiar with some popular B2C examples of these subscriptions, such as Netflix or Spotify, new ways of using these models are becoming more common in non-tech industries and the B2B space, as well. In fact, the global subscription billing services market is expected to more than double in size from USD 5.1 billion in 2020 to USD 12.5 billion in 2026.

For example, industrial companies might use subscription models that include “power by the hour” and product-as-service, one-time products and connected services bundles. B2B distributors are exploring how to create and sell subscriptions through resellers, including SaaS or customer service.

In the automotive industry, it’s one thing to sell a car through a dealer and then watch a customer drive it off the lot; they’ll unlock more value if they sell subscriptions for features that place the manufacturer in an ongoing, direct relationship with the driver, such as GPS or satellite radio services. These types of subscriptions that are available after leaving the assembly line more than offset the initial cost of having mechanics add those features during creation.For financial services companies, customers can pay for access to advisors on recurring subscriptions. Not only does this expand your service portfolio reach, but it also provides new and existing customers with flexibility at a more budget-friendly cost. These are simple examples from different industries that illustrate how far-reaching subscription models are becoming.

Regardless of what industry you’re in, there are different types of subscriptions that you can offer to customers:

◉ Replenishment subscriptions involve replacing the same products for your customers with automated renewal, such as providing a monthly cadence to restock parts for a manufacturer or groceries for a consumer.

◉ Access subscriptions enable your organization to offer special access to members-only items. You can offer long-term service contracts to products, maintenance and cloud services.

◉ Curation subscriptions provide highly personalized products, services or experiences based on customer preferences. Subscription data on consumer preferences is gathered with every dollar purchased.

No matter what type of subscription-based sales your company decides to implement, the key to growth is customer retention. Creating strong customer experiences across the entire customer lifecycle will ensure you drive adoption and renewals to generate revenue and accelerate the effectiveness of your subscription model.

How to get started with a subscription-based sales model

Your organization is used to transaction-based sales, but you may feel pressure to diversify your revenue streams. Embracing subscription models is one of the best ways to do that while keeping up with industry trends but transitioning your existing products into a subscription-based offering requires a thoughtful commitment.

Subscriptions require different platforms and technology enhancements, data integration and the internal talent to foster interactions that turn one-time buyers into recurring customers. Depending on your current prioritization of subscriptions, your business will fall on different parts of the so-called maturity curve. But whether you’re in the discovery phase or looking to enhance an existing model, it’s important to remember that creating positive customer experiences is what leads to renewals. These models are less about selling products and more about fostering long-term relationships that continuously evolve to address customers’ needs. If you are too hasty with launching a subscription offering, your business will miss the point and waste time, resources and money.

Acknowledging that your organization must prioritize the customer experience is the first step toward successfully implementing a subscription-based sales model. After that, you need to make decisions that are best suited to your organization’s maturity level and goals. Here are some tips to ensure that implementing subscriptions is a success:

1. Give customers flexibility: Allow your users to buy and pay for their subscriptions over any channel and provide multiple pricing tiers. That flexibility will allow you to retain more subscribers.

2. Focus on customer value: Cost, convenience and value are the historical drivers of shopping behavior. The best way to attract customers is to find the right combination of pricing and offerings.

3. Don’t simply add on: Don’t get caught up by just adding subscriptions onto existing products. Make sure your subscription business is based on an unmet customer need.

4. Evolve your experience: We’ve said that the customer experience is the most important part of keeping customers subscribed. Keep customers engaged with originality, consistent quality and a variety of offering options.

5. Establish new metrics: A new sales model means you need to have new ways to track your recurring revenue. Make sure you have the tools in place to accelerate your growth.

Build an agile model from the start

Once you’ve decided to embrace a subscription-based sales model, you’ll need a platform that can support your organizational goals but is also agile enough to iterate, evolve and improve. While experimenting with subscriptions might feel safer, you need to demonstrate to your customers that this model is here to stay with a more committed approach. Succeeding with subscriptions is not as simple as just flipping a switch; it must be a complete change in your company’s mindset regarding how you do business.

Salesforce allows you to consolidate your data, insights and analytics with Genie, giving you access to everything you need to intelligently progress your subscriptions. Customer 360 ensures that you don’t have disparate systems and seamlessly integrates with your existing Salesforce solutions. This also helps you enhance customer service, because issues with billing or subscription management can be remedied with your single customer view on Service Cloud, reducing friction in the customer lifecycle. You’ll be able to automate processes for selling and collecting payments, create catalogs to manage pricing and subscriptions and power your entire subscription lifecycle regardless of the selling channel — all on one platform.

Even with an agile platform like Salesforce, you still need to remain dedicated to continuously improving and iterating on your subscription mindset. With the right people, processes and technology, your company will be able to get started with a subscription-based sales model and accelerate predictable, consistent and upgradable revenue growth moving forward.

Source: ibm.com

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Healthcare’s Y2K: How to prepare for the FDA’s big update

Who would have thought we would see yet another major shift in the healthcare and life sciences industry? But a change is coming via the FDA’s proposal to revise the National Drug Codes (NDCs), replacing an existing 10-digit format (XXXX-XXXX-XX) with the new 12-digit format (XXXXXX-XXXX-XX). This blog will discuss the implications and compliments the lengthier response IBM’s Enterprise Strategy and Life Sciences team at IBM Consulting provided to the US Federal Drug Administration (FDA).

Expanding the number range addresses the rapidly deprecating number range paving the way for decades as billions of new codes will be available. But this is not without significant challenges for anyone utilizing this data. Healthcare executives experienced a similar change before: Remember the move to the International Classification of Diseases (ICD) 10?

NDCs are used across the healthcare system by pharmaceutical manufacturers, distributors, pharmacies, insurers, healthcare providers and more. They are the critical data component of routine transactions like manufacturing, shipping, dispensing and prescribing. For the most part, this data is housed in outdated systems incapable of supporting an immediate shift from a 10-digit to a 12-digit format. Why is this the case? Because for years, the industry resorted to hardcoding (manually embedding data in the source code) the NDCs into the computing systems.

What does this mean for the industry? Think Y2K but for healthcare: racing the clock to update systems and datasets with major uncertainty as to whether these updates are enough to keep the processes functioning as they do today. For this reason, industry executives need to make a game plan now to mitigate the costs and risks associated with the FDA mandate. Below is what we discussed with the FDA and our industry partners.

Act today to save time tomorrow

The revision will go into effect five years after the publication date and initially require all existing codes to adopt the new format. For most companies, this will create months of manual labor, adjusting hard-coded data across many systems. We heard from our industry partners that they don’t have a complete view of which systems, business processes and transactions involve NDCs. Such an undertaking may be disruptive, time-consuming, costly and error-prone, introducing an abundance of liability.

One-time costs will include substantial updates to software systems as well as employee training to adopt these new systems. Organizations will also need to revise all product visual design and packaging to accommodate the new barcode system. In addition to the cost of implementation, the changes will also disrupt the ongoing activities of the impacted departments. To address this, it will be worth considering how this change could qualify for investment funding being used for other supply chain resilience initiatives already underway.

Additional considerations include an exhaustive planning and implementation cycle that will disrupt major milestones like new products and manufacturing centers, which will rely heavily on NDC data functionality. Couple this with the ongoing push towards Drug Supply Chain Safety Act (DSCSA) compliance, and the entire industry is in for several years of complication and disruption. Furthermore, each organization will have its own transformation timeline, introducing challenges of format interoperability throughout the transition window. For these reasons, it is imperative that companies act today to accommodate the various challenges this update promises to deliver.

Invest in diligence and a modernization plan to help speed time-to-compliance

Regulatory affairs and operations teams can take easy steps to pull together a plan to get to compliance within the 5-year timeframe (or hopefully sooner). Business leaders can expect changes to packaging, labeling, IT systems, transaction systems, scanning hardware and more. With multiple data updates pending, now is the time to implement systems capable of minimizing these challenges. Below are a few steps we believe our industry partners should take:

◉ Determine the scope of impact including systems, business processes, transactions, labeling and packaging, and external supply, as well as any training and quality compliance standards required.

◉ Understand the underlying technologies, tech architecture and opportunities to modernize as you upgrade to get to compliance.

◉ Leverage business area stakeholders to develop a transition plan that identifies interdependencies and initiatives required to reach full compliance.

◉ Develop a financial plan and implementation timeline based on available resources and future projects expected to be impacted by NDC revisions, like new product launches and manufacturing site openings.

◉ Develop a remediation program plan for stakeholders that addresses changes, key milestones, risk mitigation initiatives, expected costs and communication plans for industry partners.

◉ Realize the transition will be staged as some trading partners will adopt the change sooner than others and, even within a single organization, new products will likely launch with the new number range while older products continue utilizing the legacy numbering.

This transition may sound daunting, but with the right strategy and an open mind about using this as an opportunity to modernize technology systems, companies may yield a lot of long-term value.

Source: ibm.com

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How can we learn from Mother Nature?

Nothing in nature operates individually. Nature works in a connected, circular ecosystem where everything is leveraged, shared and repurposed. Did you know that a grain of sand from the Saharan desert affects the fertility of the Amazon Forest? Or that seaweed in the ocean can produce around 70% of the oxygen in the atmosphere?

In nature, everything is perfectly orchestrated in harmony. Why can’t our future economy be the same? Specifically, how can we enhance our banking and payments ecosystem to make it thrive?

As we contemplate nature’s ecosystem, we realize that a good foundation is vital for survival. Just as a sterile flower won’t attract a bee, we cannot operate in an ecosystem if the foundation has defects. The base element must be functional and productive before enhancing the following operation chain.

As the base element of our economy, our existing banking and payment applications must undergo an in-depth review to see if they must be recreated before they can be part of the future economy fabric. This transformation would include the entire framework of people skills, operational processes and technology infrastructure, in addition to the core functions of the product.

Target three key areas to mimic nature

First, we must align and reinforce our banking and payment platforms on a global level. The base element must be fully functional and productive.

Some examples to enhance the functionalities and achieve higher productivity:

◉ Provide timely visibility into all global transactions.

◉ Eliminate time-consuming manual payment generation.

◉ Protect against fraud.

◉ Keep pace with industry changes (formats and technologies, particularly in the payment process).

◉ Start to adopt digital banking and provide a seamless wireless experience for both employees and customers.

◉ Embed advanced security, like Security Service Edge (SSE) and Zero Trust.

Second, we must optimize the load to share and leverage our base elements. This is how we create a common infrastructure for our resources to work together.

Some examples to achieve such optimization:

◉ Adopt a flexible cloud strategy.

◉ Optimize infrastructure load across the cloud. This helps to distribute server workloads more efficiently, speeding up application performance and reducing latency.

◉ Share cloud standard services, like security framework, certificate management, identity management, licensing services, metering and monitoring services.

Third, we must interconnect and open our systems, which is how we bring life to the entire ecosystem and make it function as one body.

Some examples to achieve such interaction:

◉ Leverage cloud interconnectivity and adopt a hybrid cloud strategy.

◉ Adopt an API and microservices strategy.

Share multiple resources for a richer ecosystem

As a banking and payment industry leader, IBM can help ignite banking and payments businesses in every country to enhance performance. Aside from technological shifts, IBM identifies the core business needs and what’s expected from those systems, applying the latest industry standards both from a business and technologies standpoint and reimagining and rearchitecting those systems to withstand the viral shifts in business requirements and technology.

Our banking, payments, business process workflows, development, infrastructure, architecture and security experts can reimagine and design systems to address future ecosystem challenges. Leveraging more than 100 years of experience, we are paving the way for the world’s future business and technology demands. This new era will change the face of this industry in terms of speed, agility, interoperability and performance.

Nature cannot depend on a single resource; nor can our financial systems. For example, enterprises face pressure and challenges to move beyond a single cloud provider. The hybrid cloud tackles those challenges by connecting and sharing multiple resources to produce an effective ecosystem with improved performance. The hybrid cloud can connect systems around the world with speed and efficiency, allowing the use of widely spread infrastructure to accelerate offerings worldwide.

That’s what the IBM Payments Center™ (IPC) is doing with the IBM Service Bureau for SWIFT as we leverage IBM financial cloud offerings with on-prem and other public cloud offerings. We set the stage to deliver a SWIFT solution that fits any client’s need in terms of cost, speed, regulations and cloud performance, without the need to tie to one provider or a single technology. Our vision for our clients allows them to consume SWIFT as a service regardless of where the platform runs.

In addition, a hybrid cloud brings many additional benefits, including the following:

◉ Modernizing at a pace that makes sense for the business

◉ Maintaining regulatory compliance as many industries require systems (or data) to sit in a specific location (such as SWIFT data)

◉ Running applications at a remote edge location, as some industries require edge hybrid computing for low latency and better user experience.

COVID has forced the acceleration of digital transformation in banking and payments. We offer contactless experiences for clients and automate more processes. Very few applications today can accomplish goals on their own without connecting to other systems within the technology stack to share data. For this reason, developers must build “open” systems with connectivity to other systems in mind. APIs can bring that fabric to life; open APIs can accelerate growth and allow the application to communicate at its core. APIs enable integration with emerging technologies at scale, exchanging information, leveraging existing systems to produce a scalable business model and allowing integration of new financial technologies.

As a leader in emerging technologies and payment solutions, IPC has adopted a strategy to mimic a natural flow. As we reinforce the fabric of payments worldwide, design future-proof solutions, adopt in-depth hybrid cloud offerings and open API to interconnect our solutions around the globe, we are creating a living financial system.

Source: ibm.com

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Overcoming the architecture challenges of a hybrid cloud world

More than likely, your organization already employs some version of a hybrid cloud approach to its IT architecture. In fact, you are likely operating between six and eight clouds, like most organizations.

It’s also likely that your organization’s mix of cloud environments has some level of on-premises infrastructure integration that spans across it and includes edge computing and/or distributed cloud. When managed correctly, this hybrid cloud infrastructure can do more than optimize your business — it can transform it. The recent IBM Institute of Business Value report, Mastering Hybrid Cloud, points out five key challenges to achieving hybrid cloud mastery. The first of these challenges is architecture.

According to the report, 97% of organizations claim to use more than one cloud. Not to mention, the average organization is anticipated to have 10 clouds by 2023. That’s a serious amount of potential chaos to manage. So how do you bring order to the chaos of a crowded cloud estate and move one step closer to hybrid cloud mastery?

Step 1: Build a single, integrated hybrid cloud platform

A single, integrated hybrid cloud platform and application architecture is the foundation on which to mount and connect all the parts. Instead of disconnected components that accomplish little on their own, it’s important to establish a united system that can save cost and create ease.

A hybrid cloud platform streamlines service provisioning and consumption through a convenient and cost-effective “build applications once, deploy them anywhere” superpower. Developers build microservices once and can then reuse them in applications that run anywhere in the cloud estate. It defines landing zones that empower platform users with a reduced level of technical and administrative burden. These zones include where your data is stored and used — and even where and how it’s secured.

Step 2: Align your hybrid cloud platform with your customer-facing product

That integrated hybrid cloud platform begs for its complement: a business-aligned application architecture. This framework guides decisions about how applications work in a hybrid cloud environment. By removing the guesswork, you can achieve greater levels of agility and innovation.

Keep in mind that the hybrid cloud platform you’re building is a platform for service delivery. You’re delivering those cloud platform services to customers who define what “value” looks like. Defining customer-centric design thinking principles at the outset of platform development can pay big dividends when you begin to launch platform services.

Step 3: Find the ideal balance

The ideal balance is where your organization’s hybrid cloud platform IT roadmap drives cloud performance improvements. That may sound obvious, but achieving it is far from commonplace across organizations today, especially in regulated environments where compliance and regulatory reporting concerns often require an on-premises storage option for the highest security.

Aim to balance resources effectively and achieve your growth goals without sacrificing operational requirements or creating undue risk. Achieving balance isn’t easy, but with optimized architecture automation, streamlined DevSecOps and risk reduction across the hybrid multicloud spectrum, it can be achieved.

Why tackle the architectural challenge?

No matter what your business and IT transformation goals are, an integrated, open hybrid cloud platform can help you:

1. Foster greater innovation and reduce time to market.

2. Protect your data and manage regulatory changes.

3. Boost developer productivity and develop new product solutions more quickly.

4. Manage complexity in your infrastructure while streamlining your operations.

5. Adopt new technology while shifting your CapEx to OpEx.

Done right, a hybrid cloud platform is a unifying strategy that orchestrates your data and workloads, management and application portability across environments. It’s empowering for your business and can move you closer to getting the most business value out of your hybrid cloud investments. So, are you ready to tackle the challenge?

Source: ibm.com

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Bridge the data literacy skills gap with data storytelling

Being a data-driven organization goes well beyond building a modern data architecture. With vast amounts of data flowing through the enterprise, the challenge lies in making sense of all of that complex information so that everyone, not just the data scientists or machine learning engineers, can interpret it for better decision-making.

For CDOs and other leaders within different lines of business, this means fostering a culture that prioritizes data literacy: the ability to read, understand, create and communicate data. Too often, data is presented in mysterious figures that are difficult for key stakeholders to understand. In fact, poor data literacy is the second-biggest internal roadblock to the success of the CDO’s office, according to the 2021 Gartner Annual Chief Data Officer survey.

To get data literacy right, organizations have to make data more approachable for non-technical experts. This means moving away from confusing charts, dashboards, graphs and complicated visuals. Instead, organizations need to humanize data and AI by creating visually compelling stories that resonate with people and transform data into actionable knowledge that drives business results.

Bridging the data literacy gap with a culture of data storytelling

Enter data storytelling, the ability to convey data not just with numbers but with engaging narratives and visuals. Creating a narrative context is important, because it brings data to life and ensures that the message it’s delivering is meaningful and relevant. Adding data visualization elements enhances the story and makes large amounts of data more digestible. When done right, data storytelling can be a powerful tool to communicate and demystify the data science.

While organizations most often relay on a combination of UX/UI designers and BI specials, when non-technical business stakeholders start developing data storytelling skills it can spark a chain reaction across teams, LOBs and the organization as a whole. In that moment, one person with data storytelling skills will lead a group of individuals to make a better, data-driven decision, But those data savvy individuals also can impart their know-how to other coworkers and inspire their teammates to hone their data storytelling skills and shape their own daily workflows.

This helps to cultivate a collaborative data-driven culture from within that gives business teams access to the strengths and skills of everyone to solve problems better and innovate faster.

The power of established data-literacy initiatives and data storytelling programs

Too often, business stakeholders blindly follow data created by algorithms. To make sure this doesn’t happen, organizations need experts who can challenge those algorithms by asking critical questions of the data and interpreting it correctly. Understanding and telling stories with data is a pivotal part of ensuring employees are still critically thinking about data, questioning it and interpreting it correctly, because it includes more people in the conversation.

The resulting unified data-driven culture brings together data visualization specialists, data scientists and software developers, executive management and other stakeholders with the goal of everyone speaking a common language made of data.

To create this culture of data literacy, organizations can start by developing a business strategy at the executive stakeholder level. Once the business strategy is clear, data leaders like the CDO can craft a data strategy that helps achieve those business goals that includes data literacy initiatives to ensure adoption and success.

Launching data-literacy initiatives and data storytelling programs will help everyone, from the C-suite to all other key stakeholders, gain the skills needed to discover data insights, trends and patterns relevant to solving business problems. Training also empowers teams to use data as a competitive differentiator.

Source: ibm.com

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Supply chains can make sustainability an operational strength

Sustainability is one of the many challenges facing chief supply chain officers (CSCOs), alongside day-to-day supply chain disruptions and pervasive technology growing pains. However, when companies address sustainability within both supply chain and procurement processes, it can serve as a source of innovation, business growth and savings. According to IBM Institute for Business Value research, 62% of sustainability trailblazer companies outperform their competition in profitability.

As explored in our recent thought leadership paper, Building intelligent, resilient and sustainable supply chains, supply chains hold the potential for sustainable, circular and measurable change. CSCOs have both the opportunity and responsibility to prioritize strategic sustainability initiatives that rethink business models and sourcing networks. They can optimize for net zero, green operations and asset management. They must also consider the impact that their upstream and downstream value chain may have on human rights. Most importantly, for CSCOs to successfully drive responsible and equitable outcomes, sustainability must be operationalized, embedded in the corporate strategy and integrated across business and technology goals.

Misconceptions and reality around sustainability initiatives

How big is the corporate commitment to sustainability? In the US alone, Fortune 500 companies are willing to invest USD 22 billion per year in sustainability initiatives. But many are still struggling to make progress on their enterprise sustainability goals because of these commonly held misconceptions by some decision makers who feel sustainability initiatives:

◉ Are expensive and the ROI is difficult to quantify

◉ Require technology and business processes to be replaced

◉ Override existing business imperatives

◉ Are easily preempted by changing economic and geopolitical factors

All these misconceptions cause hesitancy, but can be alleviated when we consider:

◉ The real and demonstrated ability to build a business case around sustainable investments.

◉ Business decisions at every level—by stakeholders, customers, employees, shareholders and beyond—are increasingly informed and made with sustainability as a key factor.

◉ Sustainability initiatives across the enterprise—and most importantly within the supply chain—do not need to replace all that exists today. Leveraging, optimizing and upcycling what exists today must be a key design principle.

The supply chain is where net zero roadmaps and corporate social responsibility (CSR) goals can be operationalized and change with material impact for the respective industry can truly happen. Historically, supply chains have focused on low-cost delivery, with little attention to environmental and social impacts. Today’s technologies allow us to do better. There is now a quantifiable business case and clear ROI for investing in sustainable supply chains across all industries. Smarter supply chains can improve visibility, reduce waste and enable new ways of working, all of which are necessary for transformative and innovative sustainability initiatives that improve environmental, social and governance (ESG) impact. Better supply chains simultaneously address business priorities, consumer demands, employee engagement and regulatory and compliance requirements.

But how do you ensure these next-generation supply chains can support sustainable operations? Establishing a solid data foundation is a critical first step and there are several other things you need to get right:

1. Leverage data, reporting and technology to provide visibility.

There’s a revolution in supply chain visibility underway. The combination of integrated data and smart technology enables real-time understanding of how your supply chain impacts the environment as well as real-time identification of human and land rights risks. Data and AI can enable supply chain professionals to make informed decisions and optimized decision orchestration can incorporate ESG impact as a key lever. This visibility is the crucial foundation in building transparency, and then trust, across your supply chain.

2. Align culture and organization to help prioritize initiatives around the quadruple bottom line: people, planet, profit and purpose.

Fifty-three percent of CSCOs say their digital supply chain transformation initiatives will be the most significant area of competitive advantage during the next three years. But these initiatives only deliver value if culture and organizational processes are aligned with the high-level strategy. The 13% of companies identified as “Transformation Trailblazers”—those that get that alignment right—achieve 20% higher revenue growth than their peers.

3. Look for incremental gains, too.

Sustainability initiatives should also be sustainably designed, leveraging what you have today across your people, processes and technology. Transformation does not mean rip-and-replace, it can be implemented via concurrent efforts that capture incremental, immediate improvement while building toward longer-term radical impact.

Ultimately, successful sustainability initiatives should treat sustainability as the ultimate ecosystem of interconnectedness between people, processes and technology. Therefore, sustainability solutions cannot be an afterthought nor the responsibility of a siloed team. They must be a shared responsibility across the enterprise with specific accountability for ESG performance measurements.

Source: ibm.com

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Approaches to long-term planning with IBM Planning Analytics

“If you fail to plan, you are planning to fail.” – Ben Franklin

In our collective rush to react to ever-changing marketplace dynamics and shifts in the economy, it’s easy to focus on short-term plans, to the neglect of long-term planning. Today’s leaders need to have several plans – short-term, medium-term, and long-term.

Different plans for different needs

How do these plans differ? A short-term plan is designed to show granular details for a limited time frame. This is often updated monthly, although we have some clients updating their plans on a weekly basis. One of our clients follows a process where local managers update their plans on Mondays and Tuesdays, have the regional managers review the data on Thursdays, and allow senior management to analyze and assess the data on Fridays. Each Monday they start the process over.

Most organizations utilize a medium-term plan that looks out anywhere from a few quarters to a full year. Most people will think of this as a standard monthly forecast with data at a bit more of a higher level, but still somewhat details.

A long-term plan often goes out multiple years. Many companies create a 5-year plan, although some industries such as entertainment and pharmaceutical often create 20-25 year plans. A long-term plan is a high-level view of the business. It’s not nearly as granular as short, or even medium-term plans. The plan does not get down to the level of looking at a GL account or a customer. It’s a measuring tool and a defined way of reviewing the progress of the company. In short, long-term planning helps to set the company’s direction.

The essentials of long-term planning

The long-term plan gives you guidance on how to answer several questions, including:

◉ How can we expand the company?

◉ How can we look into acquisitions?

◉ What products, geographies, and verticals can we or should we add?

◉ What products no longer make sense?

◉ How do debt payments impact cash flow?

◉ What type of labor, buildings, locations, and equipment do we need?

A long-term plan can be considered a proactive approach to risk mitigation, enabling companies to plan, think ahead, prepare for, and lessen the impact of potential negative effects. At Revelwood, we recommend two approaches to long-term planning: the growth percent approach and a driver-based approach.

We often see both of these methods used when performing long-term planning in IBM Planning Analytics with Watson:

Growth percent approach

The growth percent approach allows you to adjust groups of data (accounts, departments, etc.) by increasing or decreasing the values from the previous year. Some clients prefer to simply use a single percentage (example: reduce all expenses by 2% each year for the next five years) whereas some clients prefer to include more variation (example: reduce utilities expenses by 2% next year, by 3% the following year, and by 4% for the next three years). But no matter what level of detail is used, Planning Analytics’ powerful scripting tool will perform the entire long term plan in a matter of seconds.

Driver-based approach

A driver-based approach uses operational activity to calculate key variable revenues and expenses. This approach allows you to simplify the input by defining a set of drivers and creating calculations that use the drivers.  For example, a single driver of “units sold” can be used to immediately calculate revenue, COGS, and some of your variable expenses using the tool’s efficient calculation engine.

Mitigate risk with long-term planning

Long-term planning is your company’s assurance against planning to fail. There’s a reason why Franklin’s quote has lasted through the years. And it should be the motto of every planning team.

Source: ibm.com

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Creating a holistic 360-degree “citizen” view with data and AI

Achieving health equity is perhaps the greatest challenge facing US public health officials today. In a 2021 report released by the Commonwealth Fund, the nation ranked last among high-income countries in access to healthcare and equity, despite spending a far greater share of its GDP on healthcare.

Healthcare disparities are closely linked to race, ethnicity, gender and other demographic and socioeconomic issues surrounding access, cost and quality of care. Health inequities in the US came into sharp relief during the COVID-19 pandemic: Analyses of federal, state and local healthcare data show that people of color experienced a disproportionate burden of cases and deaths.

But there is promising news. The recent crisis not only highlighted the critical need to focus more on health equity but also revealed how tapping into data-driven technologies can better ensure equity for marginalized groups.

In 2020, IBM collaborated with the Rhode Island Department of Health, uncovering existing and emerging data patterns to aid the agency’s overall response to the health crisis. This work resulted in real-time, data-driven decisions that identified pandemic-fueled disparities such as lack of access to vaccines. Ultimately, the project led to more equitable emergency response services in the Rhode Island regions that needed it most.

Today state health departments around the country are taking the data-leveraging lessons learned during the pandemic and applying them to an array of public health crises affecting underserved groups. Health departments are focusing on issues such as food insecurity, unwanted pregnancies, increased suicide rates and opioid addiction. Thanks to innovations in data analytics and AI, leaders can make smarter, faster and more efficient decisions to improve public health outcomes and advance health equity.

Creating a citizen 360 view

The journey begins with building a data fabric architecture to ensure quality data can be accessed by the right people at the right time, no matter where it resides. The key is making sure all this data is transparent and responsibly governed for privacy and security.

A data fabric facilitates the end-to-end integration of various data pipelines and cloud environments by using intelligent and automated systems. It also provides a strong foundation for 360-degree views of customers, or in this case citizens rather than customers.

In B2B or B2C circles, a 360-degree view of customers or citizens offers a holistic, comprehensive picture of a person based on data collected from all touch points. This drives business value by creating more effective outcomes as well as more personalized customer experiences. For instance, this data infrastructure enables a state health workforce to better understand the overall healthcare landscape and subsequently improve individual care and address inequities.

Achieving data literacy with storytelling and visualization

Collecting massive amounts of data presents a common issue for both private and public enterprises: how to make sense of all that data.

Part of data storytelling involves data visualization, the process of analyzing large amounts of data and communicating the results in a visual context. But strong storytelling must go beyond presenting data in the form of charts, graphs and tables.

For instance, state health departments comprising many stakeholders and players need to create a compelling storyline and consistent messaging around their data, so they can communicate it effectively to their entire workforce.

Keeping the citizen front and center

Data and trustworthy AI also provide predictive analytics for insights that can solve some of the most pressing health issues, including hunger and food insecurity.

For example, the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), a federal food assistance program that operates through state health departments and local agencies, has seen decreasing enrollment over the past decade despite a sharp rebound in poverty levels. Suspected factors include slow modernization — until recently, all WIC benefits were still delivered as paper vouchers — and persistent stigma against federal assistance. Providing assistance depends on identifying and addressing these and other factors.

The WIC Enrollment Collaboration Act of 2020 calls for state health departments to count unenrolled WIC-eligible families. A data fabric with a 360-degreee view can help that count. It can also help states build and deploy referral mechanisms and conduct a comprehensive outreach campaign (also detailed in the Act). Working together, states can use data to assess and improve access to WIC and better limit food hardship.

Throughout the US, state departments of health, education and behavioral health are using data to overcome other health crises, including the opioid and suicide epidemics. A centralized data hub provides a powerful public health crisis response system that allows for collaboration across government branches and state lines. Such multi-pronged efforts are closing the gap in critical information, shedding light on how and why disparities occur and paving the way to better health equity for all.

Today IBM is working with state health departments to accelerate their digital transformations in the areas of overall governance, operations, automation, data insights and more.

Source: ibm.com

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IBM named a leader in the 2022 Gartner® Magic Quadrant™ for Data Quality Solutions

Data is the new oil and organizations of all stripes are tapping this resource to fuel growth. However, data quality and consistency are one of the top barriers faced by organizations in their quest to become more data-driven. So, it is imperative to have a clear data quality strategy that relies on proactive data quality management as data moves from producers to consumers.

Unlock quality data with IBM

We are excited to share that Gartner recently named IBM a Leader in the 2022 Gartner® Magic Quadrant™ for Data Quality Solutions.

Access the full report here.

We believe, this is a testament to IBM’s vision to empower data professionals with trusted information through data quality capabilities including data cleansing, data lineage, data observability, and master data management.

IBM recently expanded its data quality capabilities with the acquisition of Databand.ai and its leading data observability offerings. This complements IBM’s partnership with MANTA to integrate automated data lineage capabilities from MANTA with IBM Watson Knowledge Catalog on Cloud Pak for Data.

Why does data quality matter across the data lifecycle?

Data quality issues can have far-reaching consequences across the lifecycle of data:

1. Analytics and AI

When a sophisticated AI/ML model confronts bad-quality data, it is the latter that usually wins. As organizations increasingly rely on AI/ML for critical business decisions, the role of a trusted data foundation that delivers high-quality data is paramount. So, it is important to provide data consumers with a curated set of high-quality data and allow them to search for relevant data through a well-defined data catalog.

2. Data Engineering

A research survey points out that data engineers spend two days per week firefighting bad data. This could be because a lot of the current data quality approaches are reactive, triggered only when data consumers complain about data quality. Once poor-quality data moves from data sources into downstream processes, it gets challenging to remediate quality issues. A smarter approach would be to plug data quality issues upstream through active monitoring and automated data cleansing at the source. Data observability capability makes data quality checks upstream possible.

3. Data Governance

Ensuring data quality is critical for data governance initiatives. Increasingly enterprise data is spread across multiple environments which contributes to inconsistent data silos that complicate data governance initiatives and create data integrity issues that could impact Business Intelligence and analytics applications. It is critical to promote a common business language across the enterprise to break down these silos. One effective way to identify bad-quality data before it flows into downstream processes is with the use of active metadata to foster greater understanding and trust in data and ensure that only high-quality data makes its way to data consumers. Equally important is the ability to understand data lineage by tracking the flow of data back to its source which can prove handy when remediating data quality issues.

IBM’s holistic approach to Data Quality

With a strong end-to-end data management experience combined with innovation in metadata and AI-driven automation, IBM differentiates itself by offering integrated quality and governance capabilities.

IBM Watson Knowledge Catalog, QualityStage, and Match360 services on Cloud Pak for Data offer a composable data quality solution with an easy way to start small and expand your data quality program across the full enterprise data ecosystem.  Watson Knowledge Catalog serves as an automated, metadata-driven foundation that assigns data quality scores to assets and improves curation through automated data quality rules. The solution offers out-of-the-box automation rules to simplify the addressing of data quality issues.

With the recent acquisition of Databand.ai,  a leading provider of data observability solutions, IBM can elevate traditional DataOps by using historical trends to compute statistics about data workloads and data pipelines directly at the source, determining if they are working, and pinpointing where any problems may exist. IBM’s partnership with Manta for automated data lineage capabilities further strengthens its ability to help clients find, track and prevent issues closer to the source and for a more streamlined operational approach to managing data.

IBM offers a wide range of capabilities necessary for end-to-end data quality management including data profiling (both at rest and in-flight), data cleansing, data monitoring, data matching (discovering duplicated records or linking master records), and data enrichment to ensure data consumers have access to high-quality data.

Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.GARTNER and Magic Quadrant are registered trademarks and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.

Source: ibm.com

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4 trends that help organizations unlock the value of Salesforce

Over the past few years, organizations across the globe have been required to accelerate their technology investments to operate amid massive market disruptions. Companies that were already firmly rooted in digital and cloud technology endured challenges more effectively than their counterparts. The question is no longer whether to invest in these platforms — it’s how to strategically optimize those investments to accelerate business value.

Salesforce is one of the platforms leading the mandate for change. Today’s leading enterprises are maximizing the value of Salesforce through a holistic approach to business transformation and they are creating essential business systems that are agile enough to thrive amidst disruptions and uncertainty. These companies will outperform competitors and deliver consistent wins that accelerate progress.

The State of Salesforce report focuses on ways companies can unlock the next wave of value with Salesforce. We look forward and share insights into how business leaders around the globe envision Salesforce, and how Salesforce enables organizations to withstand constant change.

Below is a summary of the four trends identified in the report — trends that show the importance of using Salesforce across your entire business, not just in discrete business units or departments.

Trend #1: Unlock value by using cross-cloud solutions

The next wave of business value lies in using the cross-cloud capabilities provided by Salesforce to optimize digital operations. Leading companies are pursuing operational excellence to unlock results like profitability, higher productivity, streamlined processes and employee retention. With Salesforce, they have access to intelligent workflows, global partner networks and the features that provide customers and employees with a true 360-degree experience.

Businesses must tap into the power of the entire Salesforce platform and product suite to gain the benefits of a true cross-cloud experience. You’ll achieve results through automation, integration and collaboration to reduce costs, ramp up productivity and deepen connections among users.

Companies that embrace cross-cloud solutions come out ahead. More than 75% of organizations say Salesforce increases their business productivity, employee satisfaction and customer satisfaction.

— The State of Salesforce Survey, 2022

Trend #2: Unlock value by becoming a trusted enterprise

We’ve entered the era of the trusted enterprise. People want to engage with businesses they trust, whether as customers, partners or employees. Building a trusted enterprise comes down to using digital technology in ways that live up to stated values regarding ethics, transparency, security, privacy and safety. Leading companies are using Salesforce to create responsive, trustworthy and intelligent systems that safeguard users’ peace of mind and implement AI with integrity.

Establishing a trusted enterprise requires coordinated effort and alignment between your business culture and technology. With Salesforce and its broader ecosystem as the lynchpin between your values and processes, you’ll seamlessly clean up and secure user data and design trustworthy AI that drives engagement and growth for your organization.

Becoming a modern, trusted enterprise means embracing AI, but taking care to do so ethically. 60% of executives cite customer and employee trust concerns as a top blocker to using AI, while 57% cite issues around transparency and the ethical use of data.

— The State of Salesforce Survey, 2022

Trend #3: Unlock value by innovating smarter

Leading enterprises are building systems and technology that can respond to fast-paced changes in the market. Modern business requires an innovative mindset that’s ready to support new visions and updated methods that bring them to life. The organizations that are modernizing most effectively are taking advantage of what Salesforce refers to as “configuration not code” and embracing the constantly evolving Salesforce ecosystem to innovate infinitely.

The core Salesforce platform and its numerous new releases ensure that your business always has access to the latest features and capabilities. When your leadership is aligned with innovation-based goals in mind, you’ll effectively orchestrate and execute enterprise-wide transformation.

Innovating smarter means finding the right partners to help you get the most out of Salesforce: 83% of customers work with an external partner to manage Salesforce, leveraging their insight and expertise to support ongoing innovation and take advantage of new features.

— The State of Salesforce Survey, 2022

Trend #4: Make sustainability a transformation catalyst

Environmental impacts and disruption within the global economy have made sustainability a strategic business imperative, and IBM and Salesforce are leading transformational environmental change. Progress is possible, and both organizations offer ways business leaders can embrace eco-friendly strategies and technology that move everyone forward.

Data-driven environmentalism is quickly moving to the forefront, requiring business leaders to account for not just their internal operations but for the far-reaching impact of their products and services. Data-driven transparency and insights help your organization achieve truly transformative sustainability objectives where core values are integrated into the very fabric of your enterprise. To begin this journey and establish a scalable and measurable approach, companies must focus on their data, culture and leadership. Platforms like Salesforce provide the technology necessary to integrate all aspects of sustainability into core business functions and transform the entire enterprise.

Turning sustainability ambition into action is essential for businesses moving forward. 90% of companies cite long-term sustainability as one of the most important challenges facing their organization over the next 18 months.

Source: ibm.com

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How can a CFO foster enterprise-wide change in finance transformation?

Successful finance transformation initiatives cannot be achieved in a vacuum. Beyond building solutions that could potentially deliver enterprise-wide value, chief financial officers (CFOs) must also engage other department heads, alliance partners and key stakeholders in scope planning to encourage alignment on a shared vision.

Finance departments traditionally used data that works within their own part of the business, but they are increasingly using non-finance data from within their companies and unstructured data from external sources. An example of a significant finance transformation initiative might be embedding artificial intelligence (AI) in forecasting revenue. Modern systems will be based on insights delivered by AI. While these reports may be accurate and delivered by a CFO with a high level of confidence, the CFO’s peers (who previously relied on other manual reports yielding higher payouts) may resist this change. In this finance transformation scenario, CFOs must consider the perspectives of colleagues in other departments to mitigate resistance.

Effective integration between finance and non-finance data is crucial to the ever-evolving technology landscape. Strategic CFOs are stewards of transformation whose change management styles enable operational excellence.

Risks of change management failure

Money is left on the table. Without understanding new ways of working through change management programs, businesses will not realize the full value of any finance transformation. It’s like buying a vehicle with 4-wheel drive, but never engaging the feature—you will continue to get stuck in the snow. In finance transformations, we have seen similar operational pitfalls. We’ve seen teams continue to custom-tailor reports in Excel after their enterprise implements a new ERP or other reporting system. We’ve seen staff double-check transactional work even after the company tasked a new shared services center to execute these transactions and manage quality.

Performance takes a nosedive. Unless a focus is put on business partnership, insight generation, continuous improvement and advisory activities, business units will not fully benefit from finance transformation efforts. There is always a learning curve during transformation, but if CFOs don’t employ the most effective change management to mitigate this curve, finance function performance such as operational process metrics or time spent on business partnering, will likely lead to an increase in total cost of implementation and system ownership, which could negatively impact the business.

The superstars leave. Top talent within an organization has many career options available to them. Those individuals expect to work on well-managed programs with clear expectations. Employees need to know how transformation will make their lives better and progress their careers. If they experience the extra effort involved in transformation without a clear view of the benefits, they are likely to look for other, more attractive opportunities. Robust change programs that highlight and champion individual benefits and enable participation and contribution from skilled employees help to lower top talent attrition and have broad business impact.

Succeed in collaborative finance transformation with strategic talent

The approach will vary depending on the enterprise, the maturity of the finance organization and how the plans on scaling your new system. There are different starting points and catalysts that drive the finance transformation agenda within finance organizations.

Transformation is constant and essential, but one of the biggest challenges to overcome is transforming talent. The focus of the CFO has shifted from transactional work to relational value that generates business partners.

Organizational constructs are evolving, especially after the pandemic. Now CFOs should be less focused on acquiring talent with traditional finance competencies and more focused on talent who can be strategic and mindful of behaviors and outcomes.

Winning strategies for managing change across finance and non-finance teams

When working to unite finance and non-finance teams, here are some key strategies:

Think big, start small, act fast. Finance transformation should feel empowering and realistic. A big-bang mindset is great, but the goal should be achievable. This is possible in small, fast-paced phases where value and benefits are generated quickly and reinvested. A CFO should feel like his or her team is finally enabled to reach operational efficiency that supports the business and makes life easier. Long gone are the days of feeling change fatigue amid a big-bang transformation that also requires heavy cost takeout.

Involve your whole workforce. Spending USD $100 million or more on an ERP solution will not drive benefits if the workforce does not know how to use it. CFOs need to enable the workforce to operate in their new environment and use the new tools and technologies to make their roles more efficient.

Don’t hunt for unicorns. It’s impossible to find a one person within a finance organization who has all the skills required for every role required in a modernization initiative. But by training and equipping people across the enterprise with diverse skills and by creating a culture that’s receptive to change, teams can operate holistically to create the unicorn effect they’re striving to achieve. When working with CFO and senior finance executive clients, IBM Consulting brings not only finance and accounting experts but also data scientists, industry and technology leaders.

To gain widescale adoption of transformation initiatives, CFOs must ensure that relevant stakeholders have a purpose and a place in the planning of efforts and design principles. Empower employees with new ways of working to fully realize initiative benefits that you, as CFO, are championing.

Source: ibm.com

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Building a culture of data-driven decisions and insights with IBM Business Analytics

Organizations are managing and analyzing large datasets every day, but many still need the right tools to generate data-driven insights. Even more, organizations need the ability to bring data insights to the right users to make faster, more effective business decisions amid unpredictable market changes.

Meeting business goals with data insights

By building on our existing portfolio of business intelligence (BI) and planning analysis solutions, our clients are transcending manual and siloed analysis processes to optimize financial targets, sales goals, and operational capacity requirements. In doing so, they are putting their data to work to better meet their business objectives. Ultimately, every user, regardless of skill, can now feel empowered to make well-informed data-driven decisions.

Lessons from the IBM Data and AI Forum

Most recently we held an event at the IBM Data and AI Forum in Germany (available on demand here) where we shared the latest news in our business analytics portfolio. This included announcing the release of IBM Business Analytics Enterprise, which includes IBM Planning Analytics, IBM Cognos Analytics and the new IBM Analytics Content Hub.

During the event, we had the pleasure of hearing from many clients, including ALH Gruppe, a leading finance and insurance company in Germany who’s been using IBM Cognos Analytics with Watson for over a decade to support decision-making of all kinds, and recently tried our Business Analytics Enterprise solution. Mr. Oerthle, Head of Analytics Reporting & Infrastructure, ALH Gruppe shared, “With the new IBM Analytics Content Hub, we are able to connect internal stakeholders to multiple different BI solutions for easier, faster access to self-service data, enabling better outcomes for our end customers.”

If you missed the event and want to learn more about the new capabilities announced, here’s a quick recap of the exciting announcements:

IBM Business Analytics Enterprise

To unify the analytics experience, we’ve created a suite of our enterprise class business intelligence and planning analytics solutions, which includes the Analytics Content Hub. This suite of solutions helps transform the way clients can access, manage and consume business insights. Designed to allow users to view planning and analytics dashboards from multiple vendors, the IBM Analytics Content Hub brings all IBM and other common business intelligence tools into a single personalized view. With IBM Business Analytics Enterprise, users discover and access analytics and planning tools in a streamlined experience. As mentioned, this new pre-bundled enterprise analytics suite includes IBM Planning Analytics, IBM Cognos Analytics and the new IBM Analytics Content Hub.

IBM Planning Analytics as-a-Service on AWS

To help clients gain high availability and elastic scaling on demand, we’ve brought the power of IBM Planning Analytics as-a-Service on AWS. Clients can now request access to procure IBM Planning Analytics as-a-Service on AWS. This helps to boost forecast accuracy and consistency while driving faster time to insights. The full version will be available on AWS later this year.

IBM Planning Analytics Engine

The scaling capabilities of IBM Planning Analytics are unmatched, and we are continuing to build on this momentum. We are excited to announce IBM Planning Analytics Engine, a modernized distribution of TM1 for Kubernetes. Think – same TM1, different deployment architecture. Designed with resilience in mind, it’s available in IBM Planning Analytics 4.5.1, on-premises or other cloud providers.

With the amount of data and technology organizations have nowadays, it’s no longer possible to rely on simple spreadsheets to predict and plan for future business needs. Most organizations understand the power of analytics and business intelligence (BI) to plan, forecast and shape future business outcomes; however, for many, the analytics tooling and the insights they produce are still locked away in data silos. With the power of IBM’s business analytics solutions, organizations can gain access to real-time data, eliminating manual spreadsheets and organizational silos. They can meet their planning and forecasting needs, and ultimately transform their organization from what’s coming, to what’s next.

We are here to help! Explore our newly released eBook on the four steps to making better business decisions, or watch the on-demand sessions of the IBM Business Analytics launch event to hear more from our customers and partners on the power of using Business Analytics to make well-informed business decisions.

Source: ibm.com

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Trustworthy AI helps provide equitable preventative care for diabetics

There are over 30 million people in America who have diabetes, and people with diabetes need to remain vigilant about their health. They need the extra attention and resources provided by their healthcare systems because, unfortunately, around 38% to 40% of people with diabetes end up visiting the ER due to complications. Healthcare organizations – both providers and payers – across the nation are seeking transformative new ways to render quick aid to vulnerable members. For many, part of the solution is trustworthy AI.

A large North American healthcare organization uses an AI powered solution to help them identify vulnerable members who can benefit from timely intervention. The organization had established a community health program, with units ready to reach out to member communities to promote better health and improve health outcomes. They needed a system to identify the people who most needed the help. If they could deliver preventative care, they could also reduce member trips to the ER and help members enjoy a better quality of life, while reducing costs for the company and optimizing hospital staff and equipment.

Healthcare organization uses technology to identify members for proactive care

The goal was to predict member groups that were at risk 30–60 days before hospitalization would be necessary, to give community health units time to intervene. In addition, they needed demographic data to ensure appropriate care for the community in need. For example, if a non-Spanish-speaking unit member reaches out to a primarily Spanish-speaking community, the odds of successful intervention will be lower. The healthcare company understood that it’s not enough to build an accurate machine learning model; they needed to connect it to the human experience.

To accomplish this, the organization brought together various data sets, analyzed, and combined them, then built predictive Machine Learning (ML) models to identify their most at-risk members. At this step in the journey to AI many businesses run into trouble with their AI initiatives. And with good reason: not all AI systems are created with the proper ethical guardrails in place. Organizations need to be able to trust their data science outcomes. An AI system, especially one with an impact on health, must be fair, explainable, robust and transparent. The AI must be trustworthy.

A lot can go wrong when an organization decides to operationalize AI, and avoiding undue risk is a significant part the process. To mitigate that potential risk, many business leaders are finding success using proven data fabric architecture patterns and adapting those patterns to their specific organizational processes.

What healthcare is doing with data fabric and AI to mitigate risks

A data fabric architecture provides visibility and insights into data, enhanced access, control over your data and advanced protection and security. Here’s how that North American healthcare company achieved its goals using data fabric.

The first step was ensuring they were using relevant data sets. They started with claims data. Demographic data as well as diagnostic information from the patient’s past medical visits were then combined. To complete that story, the organization brought in socio-economic data via Social Determinants of Health (SDOH) datasets.

After connecting all the different data sources — claims data, diagnostics data, socio-economic data, and demographics data — with appropriate rules and policies in place within a data fabric using IBM Cloud Pak for Data, a team of data scientists built Machine Learning models, following best practices for the AI/ML lifecycle.

Just as being accurate in your predictions is important, it is equally important that the predictions be equitable. The organization must have confidence that the predictions will cover a diverse member population, to ensure quality care reaches everyone. Guardrails were put in place to check for and catch bias at various stages of the AI/ML lifecycle. This starts with checking for bias in the data set, checks during the model build and validation stages, and ongoing bias monitoring after the model is deployed. Similar guardrails were built to monitor quality and data drift as well as to generate explanations for the model predictions.

How trustworthy AI provides better help

Using architecture patterns for Data Fabric and Trustworthy AI, the North American healthcare organization can ensure care that is equitable across diverse member races and social classes. The solution can identify at-risk members who need intervention, the automation saves time, increases efficiency, and provides a pathway to get members help when they most need it. Additionally, community health workers have access to better information about the communities they serve, making it easy for them to explain why members are receiving a visit, which builds trust in the process and maintains a good relationship between the organization and members.

IBM Expert Labs offers a variety of architecture patterns mapped to successful use cases and common entry points like Data Governance and AI Governance/Trustworthy AI. The healthcare organization used such an architecture pattern to help them better address their members’ health and well-being. What could your business use it for?

Source: ibm.com

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