Drama, disruption and daring to look ahead

The recent potential for a rail strike in the US threatened a system integral to our supply chain. A disruption would have catastrophic impacts on industries, suppliers, manufacturers and retailers across the country. It would be yet another stressor on an already strained supply chain that, over the last 3 years, has faced disruptions from the global pandemic, rising inflation, climate change, historic geopolitical events, unstable financial markets and sustainability challenges.

As chief supply chain officers (CSCOs) walk the tightrope over potential disaster, their steps are far from tentative. A new report by the IBM Institute for Business Value (IBV) collects insights from 1500 surveyed CSCOs. According to the report, CSCOs are helping their organizations differentiate and create competitive advantage by using data and AI to improve their supply chains. And that competitive advantage is driving profitability and an increase in revenue over their peers.

Smart investments give clear advantages

Corporations that align their digital and sustainability transformation agendas achieve 20% higher revenue growth when compared to their peers, the report reveals. CSCOs are seeing a clear competitive advantage because of these investments, from a top-line and bottom-line perspective. They’re also getting a differentiated proposition to attract top tenured talent and early professional talent.

Over half of surveyed CSCOs are accelerating investments in digital technologies, including increasing automation and digitization of physical and asset-driven processes. 48% are applying open innovation with business partners, 46% are exploring new risk models and 54% are taking a cutting-edge approach to data-driven innovation, including employing predictive approaches and implementing tech-infused workflows.

Take for example the Hong Kong Applied Science and Technology Research Institute Company Limited (ASTRI). This R&D center for information and communications technologies is tasked with promoting Hong Kong’s competitiveness in technology-based industries. As part of its mission, ASTRI is helping manufacturers shorten their time to market, reduce development costs and enhance the quality of their products.

ASTRI has developed a digital-twin approach to equipment development. By implementing a science-based, agile approach to designing smarter manufacturing equipment, leveraging intelligent workflows across assets throughout the extended production process and using requirements-driven analysis and a model-based design, the organization creates a digital twin of an equipment piece. This allows engineers to perform a wide range of simulations and tests at nominal incremental cost to identify potential design defects sooner in the cycle. This model-based method also enables earlier validation of customer requirements.

ASTRI estimates that the twin approach has reduced integration time by 40% and cut the total cost of development by 30%. In addition, the use of robotic automation, IoT sensor integration and digital twin modeling for predictive maintenance supports 24/7 factory uptime.

Innovators edge out the competition

Using such transformational technology investments, CSCOs manage their supply chains to drive powerful results. They ratchet up tech strategies and adopt a data-driven innovation approach that emphasizes the scaling of a hybrid cloud infrastructure, AI-enabled workflows, customer-focused sustainability and a deeper focus on cybersecurity. These CSCOs make up the top 20% of those surveyed, also known as “the innovators.”

Innovators are edging out other CSCOs by embracing digital transformation. They use hybrid cloud platforms 60% of the time, versus 49% among their competitors. Innovators also lead the field with digital infrastructure that enables new technology investments to scale efficiently and deliver value. They use digitalization and AI automation 81% more than their peers. 90% of Innovators use AI and advanced analytics in demand management and predictive forecasting, which is 18% more than their peers.

The results highlight the importance of innovative CSCOs who prioritize digitalization for efficient end-to-end visibility and dynamism. In short, if you want to increase performance and value, data-led innovation is your journey.

Source: ibm.com

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Four steps to app modernization success

App modernization can save costs and increase revenue, but you need a strategic approach. Success requires a deep understanding of your organization’s needs and a plan of action that won’t disrupt your business as you integrate new methods into your company culture.

The recent IBM Consulting publication Strategic app modernization drives digital transformation spells out the enormous potential benefits of a successful app modernization project:

◉ 15–35% savings on infrastructure year-over-year

◉ 30–50% lower application maintenance and running costs

◉ 74% lower costs on hardware, software and staff

◉ 10% improvement in application operational efficiency

◉ 14% boost in annual revenue

Yet the vast majority of app modernization attempts struggle to succeed or are underwhelming. How can you avoid the pitfalls that can cause efforts to stall out or underperform?

App modernization is a series of journeys that add up to a more thorough digital transformation. You can respond to each new opportunity over time and address new challenges as they arise. In this way, every modernization effort — for apps, infrastructure, processes or something else — mirrors the goals of the IT industry as a whole. They’re fundamentally about adapting to change driven by business demands.

The following four steps provide a sound framework for app modernization. Think of them as best practices for starting your journey and as guardrails to protect you from common mistakes.

1. Assess

Understand the current state of your company, the goals you want to achieve and how to transform without disruption. Then go through an org rationalization exercise to analyze your existing systems and workforce. Build a solid basis of understanding of both your business needs and your existing application landscape. This step incorporates the three types of understanding outlined in a previous piece, “What keeps a CIO up at night?”

2. Select

Transform your understanding of challenges and starting points into a concrete plan of action. You need to move from a general desire for improvement to the specific technical goals that you can achieve through app modernization. This step also involves choosing the correct hyperscalers or other public and private cloud providers to deliver the services you need.

3. Outline

Design a roadmap and timeline with strategically staggered app modernization journeys, each of which adds value without disrupting existing operations. In this step, you draw on your understanding of your current situation to plan how processes and dependencies will change as you modernize each app. Third-party help is particularly useful in this step, because internal perspectives on processes and dependencies often lack clarity.

4. Adapt

Connect your new app environment to the people and processes in your organization. As you modernize your application mix, it will support and challenge your workforce in new ways. Integrated processes might be more efficient, but they’re also unfamiliar. As you empower people with new capabilities, they’ll also take on new responsibilities. The process can be disorienting without proper support and training. And in the worst case, a disengaged workforce can completely undermine the value of any modernization effort. Planning cultural change as part of your technical modernization is essential, not an afterthought.

The right help can make all the difference. An experienced modernization partner can work alongside you to assess, plan and modernize your apps. By working with IBM Consulting, you can leverage years of institutional knowledge, experience across industries and our expertise in delivering cutting-edge innovation.

Source: ibm.com

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How Newcomp Analytics partners with IBM to advance clients’ supply chain insights

When Newcomp Analytics started working with chocolatier Lindt Canada more than 15 years ago to support their supply chain, Lindt had no full-time IT personnel for analytics. Lindt now has a team of 10, including a business intelligence (BI) manager and BI developer analysts. Yet Newcomp continues to be an essential and trusted partner, helping the company keep up with the high volume of analytics solutions it needs to address. “Newcomp has a track record of delivering with no surprises,” says John Walter, IT Director at Lindt Canada.

Helping clients close the business analytics skills gap

What makes Newcomp so invaluable to clients like Lindt? The company’s up-to-date expertise with IBM Cognos Analytics and their close relationship with IBM are key factors. Brian Simpson, VP, Analytics & Performance Management at Newcomp Analytics says “Newcomp has been a strong partner with IBM for many years, dating back to the early days of Cognos Analytics. IBM has the best channel ecosystem in the market today… it’s like a well-oiled machine. They are the standard to which we hold all other vendors.”

“There’s a lot of demand for analytic skills in general, a lot of demand for Cognos Analytics… and organizations are all fighting for a limited number of resources,” says Brian Simpson. “As an IBM business partner, we can bring those skills in a temporary capacity to the organization, help them with the heavy lifting, and get the project completed, so they don’t have to have a roadblock of needing to recruit and train analytics professionals—they can do the project while building those skills in-house.”

Lindt has used Cognos Analytics for more than 20 years as an analytics solution for its sales and marketing functions. The application provided these teams with valuable business intelligence and trend analyses across a wide variety of variables from single SKUs to product categories, from store-by-store sales to regional trends, and temporal factors such as seasonality. These insights supported the company’s double-digit growth in Canada during that time.

Extending business analytics to supply chain management

Though a supply chain management team doesn’t directly influence sales, cost-to-serve factors such as transportation and palletization can have a significant influence on profitability when delivering hundreds of millions of dollars’ worth of chocolate.

Unfortunately, Lindt’s supply chain management team had been under-serviced. Left to their own devices, they had resorted to using legacy reporting tools such as Excel that required manual gathering, slicing and dicing of data. Consequently, this data was siloed, unshareable, hard to use, lacked quality and governance controls, and could not be used in automated processes.

Newcomp drew on their technical ability and extensive industry experience with CPG metrics, collaborating with Lindt to understand their business challenges and where to optimize. Working with Lindt’s key stakeholders on the supply chain team, they identified key priorities for migrating the team from its legacy tools to Cognos Analytics’ modern data analytics toolset. Lindt’s satisfaction using the application in its sales and marketing capacity bolstered their decision to expand it to the supply chain management while also supporting other key components of their technology stack including Microsoft SQL Server and Microsoft Server SSIS.

By incorporating new data feeds from transportation providers and warehouses and aggregating these to the master dataset, Newcomp developed a cost-to-serve dashboard in Cognos Analytics. Now Lindt could ask new questions and draw new insights: Why do we spend more shipping to certain retailers? How can we drill into the data to identify underlying factors and get a better outcome?

Advancing clients’ strategic data analytics capabilities

The solution, according to Brian Simpson, was “A huge advance in Lindt Canada’s business intelligence capabilities.” It helped Lindt’s supply chain management team reduce their reliance on Excel, and reduced time and effort. The data ingestion process improved data quality and governance; automation also improved data quality by eliminating manual merge and preparation of calculations. A consolidated view of data is now available through the enterprise data warehouse and through Cognos Analytics. Overall, the solution has increased the speed-to-insight and ability of Lindt’s supply chain team to share and visualize high-level KPIs from their own dashboards and data sets. It has also freed up the executive team’s time to focus on more strategic activities.

Next steps for Newcomp and Lindt: building a dynamic cube in Cognos Analytics and exploring how the company can use IBM Planning Analytics to improve forecasting and data-driven decisions for competitive advantage.

Newcomp has a strong partnership with IBM, maintaining its certifications and expertise to stay at the forefront of business analytics solutions. This in turn makes Newcomp a trusted client partner for companies such as Lindt Canada, consistently delivering value across a growing range of business functions.

Read the detailed case study to learn more about the work Newcomp Analytics and Lindt Canada are doing. To learn more about IBM Business Analytics, watch the replay of the Business Analytics Launch Event, where you can hear more case studies on how others have used IBM Cognos Analytics and IBM Planning Analytics to accelerate decision making.

Source: ibm.com

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What do you need from an app modernization partner?

Strategic app modernization means assessing and optimizing your application mix to overcome challenges and build toward future goals. But an almost endless number of variables can arise while modernizing your applications. Even if two different enterprises are modernizing similar apps using the same products and public and private cloud hyperscalers, various other factors will send them down different paths. For example, they may have different business priorities, distinct budget considerations and differing levels of talent within their organizations.

As I wrote in my previous blog posts, “What keeps a CIO up at night?” and “Four steps to app modernization success,” the failure rates for enterprise app modernization efforts show that this knowledge may not be enough. You often need a trusted partner to help support the process.

Even though the goals of app modernization might be similar across different cases, the actual work will be highly customized. With custom work, an experienced modernization partner can make the difference between failure and success. If you can leverage the expertise of a partner with proven experience, you don’t need to rediscover solutions for every challenge you face.

For example, you could apply a predesigned set of best practices for integrating popular technologies like S4/HANA, AWS or Azure. Or you could leverage existing blueprints from previous implementations as inspiration that shows the necessary steps and interconnections. These prebuilt tools and procedures can accelerate the implementation and delivery of modernization projects, making success more likely and more rapid.

At IBM Consulting we think about the app modernization journey as well-defined steps: moving from the desired outcome to specific patterns of activity, choosing a hyperscaler and then deploying resources to cloud as necessary. Multiple overlapping app modernization journeys can add value in phases without disrupting existing workflows.

An experienced partner can help you make these choices and develop a plan. IBM Consulting brings together solutions and strategies in a comprehensive service and platform that orchestrates our extensive expertise, including rules, tools, technical assets and starter kits. This service can help you achieve your desired cloud outcomes quickly and reliably.

Here are some of the things that you should look for in an app modernization partner:

◉ Sound engineering principles delivered through a collaborative methodology to deliver technical excellence regardless of technology or provider

◉ A core technology foundation that applies regardless of landing zones and geography to drive standardization, scale and consistency

◉ Red Hat® OpenShift®, Nordcloud and Taos® accelerators to deliver portability and end-to-end hybrid cloud management

◉ Embedded security and compliance to leverage solutions such as IBM Cloud Pak® for Security and X-Force® to automate and improve security and compliance performance across environments

◉ Proprietary assets to incorporate hybrid cloud journeys, playbooks and tools developed over years of experience and implementations

◉ Collaboration with experts to access the latest technical solutions from a world-leading R&D arm such as IBM Research®

While every client’s app modernization journey is different, there is an underlying method to how we conduct it. The answers we provide aren’t necessarily different than what you might arrive at on your own — we believe they’re answers that make sense for you — but partnership can help accelerate reaching goals with less disruption and error.

Source: ibm.com

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CSCO: Invest in control tower and digital twins to build your cognitive supply chains

Chief supply chain officers (CSCOs) have once-in-a-generation opportunity to pivot from cost-focused reactive operations to running a resilient and agile value chain. In the past three decades, supply chain operations have expanded across the globe, incorporating multiple partners, cultures and systems. As a result, CSCOs have long struggled to answer many questions in real time.

As explained in the recent IBM Consulting paper “Building intelligent, resilient and sustainable supply chains,” even a well-run supply chain has weaknesses that can leave companies asking: Where are my orders? What is currently in manufacturing? Do I have a supply shortage, and how do I mitigate it?  When will the orders arrive at my distribution center or at my customer’s front door? What is in the container I’m tracking?

This lack of visibility means that most supply chain operations are fundamentally reactive—constantly catching up with events. Research from the IBM Institute for Business Value has shown that Fortune 500 companies lose anywhere from 2% to 5% of revenue due to misplacement of inventory or production of incorrect SKU and channel mix.

This isn’t tenable. The supply chains of the future will need intelligence, speed and agility to meet growing expectations of consumers and B2B partners. The next generation of supply chains embedded with exponential technologies will be able to predict, prepare and respond to rapidly evolving demand and a continually changing product and channel mix.

As companies mature their digital twin, prescriptive and cognitive capabilities, they have an opportunity to improve supply chain productivity by 10–15%, eliminate non-value-add work by 50–60% and improve their disruption response time from days to hours or minutes.

Cognitive supply chains harness data as fuel to build resilience and agility into their processes. A strong data foundation is an essential first step, but companies must further build capabilities in three areas to provide end-to-end visibility, optimization of upstream and downstream processes and simulations of scenarios and alternatives based on margin optimization or service level attainment.

When IBM focused on building these capabilities internally, it brought dramatic improvements. IBM employs supply chain staff in 40 countries, collaborating with hundreds of suppliers to make hundreds of thousands of customized customer deliveries and service calls in over 170 countries. In building the world’s first cognitive supply chain, IBM moved from inefficient, siloed, manual systems to one integrated system augmented by AI. For more detail, read the case study.

In the cognitive supply chain, rote work is reduced or eliminated, while an integrated supply chain picture emerges from multiple solutions, including a cognitive control tower, cognitive advisor and demand-supply planning and risk-resilience solutions. The end result is real-time, intelligent supply chain visibility and transparency.

The systems also sense and respond to changes in demand as they happen and simplify the automation of supplier management. On a minute-by-minute basis, employees have immediate access to the information they need to identify and mitigate disruptions.

Since its cognitive supply chain became operational globally, IBM has saved USD 160 million related to manufacturing optimization, reduced inventory costs, optimized shipping costs, better decision-making and time savings.

To follow this example and adopt proactive supply chain management, companies need to take three strategic actions:

1. Deploy a control tower and digital twin

AI has enabled the digital twin to provide visibility of events across customers, suppliers manufacturing locations and third-party logistics, and it has enhanced ability of companies to understand their operations real time. By adding a control tower—an AI-based simulation and recommendation engine—companies can more easily manage complex supply chain processes amid constantly changing market conditions, and they can prescribe recommended actions based on historical precedents or predetermined cross-functional business rules.

A capable digital twin solution should be paired with a control tower to:

◉ Enable near-real-time visibility within the internal and external network

◉ Ingest data across multiple supply chain functions such as planning, logistics, manufacturing and warehousing

◉ Simulate and model network disruptions or the effect of near-term plans

◉ Provide decision automation and recommendation engine capabilities

These capabilities transform business response during crucial moments. For example, during a supply disruption, an integrated system could detect the event, understand the timeline and impact of disruption, and recommend to either find alternative sources, put finished product on fair share allocation or increase order confirmation lead times.

2. Automate decision making and set up business value audit process

In previous work with leading companies, IBM consultants found that supply chain professionals make hundreds of decisions every day, ranging from inventory deployment, substitution, expediting and additional shifts to menial data cleansing ones. Even a capable control tower solution can’t address and automate all these value points individually. Companies should identify areas where decision automation and augmentation can bring bottom line improvements, add consistency and value quickly, and build momentum for further use cases. As an example, companies can deploy demand sensing and prediction algorithms to better match supply and demand if they have higher incidence of stockouts.

3. Build cross-functional workflows and avoid the functional excellence trap

As companies build digital capabilities, there is a temptation to focus on the most supportive functions to claim an early win. This may work in the short term, but it will ultimately reinforce the old supply chain model where functional excellence does not lead to a superior customer experience or reduced cost. Insist on re-imagining traditional processes and building cross-functional workflows where different functions and capabilities can improve business outcomes.

For example, don’t just focus on demand sensing capabilities; also train AI models for intelligent planning and risk mitigation. Insist on building automated sales and operation execution (S&OE) workflows wherein recent changes in demand patterns can be seamlessly propagated to inventory deployment and logistics. Use your capabilities to deliver superior customer service and more on-time in-full fulfillments.

Source: ibm.com

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Building stronger communities for future economic resilience

Evolving our thinking toward a human-centered circular economy

The principles of a circular economy are to eliminate waste and pollution, keep materials in use and regenerate natural systems. Applying these principles to everyday business applications is more vibrant than ever, especially as organizations shift toward new economic models. But approaching this without clarity is also where some of today’s challenges start to precipitate.

Collectively, business and society have excelled at discussing why it’s important to make these shifts. But to date, no one has holistically cracked the how. The economic argument for a circular economy has been largely anchored in the environmental elements of systems change, not in risk mitigation and proactive resilience, and certainly not incorporating the social impact of the changes to the system. But it’s crucial to put local communities and their approval of the social license to operate (SLO) at the center of the economic argument.

What would a circular economy look like with equitable access at the center?

As climate challenges heighten, consumers are taking notice and demanding change, and investors are asking companies for more transparent environmental and social governance practices. People are shifting their behavior to live and work more sustainably. Businesses talk a lot about a “just transition” and “economic equity.” But this has not translated into significant action so far. Why does progress feel so slow?

The role of society in systems change

Sustainability solutions so far have mainly spoken to environmental stewardship and profitability, as described in a report by the Institute for Business Value (IBV), Balancing sustainability and profitability. As we try to shift “systems,” many have overlooked the social dynamic of systems change. Thus, they have only created partial solutions that focused on economic growth at any cost, with incremental and inconsequential environmental benefits.

The supply chain crisis has limited our ability to make and distribute “stuff.” Empty shelves and shipping delays have crystalized awareness of the complexity of supply chains and how important they are to communities and economies. At the same time, supply chain leaders face mounting demands for sustainability, adaptability and value creation—all of which expose new risks and new opportunities for transparency, visibility and resilience.

Some of the greatest supply-chain thinkers have been talking about resilience and the capacity to recover quickly from difficulties. Resilience planning is a future-proofing method to not just ensure short-term recovery after a disaster, but also reduce long-term disaster risk.

Over the next decade we will see greater and greater disruption to global supply chains, due to climate change and poor systems design in an economic model that externalizes the total costs of ownership. According to the IBV report “The Resilient Digital Supply Chain,” extreme volatility has cast dramatic performance and financial impacts on supply chains over the past three years. 67% of Chief Supply Chain Officers (CSCOs) report significant negative effects on demand forecasting. 66% report greater volatility in order cycle times and 47% report that order rates are becoming worse.

We will see greater levels of climate migration—individuals forced to leave their homes due to climate related conditions—and disruption to communities. Typically, these communities sit on the poverty line and therefore have lower levels of resilience in times of disruption and change.

In the 21st century, businesses are built on distributed, long supply chains that prioritize a low-cost model and, in many ways, externalize risks tied to Environmental, Social and Governance (ESG) performance. This paradigm hits the communities at the base of our supply chains—where our clothes are woven, our food is harvested and our product materials are created or extracted—first and worst.

But what if the connection and collaborations between communities and corporations were closer and could increase resilience?

As the global population and middle class grow, so do climate migration and the widening economic divide. Threats like climate change and biodiversity collapse will permeate every facet of our access to clean energy, commodities, clean water and healthy and nutritious food. Choice will only continue to intensify these issues. Is the concept of shared value enough to cross the gap? We must demand regenerative, restorative disruption and investment to reach far and deep for progress.

During a panel at COP26, Philipp Hildebrand commented that “25% of global GDP is at risk over the next 20 years.” If we do nothing, or move too slowly, this will affect all of us. It will preoccupy all our lives and choices.

Therefore, if businesses want to create future resilience, we need to put social impact and community, not just the environment or the economics, at the heart of all of business decisions. We need holistic change and new models of success that are equitable and inclusive and that generate shared value for people and planet. This often means breaking away from the use of traditional key performance indicators (KPIs).

IBM's Sheri Hinish redefines the enterprise approach to sustainability

Future economic planning needs to be viewed through a social lens and is completely compatible with current circular economic thinking. The circular economy is about accessibility, ingenuity and resourcefulness. It’s about growth in a regenerative and restorative economy. It cannot only be for the affluent, or for those who choose to spend an extra “green premium” to offset the environmental impact.

The circular economy is an economic resilience model where materials are available and humans are also consumers of eco-services. A social circular economy is merely the next evolutionary stage of unpicking and solving for the complexities we face.

If you are a business that has a distributed supply chain, crossing borders, industrial verticals, and communities, why would you not consider the resilience of that community, that supports the start of your supply chain, as an area where you can create the greatest level of business risk mitigation and build resilience?

This is about creating resilience within a community to weather all coming storms: in climate, health, education, nutrition and all other problems and pressures that the community faces now and in the future. When we consider what systems we need to create for the future, what role does business play to ensure resilience? And importantly, what is stopping this shift?

As business leaders, how do we ensure the community that supports our workforce, and ultimately is our workforce, has access to fresh clean water, to healthy and nutritious food and to the education needed to meet the needs of supply chains? How does business create direct community resilience, to secure future economic resilience and de-risk for the long term?

In an Institute for Business Value (IBV) study of CSCOs and other C-suite executives, 32% of organizations cited increasing sustainable operations among their most important business priorities. This focus has forced supply chain leaders to become serial innovators linking social and environmental issues with business solutions. Many business leaders are using a circular economy approach to mitigate near-term cost concerns and focus on long-term value to the customer.

Transitioning to a circular economy requires supply chain leaders to embrace a new mindset and develop an appetite for business un-usual. Emerging technologies help organizations meet these complex challenges: Data incorporated from multiple sources—internal, public, scientific, marketplace—can be infused into business processes and decision-making to improve environmental outcomes. Virtualization can underpin the circular economy by applying the 9 Rs of circularity: Refuse, Reduce, Reuse, Repair, Refurbish, Remanufacture, Repurpose, Recycle, and Recover.

A new paradigm connecting the social license to operate to human-centered circularity and resilience

“You can’t do business on a dead planet.” More importantly, you can’t move ahead without treating the causes.

Our paradigm shift and new approach require us to think more about replicability rather than scale. The solutions to the challenges communities face today—to bridge the digital divide, to ensure access to education, arable land, clean energy and healthcare—will be complex, specific and socio-economically bound. We are drawn to simple solutions, as they create visible action. But complex problems require complex solutions, and that complexity can only be understood by taking a community-first approach, bringing the challenges and nuance of a geography to the heart of the solution, be that social, cultural or economic. This is the lens we must bring to our thinking. How do we bring people to the center of our solutions?

Any solution framework will also have to use data and technology to help redesign the way that local system works and how it creates equitable access. We have the tools to make this change happen. We just need to put them in the hands of the people that need them to thrive. And we must co-create these solutions with them.

To accomplish this, IBM has worked with Pyxera, a global organization dedicated to addressing challenges at the community level. Pyxera emphasizes creating and sustaining inclusive, equitable and regenerative systems. The organization has participated with IBM Impact Initiatives to support organizations committed to building stronger communities through economic resilience.

Businesses can create resilience by solving challenges at the community level, engaging with employees and community members. Doing so allows them to forecast and mitigate the risk associated with some of those meta-challenges faced collectively, which individual businesses cannot stop or influence on their own. This is therefore an opportunity to bring together the right stakeholders, the right organizations and the right community members to solve for the long term. We can help safeguard economic resilience by creating community resilience. It is a concept of shared value made possible by bringing the community to the heart of the conversation.

Source: ibm.com

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Understanding the current state of cloud transformation

To unlock transformational business performance, enterprises must be able to employ applications and data at scale across the enterprise IT landscape. Mastering hybrid cloud enables these capabilities with speed and security.

The IBM Transformation Index: State of Cloud helps establish an advanced view into the state of cloud transformation year after year. This informs technology investment for global businesses and allows organizations to benchmark their progress.

The development of this index is detailed in a new report from the IBM Institute for Business Value (IBV), “A comparative look at enterprise cloud strategy: IBM Transformation Index: State of Cloud.” As described in this report, the index is informed by deep data analysis of survey responses from 3,000 C-suite business and technology leaders across 12 countries and 15 industries. The survey highlights key findings that allow business leaders to evaluate and innovate hybrid cloud management.

Hybrid cloud has become the dominant architecture, but few continue to innovate and manage cloud environments holistically

The Index points to a strong correlation between hybrid cloud adoption and progress in digital transformation. In fact, 71% of those surveyed think it’s difficult to realize the full potential of a digital transformation without having a solid hybrid cloud strategy in place. At the same time, only 27% of those surveyed possess the necessary characteristics to be considered as “advanced.”

When companies first started migrating to cloud they assumed it would give them scalability, reduce costs and reduce technical debt. However, for this to happen, organizations must first determine how they want to connect the cloud assets and the rest of their estate to enable new ways of working. Adding more clouds does not address business objectives; companies need to create a solid hybrid cloud strategy that helps deliver the capabilities needed to achieve the business outcomes.

The initial excitement with respect to cloud is now shifting toward businesses partnering with the CIO, asking questions such as:

◉ Why should I move to cloud?

◉ How will it accelerate achieving my business objectives?

◉ What capabilities do I need before I can leverage the cloud?

◉ Which applications are best suited to move, modernize or build new?

A holistic strategy will help answer these questions and help companies define an architecture for delivering a single, secure hybrid cloud platform that supports the business need.

Lack of skills and talent is a limiting factor

When it comes to managing their cloud applications, 69% of respondents say their team lacks the skills needed to be proficient. This, combined with each cloud generating its own operating silo, puts constraints on the efficiency and effectiveness of people’s work.

To develop a cadre of cloud-skilled resources and create a single effective hybrid cloud operating model, consider the following steps:

◉ Start with defining a strategic workstream on a people agenda

◉ Empower a cloud Center of Excellence (CoE) to bring the hybrid cloud operating model to life to incubate and hone the necessary skills

◉ Accelerate execution and empower your people with a skills and experience development program to thrive in the hybrid cloud operating model

As you are on this journey, define the work required for hybrid cloud operations first and adjust your organization chart second.

Businesses have the tools to secure workloads in the cloud, but challenges exist

Though the adoption and use of security tools is ubiquitous, one thing that stands out in the survey results is that security is a concern for a large number of respondents who believe public cloud is not secure for their data.

More than 90% of financial services, telecommunications and government organizations who responded have adopted security tools such as confidential computing capabilities, multifactor authentication and others. However, gaps remain that prevent organizations from driving innovation. In fact, 32% of respondents cite security as the top barrier for integrated workloads across environments, and more than 25% of respondents agree security concerns present a roadblock to achieving their cloud business goals.

A modern security model must align with a dynamic hybrid cloud infrastructure while moving at the same pace as innovation happening at the data and application layer. This approach embeds security into the hybrid cloud product development process. It keeps system owners and developers accountable for employing security and privacy best practices in each code release, all the way down to the level of the workload.

Regulatory and compliance roadblocks can stand in the way of cloud goals

As regulations rise, so too do compliance challenges. 53% of respondents believe that ensuring compliance in the cloud is too difficult, and nearly one-third cite regulatory compliance issues as a key barrier for integrating workloads across private and public IT environments. This is particularly true for highly regulated industries like financial services, where more than a quarter of respondents agree that meeting industry requirements is holding them back. Embedding these requirements as core to the hybrid cloud architecture and operating model is crucial, as this will remain an ongoing need.

There is a lot of expectation about what cloud can do for business transformation, and some growing awareness about what it will take. There is a still a way to go towards mastering hybrid cloud.

As IBM Consulting works with clients across the globe, we see five common challenges on the journey to mastering hybrid cloud: architecture, people and operations, security, finance and the partner ecosystem. Luckily, these aren’t insurmountable. The truth is, you’ve probably solved similar challenges before, just not in the specific context of a hybrid cloud environment where public, private and on-premise IT landscape is today’s norm.

Source: ibm.com

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Flex your cloud-enabled ERP

The world of cloud-based enterprise resource planning (ERP) systems is ever-evolving. For some finance operators, investing in the right ERP system, or a cloud-based counterparts, can be a tough decision.

While many finance organizations realize the importance of modernizing their ERP systems, some see it as a heavily convoluted effort, and not one they’re willing to dive into without guidance. They let their system age, and the total cost of ownership (TCO) rises. It might feel like there’s never a “right time” to undertake modernization. But the right time was yesterday.

Other, braver organizations and finance operators eagerly take a go at implementing cloud-based ERP systems on their own, but they fail to unlock the greatest possible value of these capital-intensive projects. Integrating these systems in a way that delivers enterprise-wide value will require alignment with peers and stakeholders. Moreover, making solid ERP purchasing decisions and implementing them effectively requires core ERP competencies and a clear understanding of how to limit cloud cost waste.

Huddling around the virtual water cooler with finance operations and transformation gurus has revealed one thing for sure: IBM Consulting knows too well that it can be daunting for organizations and their stakeholders to effectively embark on this process. We’ve seen the ERP decision paralyze customers with on-premise ERPs, and we recognize what it takes to move to a cloud-based ERP system.

The primary aim for many should be ERP readiness and preparedness

After you’ve done your due diligence, you’re ready to implement and scale. Make sure you have explored modern ERP options and identified that these will yield the desired benefits. Then partner with finance transformation consults to assess the feasibility of implementing the new system. Last, enable and empower your team to take on the new transformation and accept a new operating model.

During this process, you should recognize that ERP transformation is less about choosing a specific technology and more about choosing the right technology to achieve desired outcomes. Consider these insights when identifying new and enhanced ERP systems, and set goals for current and future business needs to help realize the value of a cloud-enabled ERP.

Why is a cloud-enabled ERP best?

ERP is an essential part of a business and IT strategy. It’s the backbone that connects all aspects of a business. With a cloud-enabled ERP, you can:

◉ Integrate critical business processes

◉ Automate labor-intensive workflows

◉ Discover new patterns, insights and data anomalies using machine learning

◉ Stay competitive with a next-generation infrastructure and integrated technologies designed to help you run your entire business and finance operations more efficiently

For many organizations, the top consideration is operational efficiency. No matter what the starting level and regardless of the sophistication of the ERP, the suite of available options can be tailored to help meet identified needs. Moreover, the digitization of critical processes will allow businesses to propel and improve how technology is used. This allows for greater value realization and incremental investment throughout the journey as processes are refined and workforces are enabled to manage the new ERP system.

Organizations don’t need to face the risks of a cloud migration by themselves

Cloud computing can make organizations more competitive. But an estimated 32% of cloud spend is wasted. To reduce TCO and minimize the cost of implementing systems, many organizations partner with finance transformation experts.

If you’re among the few who have completed or earnestly kicked off an ERP deployment on your own and have realized planned savings and ROI, kudos, you are well on your way. If not, working with a partner with core ERP competencies will help you address unforeseen integration and value realization challenges. Keep in mind that a cloud-first approach reigns over on-prem these days — because it can also help improve your finance organization’s agility and time-to-value.

It’s also advisable to get help exploring many valuable cloud-enabled ERP applications that can help with broader system adoption. Whether it’s an Oracle Cloud Infrastructure (OCI) or another, the ideal approach is a solution that can be set up in a matter of weeks (from plan to complete) with expert advice from your business transformation consultant.

As we’ve personally seen from our clients, once you get buy-in from critical stakeholders and peers, you can rapidly accelerate the modernization effort and often see lower TCO, increased agility and improved productivity.

What if my on-prem ERP system is at the end of its useful life?

Clients often come to IBM Consulting with an aging on-prem ERP solution. With their on-prem warranty nearing end-of-life, an IBM Consulting client in the mining industry set out to migrate their ERP landscape. In this particular case, they partnered with IBM to deploy Oracle E-Business Suite, enhance analytics, implement multiple non-production builds — including upgrades for their operating systems and data base — and migrate their service-oriented architecture (SOA) applications to OCI.

Their commitment to the adoption of a sustainable and scalable cloud mode helped them eliminate mundane tasks. Not only did this lead to a significant reduction in TCO, but this client also realized a notable improvement in the health of the overall operations. In addition, by using intelligent workflows and artificial intelligence (AI), this client achieved a 34% cost saving and 75% improvement in ancillary benefits.

Another client in the business intelligence and publishing industry considered attempting an ERP migration on their own. After long internal deliberations, they chose to engage a consultant instead. They uncovered greater value after IBM Consulting helped them migrate multiple environments from on-prem to cloud. By accelerating their migration to cloud, they improved system reliability and performance in just under three and a half months — well ahead of their anticipated date of completion.

What are some additional innovations and advancements to keep on the radar?

The combination of cloud, data and emerging technologies (such as AI) is radically reshaping business processes into intelligent workflows. But those that operate in a silo tend to experience more challenges and may fail to realize the synergies between these advancements. Increasingly, the tight collaboration of CTO, CFO and CIO needs to come to bear given that many IT organizations lack the financial management capabilities to fully measure and manage cloud value.

Enterprises of all sizes and industries can extract the most value from a new ERP once the system has been implemented. For example, by leveraging intelligent workflows, you can further modernize and take advantage of continuous innovation to meet the ever-changing technology landscape.

Getting started is a challenge. One way ERP clients are deriving value quickly and at scale is through use of IBM Garage Jumpstart sessions, which provide a framework for accelerating their digital and finance transformation. These serve as a convenient platform for generating innovative and relevant ideas. In my experience, we can bring in the practice leads, technologies and experts to help turn those ideas into business value in a matter of weeks.

The level of engagement in these sessions is exciting. Customer pain points come into focus and teams are empowered to take calculated risks. As we’ve witnessed, clients who come in fully educated and engaged in the adoption of leading technologies like cloud-enabled ERPs are bound to achieve their desired outcomes. We help speed up solution development and measure and quantify that value.

In 2022 IBM was named a Leader in the 2022 Gartner® Magic Quadrant™ for Oracle Cloud Application Services, Worldwide. Our team of finance transformation consultants can help you successfully implement and flex your new cloud-enabled ERP.

Source: ibm.com

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Empower your organizations to make smart workforce decisions

Over the past few years, the workforce has evolved more than ever. According to the U.S. Bureau of Labor Statistics, 4.25 million people quit their jobs in Jan. 2022, up from 3.3 million in Jan. 2021. And a 2021 report by the Society for Human Resource Management shows more than 40% of U.S. workers are actively seeking a new job or plan to do so soon. To stay resilient in these changing times and be ready for the future, it’s critical that organizations reexamine their human resources (HR) planning tactics. More specifically, organizations must turn to a holistic planning solution that enables data-driven decisions to improve their workforce needs without losing individual focus.

Why HR Planning?

One of the most important parts of HR planning is enabling collaboration and transparency across all teams. Consider a mid-sized company and all the different line managers associated in making salary, incentive and promotion decisions. HR must consider the following:

Performance ratings

◉ Who are the top performing employees?

◉ How do we retain them?

Staff movement

◉ Are there new hires?

◉ Who is changing roles internally, and is there a promotion involved?

Salary bill

◉ What is the spend for each team and across the organization?

◉ What are the increases and bonuses?

◉ What long-term incentives can we provide to ensure sufficient lock-in is in place?

Job market data

◉ Are we providing equal pay for equal work across race, gender and disabilities?

◉ How does our remuneration compare to that of our competitors/industry and the market in general?

Considering all of these factors above, an organization should invest in a holistic, extended  planning and analysis solution to bring together all the data impacting performance ratings, staff movement, planned salaries, job market data, and more in a single, consolidated view. This way, there’s no hidden data, but rather full transparency in the decisions being made – with the help of continuous, integrated planning at the heart of your business.

Governance and compliance in HR planning

Instead of focusing on manually pulling together disparate data in rows upon rows of Excel-based spreadsheets, which often leads to errors in a process that should be foolproof, your organization should look to solutions that can streamline your existing HR planning processes. Within IBM Planning Analytics, for example, you can build and maintain the right responsibility hierarchy and workflow that ensures the relevant managers are planning, reviewing and driving HR planning decisions to the next level.

If your planning processes are audited, having an extended planning and analysis (xP&A) solution like IBM Planning Analytics is a game-changer in tracing precisely who entered what data into which models used in the planning process.

HR planning for longevity and success

HR planning isn’t just about having the right employees; it’s also about recognizing and retaining your performant employees and encouraging workforce longevity and success. Aside from salary, stocks and monetary incentives, training and educational development are key parts of successful HR planning and staffing execution. Many organizations offer employee training programs, certifications, learning hours and more. But how are they keeping track of such metrics? What does continued success look like?

We’ve seen that IBM Planning Analytics can help HR teams better track and measure workforce success factors. In turn, this helps justify the investment in employee training programs and identify the ones best-suited to boost skills and performance. The result can be seen in improved bottom-line performance and ROI for a variety of organizations. With IBM Planning Analytics, you gain insights into performance metrics and employee morale, helping you prevent attrition and turnover challenges using trends that highlight risks much earlier.

Continuous workforce planning

Now more than ever, the steps organizations need to take to develop and enhance their existing HR planning processes is critical to support the entire workforce, which we know to have a significant impact on the success of the organization at large. Employees are the foundation of every business. Having a reliable, integrated planning and analysis tool is key – not only for your first-line managers to make better decisions, but for your entire organization to trust that fair and data-driven decisions are being made. We’ve seen solutions like IBM Planning Analytics help organizations to do just that.

Source: ibm.com

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IBM invests in ecosystem partners’ skills and experience to foster faster growth

As I’ve shared this year, IBM is on a journey to double down on our commitment to the IBM Ecosystem. We’ve made significant investments in placing our ecosystem partners at the center of our company’s go-to-market strategy. We continue to work diligently to simplify the experience and be more essential to their businesses with improved and expanded tools and resources.

Today, we are taking the next step in our partner journey by announcing a revamped approach to skilling that, for the first time, gives all registered PartnerWorld members access to the same training and enablement as IBM sellers. Importantly, partners now have access to those resources at the same time as IBM sellers, and at no cost to them. We are also rolling out a one-stop shop for learning and credentialing.

Premium training and enablement to help close deals

Partners have told us that the more expertise they attain in the IBM products they sell, the better equipped they are to win with clients. With this in mind, and with the goal of helping them win more, we have extended access to the same trainings, badges and enablement materials that our own sellers enjoy.

The skilling available to partners closely aligns to product offerings that partners use to deliver hybrid cloud and AI solutions for clients, within data and AI, automation, security, sustainability, infrastructure and more. New sales and technical badges demonstrate a partner’s industry-recognized expertise, including the ability to position and differentiate an IBM solution to clients. The badges are also shareable on professional social platforms such as LinkedIn, and they travel with the learner.

Some of the additional materials we make available include:

◉ Sales demos: guidance that enables partners to run their own successful demos for clients, including verbatim scripts that highlight benefits of the offerings

◉ Seller presentations: key templates to help win deals, including how to position the offering and how to share advantages over competitors

◉ Client presentations: ready-to-go assets for client meetings that highlight key benefits and advantages of IBM’s offerings

◉ Digital prospecting: additional content that showcases IBM product capabilities that can be shared with clients, such as white papers, analyst reports, decks and solutions briefs

When new content is made available, it can be accessed by IBMers and partners at the same time, to help improve collaboration and make engagement more dynamic.

Improved digital experience

As part of IBM’s undertaking to introduce efficiencies in an agile way, partners can access the skilling and enablement materials through a new learning hub designed to drastically improve the digital experience. It’s now simpler than ever to find the right training at the right time and complete the desired coursework. Users will notice a more modernized and consistent experience on the IBM training site, making it easier to find resources.

I encourage you to explore – start now by visiting the learning hub.

IBM’s commitment to the ecosystem

I want to be clear – partners and IBMers are considered a single team. The investments we continue to make in the partner experience are a part of our ongoing commitment to be more essential to their businesses. In addition to what we introduce today, over the past year, we have doubled brand-specialized partner sellers in the IBM Ecosystem, increased technical partner sellers by more than 35% and built up the digital experience with our Partner Portal. Our work has resulted in improved deal registration and introduced to partners more than 7,000 potential deals valued at over $500 million globally. (Proprietary metrics obtained from IBM sales data, January 2022–August 2022.)

Our work doesn’t stop here. We will continue to make investments in the partner experience so that together, as a single team, we can achieve our goal of doubling revenue through the IBM Ecosystem in the next 3–5 years. You have my commitment.

Statements regarding IBM’s future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

Source: ibm.com

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How IBM Planning Analytics can help fix your supply chain

Join the IBM Business Analytics live stream event on October 25, 2022

IBM Planning Analytics, or TM1 as it used to be known, has always been a powerful upgrade from spreadsheets for all kinds of planning and reporting use cases, including financial planning and analysis (FP&A), sales & operations planning (S&OP), and many aspects of supply chain planning (SCP). As far back as the 1990s and early 2000s there were companies, like the one discussed in this podcast episode, that took advantage of TM1’s power to support full integration of their financial and supply chain planning processes.

Build planning models to improve supply chain management

The challenge faced by every company is matching supply with demand. In a perfect world you would know precisely how much of your product the market desires, and you would be able to produce and ship exactly that amount to every location where your customers would be waiting, ready to buy.

In lieu of a perfect world, what do you do? You plan. Plans help you explore the consequences of your decisions in advance so you can understand your hedging options: Do I build up inventory here? Do I need to find new suppliers there? Do I have enough cash to fund these investments while also covering day-to-day operations?

You also build planning models to capture relationships and constraints so that you can change your driver assumptions and immediately see the impact on resources and capacity over time. Having the ability to build and use models in this way is fundamental to managing supply chain and financial risk through activities like “what-if scenario planning”, as explained in this blog post. Time matters too: your models must be quick to run, so analysis can be done before the assumptions are out-of-date. As such, planning becomes a continuous rolling activity as the lines between “plan”, “budget” and “forecast” are blurred.

Since there are clear cross-functional business correlations between demand and sales, supply costs and Cost of Goods Sold, it’s not hard to argue for supply chain and financial planning models to be integrated across the Extended Planning and Analysis (xP&A) cycle. However, the reality of this is complicated by several factors including:

◉ Differing time horizons and cadences: Days/Weeks vs Months/Quarters

◉ Differing levels of detail: SKUs/ Products vs Product Groups/ Lines of Business

◉ The need to collaborate, share data and agree on definitions across organizational boundaries and systems

Choosing the right technology to support xP&A for your strategic goals

A growing number of forward-looking companies are successfully navigating these complexities using IBM Planning Analytics, a technology capable of supporting secure collaboration, fast automated data acquisition, driver-based and AI-powered predictive modeling, and, unique in the market, the handling of large amounts of detail at scale without sacrificing performance.

With the right technology-foundation in place, it becomes easier to tackle the business alignment questions, starting with designing an end-to-end integrated business planning process that will lead efficiently to a consensus forecast (or plan).

The first step is always the unconstrained demand plan.

Even when supply constraints seem overwhelming, it’s still important to have this view, so you can take action to overcome the constraints in the future. Depending on the patterns of your business, predictive models can play a significant role in improving the accuracy of your demand plan, while also saving time through automation, as experienced by Arthrex, a global medical device company.

The next step is to start layering on constraints.

In a manufacturing, distribution or retail context, this is the supply plan. The supply plan is typically anchored in capacity and can combine manufacturing capacity, supply capacity and labor capacity.

Then, everything comes together.

With everything in the IBM Planning Analytics dashboard, it’s now possible to see where and when capacity shortfalls (or excesses) are imminent and explore options for mitigating situations in accordance with strategic goals.

IBM Planning Analytics can help your teams modify assumptions such as production capacity and labor allocation across a variety of scenarios in real-time, and immediately see the impact on all related metrics including constrained demand, inventory, sales, costs, and cash. QueBIT’s webinar includes a demonstration with IBM Planning Analytics of the interplay between all these components, beginning with the demand plan and ending with the impact on financial statements. You can also find a more nuanced explanation of the relationship between supply chain decisions and financial KPIs here.

I also encourage you to join the IBM Business Analytics live stream event on October 25th, to hear more case studies on how businesses have used Planning Analytics to accelerate data-driven business decision making.

Source: ibm.com

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AI Governance: Break open the black box

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation. Today, AI presents an enormous opportunity to turn data into insights and actions, to amplify human capabilities, decrease risk and increase ROI by achieving break through innovations.

While the promise of AI isn’t guaranteed and doesn’t always come easy, adoption is no longer a choice. It is an imperative.

Those businesses that decide to adopt AI technology will have an immense advantage, according to 72% of decision-makers. Furthermore, 59% of executives claim AI can improve the use of big data in their organizations, facts about artificial intelligence show. (IBM Global AI Adoption Index 2022.)

What is stopping AI adoption today?

3 main reasons why organizations struggle with adopting AI

1. Lack of confidence to operationalize AI

Many organizations struggle when adopting AI. This is due to:

◉ An inability to access the right data

◉ Manual processes that introduce risk and make it hard to scale

◉ Multiple unsupported tools for building and deploying models

◉ Platforms and practices not optimized for AI

“According to Gartner 54% of models are stuck in pre-production because there is not an automated process to manage these pipelines and there is a need to ensure the AI models can be trusted.” (Gartner AI in organizations survey.)

Well-planned and executed AI requires reliable data backed by transparent, automated tools and explainable processes. Success in delivering scalable enterprise AI necessitates the use of AI tools and processes that are specifically made for building, deploying, monitoring and retraining models.

2. Challenges around managing risk

Customers, employees and shareholders expect organizations to use AI responsibly, and government entities are demanding it. This is critical now, as more and more share concerns about brand reputation with their use of AI. No one wants to be in the news for the wrong reasons. Increasingly we are also seeing companies making social and ethical responsibility a key strategic imperative.

3. Scaling with growing AI regulations

With the growing number of AI regulations, responsibly implementing and scaling AI is a growing challenge, especially for global entities governed by diverse requirements and highly regulated industries such as financial services, healthcare and telecom. Failure to meet regulations can lead to government intervention in the form of regulatory audits or fines, damage to the organization’s reputation with shareholders and customers, and revenue loss.

The solution: AI Governance

AI governance is an overarching framework that uses a set of automated processes, methodologies and tools to manage an organization’s use of AI. Consistent principles guiding the design, development, deployment and monitoring of models are critical in driving responsible, trustworthy AI. These principles include:

◉ Know your model: Model transparency starts with the automatic capture of information on how the model was developed and deployed. This includes capturing of the metadata, tracking provenance and documenting the model lifecycle. Model transparency promotes explainable AI driving trusted results that build public confidence, promote safer practices and facilitate further AI adoption.

◉ Trust your model: Complying with rules, regulations and driving AI that minimizes bias requires well defined and automatically enforced enterprise policies, standards and roles. Manual manipulation of data and models can introduce costly errors with far-reaching consequences. In addition, the automation of enforcement rules for validation drives model retraining and reliability to address drift now and over time.

◉ Use your model: Transparent and explainable AI requires the automation of the analysis of model performance against KPIs while continuously monitoring in real-time for bias, fairness and accuracy. The ability to track and share model facts and documentation across the organization provides backup for analytic decisions. Having this backup is crucial when addressing stakeholder, customers and concerns from regulators.

At IBM, we believe AI governance is the responsibility of every organization, and will help businesses build more trustworthy AI that is transparent, explainable, fair, robust and respecting of individual privacy. Responsible AI requires upfront planning, automated systems and the governance necessary to drive fair, accurate, transparent and explainable results.

The three foundational capabilities of the IBM AI Governance solution

IBM AI Governance is a new one-stop solution built on IBM Cloud Pak for Data. It is designed to help businesses meet their regulatory requirements and address ethical concerns through software automation. It drives a complete governance solution without the excessive costs of switching from your current data science platform.

Everything needed to develop a consistent transparent model management process is included in IBM AI Governance. This includes repeatability and the ability to capture of model development time, metadata, post-deployment model monitoring, and to customize workflows. IBM AI Governance is built on three critical principles, meeting the needs of your organization at any step in their AI journey:

1. Lifecycle Governance: Monitor, catalog and govern AI models from anywhere and throughout the AI lifecycle

◉ Automates the capture of model metadata across the AI/ML lifecycle to enable data science leaders and model validators to always have an accurate, up-to-date view of their models. Lifecycle governance enables the business to operate and automate AI at scale to ensure that the outcomes are transparent, explainable and devoid of harmful bias and drift. This increases the accuracy of predictions by identifying how AI is used and where corrective action is indicated.

2. Risk Management: Manage risk and compliance to business standards, through automated facts and workflow management

◉ Model risk management is used to identify, manage, monitor and report on risk and compliance initiatives at scale. Dynamic dashboards provide clear, concise customizable results that enable a robust set of workflows, enhanced collaboration and helps to drive business compliance across multiple regions and geographies.

3. Regulatory Compliance: Help to proactively ensure compliance with current and future regulations

◉ Translate external AI regulations into a set of policies for various stakeholders that can be automatically enforced to ensure compliance. Users can manage models through a dynamic dashboard and that tracks compliance status across all policies and regulations.

Source: ibm.com

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Don’t rebuild your SWIFT connectivity on cloud

Banks and businesses worldwide have embarked on a modernization journey, trying to re-imagine their systems and get ready for the world of tomorrow. While each institution faces different challenges, all are seeking common goals: new and improved channel experiences, integrated new technologies, cost management and cost takeout, improved risk management and security, reduced down-time, and operational efficiency. These goals are aimed to set the foundation for growth and agility and ultimately a better client experience.

To support this journey, most banks and businesses have announced a cloud adoption strategy. They see that the success of their transformation strategies is inextricably linked to moving to a cloud model for the flexibility, agility, resilience and time-to-market acceleration it offers. As the race to cloud adoption continues, now is the time to stop and evaluate the many options available to achieve your goals. Can you securely interoperate with ecosystem partners and networks? Can you automate to mitigate compliance risk? Are your systems designed with zero trust in mind? Are your in-house resources optimized for high-value work or burdened by increasing operational demands?

Cloud adoption has become mainstream. With its proven benefits, executives in every industry are investing and demanding that their physical infrastructure is moved to cloud, pressuring their teams to deliver mass migration to cloud while losing sight of their real objectives. Increasingly, we see businesses “lift and shift” their systems, recreating the same issues in a new environment and gaining nothing but the bragging rights of a “cloud infrastructure.”

Cloud adoption is a tool to achieve your goals, it should never be the goal. 

Should you rebuild your SWIFT connectivity on public cloud?

Of the critical components in banking and payments infrastructure, SWIFT provides the key core network for domestic and international financial messaging. It is the backbone on which the global economy is built. Maintaining connectivity to SWIFT is critical and any unplanned downtime of exclusion from the network harsh economic impacts. Recently, SWIFT has broadened access to its 11,000 member bank and corporate network with public cloud connectivity provided they comply with SWIFT Customer Security Program (CSP) requirements and abide by the application installation and configuration guidelines. SWIFT hardware components need to continue to be deployed on-premises or in colocation facilities to establish and maintain connectivity.

Modernize your payments with the IBM Payments Center

This sure smells like a “rebuild your SWIFT connectivity ’as-is’ on public cloud.” So what do you gain? You still have to build and configure your infrastructure. You’re still responsible to maintain the infrastructure and apply upgrades. You still have a physical footprint to manage. You still have to build or retain the skills and resources to support a SWIFT infrastructure and the responsibility to comply with mandatory controls. This is not cheaper, better or faster. Instead, consider shifting from a “build and maintain” model to a “subscribe and accelerate” model that integrates a value-added, SWIFT-certified service bureau and a purpose-built cloud for financial services.

Imagine a model where your SWIFT infrastructure is hosted on a public cloud specifically designed to comply with financial services standards, fully maintained and managed by a team of SWIFT experts you can leverage at any time. You could connect to a worldwide network of fully redundant SWIFT gateways, guaranteeing the availability of your connectivity while completely eliminating the hassle of managing it. Sound too good to be true? This is achievable, but it requires a partner with the end-to-end capabilities and expertise to meet the complexities of the challenge.

So what’s the primary consideration if you are moving your SWIFT infrastructure to cloud? It all boils down to one question: “What value am I looking to gain from this initiative?”

The reality of a SWIFT infrastructure is that it requires a physical footprint to host hardware components. A migration to cloud will likely require you to maintain some components on premises or deploy them in a new colocation facility, thereby increasing operational complexity. Leveraging managed services, at least for key components of the infrastructure, will drastically reduce cost and risk.

Furthermore, although hyperscalers have accelerators and tools to help build the infrastructure, you are still responsible to deploy, configure, integrate, maintain and update your infrastructure. This requires you to develop and maintain highly sought-after skills and resources. Finding the right partner who can manage your SWIFT infrastructure will allow you to leverage a pool of specialized resources available on demand. These resources will support you through the implementation and run phases of your deployment. This team will also be available to recommend innovations and support you in future initiatives to adopt new SWIFT capabilities (gpi features, APIs, other messaging options, etc.) or to comply with future mandates.

Finally, complying with SWIFT Customer Security Program (CSP) controls is mandatory, and SWIFT’s multiple architecture models provide you options and flexibility to minimize the number and complexity of in-scope components. Leveraging API integrations or outsourcing certain components to a SWIFT Certified Service Bureau will enable you to simplify your annual assessment and transfer much of the responsibility to your partner.

Selecting the right cloud provider should enable you to go beyond the SWIFT mandates. When a cloud is designed for financial services, it addresses the complex operational, cyber, regulatory and technical risks that are unique to the industry. Only a cloud that addresses these risks can truly meet the needs for cyber resiliency, operational resiliency and operational efficiency.

For a cloud provider to stay abreast of complex regulations governing financial services industry adoption of cloud, it must join forces with leading financial institutions and industry regulatory partners to define and establish a security controls framework. It must then integrate these controls comprehensively into its IaaS and PaaS services and offer industry leading security capabilities and best-in-class encryptions to protect the most sensitive financial data. Such a cloud dedicated for financial services is designed to accelerate migration of most sensitive workloads in a highly regulated industry while reducing the risk, cost and time required for such transformation.

The migration of your SWIFT infrastructure to cloud may seem like a complex program to undertake. Fortunately, it doesn’t have to be an all-or-nothing approach. There are great gains to be made through a phased and strategic approach.

Think of the options that allow you to address your biggest pain points while minimizing the amount of investment: You can simply migrate your DR and keep your production environments intact. You can keep your messaging interface on prem while outsourcing your gateways and connectivity. You can maintain your environment as-is but deploy a third redundancy site on cloud. There are many other options you can consider that will drive value without a large cloud migration.

The right partner can help you not only assess options but think through and execute against the right combination of operating model, technology and skills needed to realize results in this dynamic environment.

Source: ibm.com

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