Thursday, 6 October 2022

IBM

Reflections on an impactful partnership with Celonis: Consultants share insights on value creation with process mining

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Strong partnerships are key to helping clients improve operations and boost productivity across their enterprises. A year ago, IBM Consulting and Celonis joined forces to embed the execution management system capabilities of Celonis at the core of IBM Consulting’s finance transformation business. Since the inception of the partnership, IBM has delivered greater flexibility and choice in how its clients deploy workflow intelligence technology, and it’s changing the way value is delivered to clients.

This partnership is critical for both companies. IBM Consulting has set the agenda for data-driven consulting and moved clients to value faster by embedding Celonis into business transformation workstreams. For Celonis, IBM Consulting introduces their platform’s process mining, automation and execution management capabilities to its customers. IBM and Celonis have also developed industry-specific applications for multiple use cases including supply chain, procurement and accounts payable and receivable.


IBM initially set out to certify 2,000 consultants on Celonis and hit that mark ahead of schedule. Since the inception of the partnership, the companies have made great strides. Several consultants shared insights and reflected on the outcomes of this partnership.

Scott Kim, a Category Manager for IBM Consulting, said “Celonis has given clients an opportunity to fix problems they never knew existed. Process innovation provides such an improvement opportunity, and the data gives you a lot of ideas for initiatives and developing KPIs.”

Kristina Dreher, Associate Consultant at IBM, has focused on being a process mining consultant for the last 18 months. When Dreher initially worked with a client using legacy systems, she had to map out processes and discover opportunities without the capabilities of Celonis. “After a couple of months, I knew there was a better way,” she said. “With the data provided by Celonis, it’s unbiased. One of the issues I had was that every time we tried to get a process locked, there would be a new idea, changed minds and the client was unsure how the process would run.”

Dreher added that Celonis enables IBM consultants to show processes based on data. “When you can show them with data and not words, minds are more open,” said Dreher. “I prefer to tell story based on data, not general ideas.” With a data-driven approach, Dreher said she can start with a workshop to outline goals based on data: “If all goes well, I receive the data quickly or connect to core systems and quickly get something visual in Celonis for the client.”

Clients may need time to process and understand what they are seeing, but typically they become curious and look for deep dives into processes. Dreher’s advice: “Be curious about processes and the underlying data as well as the full value chain. You can connect dots from different departments, analyze them together and drive real improvements. Think big and don’t stop.”

Dreher’s delivery projects include IBM peers as well as Celonis experts. “We act as one team, and it feels like the family has grown,” said Dreher. “IBM and Celonis have combined forces.”

Cazzie Williams, IBM Delivery Project Executive, is a strategic-sourcing veteran who had positions at Honeywell, Electrolux, Microsoft and Whirlpool. When the IBM and Celonis partnership was announced, Williams said it was clear he “had to jump right in.”

After about two weeks of tutorials, Williams began integrating Celonis into his procurement engagements. Williams’ clients are in multiple industries. “It’s about efficiency with my clients,” said Williams. “What used to take a week or more for information gathering now takes less than 5 minutes.”

For instance, if a client is trying to find out why suppliers aren’t getting paid, Celonis can show the purchase order process, show how to fix it and then deploy a solution. Williams said his Celonis usage has ramped from a bi-weekly check of client processes to looking at the data every other day.

Much of Williams’ personal efficiency from Celonis is on the front end of an engagement. “You can bring data in with data models and say, ‘Here are the gaps, here’s what’s good and here are the opportunities,’” said Williams.

Compared to manual process mapping and discovery approaches, Celonis has cut the time to make recommendations in half. Data-driven consulting with the help of Celonis means that IBM can do more with less and focus on high priority projects ranked by value.

“The future of consulting is having readily available information to tell a story and drive a direction much faster,” said Williams.

Williams’ advice for veteran consultants looking to better serve their clients: “You can build a culture and create a community around Celonis usage where everyone helps each other. Process mining will be part of the culture if you create the environment.”

Oliver Wilhelm, Associate Consultant, joined IBM Consulting with an automotive background and a strong interest in improving processes leveraging technology.  Wilhelm discovered Celonis and shares, “I started with classical process mapping to discover improvement potential. Two years ago, I started working with Celonis as its data-based view on processes that provides an objective perspective on processes while identifying automation potentials.”

Wilhelm added that Celonis enables him to assess process KPIs before he even talks to the client in workshops. “It speeds up the process a lot when you have a first session with the business and hand over a list of calculated opportunities backed up by actual process data,” he said.

According to Wilhelm, Celonis is running in every project he has across industrial and automotive clients. Since the IBM Celonis partnership launched, Wilhelm said he has seen strong technical support from Celonis colleagues. “We have a personal connection and knowledge exchange,” said Wilhelm. That relationship makes it easier to customize as needed for clients.

Wilhelm said his projects have been a mix of clients that already use Celonis and ones where the technology is new. “When Celonis is new to the engagement, we can showcase some simple things, ask more precise questions and calculate benefits,” he said. “Where Celonis has been implemented, we can begin talking about a global strategy and rollout.” The resources IBM brings can help clients understand the process, compare it with industry benchmarks and implement appropriate process improvements.

Another perk of working with Celonis is that Wilhelm can hone his technical skills since he likes working with numbers and code. He added that he has an interest in both SQL and the Celonis PQL, as well as IT system migration projects.

The goal for Wilhelm is to move clients more into automation and action flows via the Celonis Execution Management System (EMS) as they expand beyond process mining and discovery.

Wilhelm’s advice: “There will be a time when every company has process mining in place. There’s high potential for personal development and your career if you can always point back to numbers and very clear measurements.”

IBM has over a dozen applications available in the Celonis Marketplace for users to explore, including those covering functional areas such as procurement, record to report, supply chain, and customer and IT services. Many of these apps have been specifically designed for key industries including banking, insurance, industrial, engineering and more.

Moreover, IBM Garage Jumpstart sessions with Celonis EMS offer many of our clients a great starting point for process exploration — and we’re finding that our consultants can accelerate time to value realization through these engagements too. “The exploration process with Celonis EMS gives our consultants new capabilities and in turn, they’re identifying cost-reductions for a wide array of enterprise clients that are much needed,” comments Juan Jimenez, Partner Marketing, IBM and Celonis.

“In today’s unstable economic environment, every opportunity to improve the bottom-line matters. IBM and Celonis share a common vision around the power of intelligent workflows, and we take a systematic approach to uncover hidden inefficiencies — so that we can help our customers reduce costs,” added Juan.

Even the most mature organizations can lack the tools and experience to look beyond blind spots. To ensure clients are well served, surround them with practitioners that can operate in partnership across their specific domain and know how to orchestrate it all.

Source: ibm.com

Tuesday, 4 October 2022

Turning insights into actions with IBM Business Analytics

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We are living in the age of the unexpected. The pandemic, regulatory changes, economic questions, and human resource and supply chain challenges are just some of the disruptions that have impacted organizations. Disruptions will continue to surface unexpectedly, leaving broad and lasting impacts on organizations and their ecosystems. The result is an increased pressure to make smart decisions faster and often against a moving target.

Most organizations are now understanding the value of making decisions based on data insights rather than experience or intuition alone. However, the organizations that will navigate the unexpected successfully and win will do more than make data-driven decisions. These organizations will focus on how insights are framed, created, marketed, consumed and stored for reuse.

That’s where business analytics comes in.

What is IBM Business Analytics?


IBM is helping clients successfully navigate the age of the unexpected with IBM Business Analytics, an enterprise-grade, trusted, scalable and integrated analytics solution portfolio. It streamlines and extends enterprise reporting, self-service analysis and planning strategies across the organization to empower teams to better predict and shape future outcomes.

With the new IBM Business Analytics Enterprise, we are bundling together Planning Analytics with Watson, Cognos Analytics with Watson and the new Analytics Content Hub. This enables a single point of entry for planning, budgeting, forecasting, dashboarding and reporting. Now you aren’t just breaking down departmental and data silos, but analytic silos, too.

The capabilities of bundled business analytics


Planning Analytics with Watson addresses integrated business planning in extended planning and analysis (xP&A) including FP&A, HR, S&OP, Marketing, Project/IT planning and more. It’s the only planning analytics solution on the market that excels in all areas of continuous, integrated, predictive and prescriptive planning.

Next, IBM Cognos Analytics with Watson is a trusted AI co-pilot for business decision-makers who want to improve the impact of their business function by empowering every user to turn data into insights, and rapidly make business decisions. IBM is the only partner that can plan at the speed of your business and for the integrity of your environment, increasing accuracy and consistency with AI and prescriptive analytics capabilities you can trust.

And last but certainly not least, we’ll showcase the new IBM Analytics Content Hub in Business Analytics Enterprise, which is designed to break down organizational analytic silos and help you deliver all your analytics capabilities to your teams.

The benefits of business analytics


Most recently, review site G2 named Planning Analytics a “Leader” in their Fall 2022 report and Cognos Analytics a “Top 50 Analytics and AI” product for 2022. TrustRadius awarded both Planning Analytics and Cognos Analytics a “Top Rated” designation. Over the last couple years, a range of companies shared their feedback, leading to many of the improvements in the user experience, AI innovations and deployment options available today.

Organizations use analytics and AI to enhance decision-making that drives competitive advantage. Consider food packaging leader Novolex, who had to adapt their planning cycles during the COVID-19 pandemic. As shared in the case study, Violeta Nedelcu, Supply Chain Director at Novolex states, “Instead of taking weeks, the company can now process data within a few hours, taking two days for analysis, discussion and review, and provide clarity on the available capacity to proceed with new products and to support the current market.” Overall, Novolex was able to see a 83% reduction in forecasting processing times.

With business analytics, organizations in all industries, can experience the power of faster, better planning and analysis with data-driven precision. We look to continue helping organizations achieve successful implementations across their analytics cycle. As such, we have exciting new updates to our business analytics solution portfolio coming in the next month.

Register today for our Business Analytics launch event on October 25th to hear about the new Business Analytics Enterprise, including new deployment options and capabilities. You don’t want to miss out!

Source: ibm.com

Saturday, 1 October 2022

ESPN, IBM Consulting and the power of data-driven decision making in fantasy football

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Fantasy football has been around since the 1960s, when a part-owner of a professional football team gathered with friends to “draft” athletes into fantasy leagues and accrue points based on the actual performance of those players in their real-life games. It was an early effort to gamify the experience, have fun with friends, and increase interest in the football season.

It worked. Today, fantasy sports aren’t just fun and games; they’re an $8.8 billion-dollar business. An estimated 45 million Americans play fantasy football, dedicating nearly seven hours a week to researching players and managing their rosters throughout the season. And ESPN is the undisputed champion of the fantasy football platforms, with a record 11 million players managing more than 17 million teams.


“We want ESPN to be the destination for all fans playing Fantasy Football, whether it’s their first time or they’ve been managing a league for 20 years.,” said Chris Jason, Executive Director, Product Management at ESPN. “To meet that bar, we have to continuously improve the game and find ways to enhance the experience with new innovations.”

To keep that constant innovation moving, ESPN has been working closely with IBM Consulting over the last six years, designing, developing and delivering new features that enhance the user experience. In particular, ESPN is eager to develop ways to serve up insights that help fantasy players make great roster decisions.

“Football produces a massive amount of data,” says Stephen Hammer, Sports CTO, distinguished engineer, ES&iX, IBM Consulting. “There are 1,900 players in the league. Every time they take the field, they produce a whole series of data. And that’s just the structured data. Millions of blogs, articles, and podcasts about football are produced every season. And those contain important insights as well.”

To get a handle on all this data, ESPN worked closely with IBM Consulting to visualize the kinds of features and insights end users were looking for. They used IBM Design Thinking to understand the different personas of fantasy football players and map out the various user journeys they undertake. And they worked in the IBM Garage model, a proven methodology for co-creation that accelerates the innovation process.

The teams co-created two solutions, Player Insights with Watson and Trade Analyzer with Watson.

Player Insights combine analysis of structured data like scores and statistics, with AI-powered analysis of media commentary using Watson Discovery. This results in comprehensive and user-friendly insights designed to help fantasy managers understand a player’s boom or bust chances, or to assess how injuries will affect their lineup.

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Trade Analyzer with Watson uses those same analyses to evaluate potential trades between fantasy managers. When one fantasy manager proposes a trade, Trade Analyzer examines the strengths and weaknesses of their team and shows which positions the manager needs to fill to make their team stronger.

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In just the first week of the 2022 season, more than 6 million trades were proposed on ESPN’s platform. And last year alone, IBM served up more than 34 billion AI-powered insights through the ESPN fantasy app.

“This is the same technology we’re using to help clients transform data into insight in every industry,” says Hammer. “Whether it’s fantasy football or financial services, it’s all about data-driven decision making.”

Source: ibm.com

Thursday, 29 September 2022

From principles to actions: building a holistic approach to AI governance


Today AI permeates every aspect of business function. Whether it be financial services, employee hiring, customer service management or healthcare administration, AI is increasingly powering critical workflows across all industries.

But with greater AI adoption comes greater challenges. In the marketplace we have seen numerous missteps involving inaccurate outcomes, unfair recommendations, and other unwanted consequences. This has created concerns among both private and public organizations as to whether AI is being used responsibly. Add navigating complex compliance regulations and standards to the mix, and the need for a solid and trustworthy AI strategy becomes clear.

To scale use of AI in a responsible manner requires AI governance, the process of defining policies and establishing accountability throughout the AI lifecycle. This in turn requires an AI ethics policy, as only by embedding ethical principles into AI applications and processes can we build systems based on trust.

IBM Research has been developing trustworthy AI tools since 2012. When IBM launched its AI Ethics Board in 2018, AI ethics was not a hot topic in the press, nor was it top-of-mind among business leaders. But as AI has become essential, touching on so many aspects of daily life, the interest in AI ethics has grown exponentially.

In a 2021 study by the IBM Institute of Business Value, nearly 75% of executives ranked AI ethics as important, a jump from less than 50% in 2018. What’s more, suggests the study, those organizations who implement a broad AI ethics strategy, interwoven throughout business units, may have a competitive advantage moving forward.

The principles of AI ethics


At IBM we believe building trustworthy AI requires a multidisciplinary, multidimensional approach based on the following three ethical principles:

1. The purpose of AI is to augment human intelligence, not replace it.

At IBM, we believe AI should be designed and built to enhance and extend human capability and potential.

2. Data and insights belong to their creator.

IBM clients’ data is their data, and their insights are their insights. We believe that data policies should be fair and equitable and prioritize openness.

3. Technology must be transparent and explainable.

Companies must be clear about who trains their AI systems, what data was used in training and, most importantly, what went into their algorithms’ recommendations.

When thinking about what it takes to really earn trust in decisions made by AI, leaders should ask themselves five human-centric questions: Is it easy to understand? Is it fair? Did anyone tamper with it? Is it accountable? Does it safeguard data? These questions translate into five fundamental principles for trustworthy AI: fairness, robustness, privacy, explainability and transparency.

AI governance: From principles to actions


When discussing AI governance, it’s important to be conscious of two distinct aspects coming together:

Organizational AI governance encompasses deciding and driving AI strategy for an organization. This includes establishing AI policies for the organization based on AI principles, regulations and laws.

AI model governance introduces technology to implement guardrails at each stage of the AI/ML lifecycle. This includes data collection, instrumenting processes and transparent reporting to make needed information available for all the stakeholders.

Often, organizations looking for trustworthy solutions in the form of AI governance require guidance on one or both of these fronts.

Scaling trustworthy AI


Recently an American multinational financial institution came to IBM with several challenges, including deploying machine learning models in the hundreds that were built using multiple data science stacks comprised of open source and third-party tools. The chief data officer saw that it was essential for the company to have a holistic framework, which would work with the models built across the company, using all these diverse tools.

In this case IBM Expert Labs collaborated with the financial institution to create a technology-led solution using IBM Cloud Pak for Data. The result was an AI governance hub built at enterprise scale, which allows the CDO to track and govern hundreds of AI models for compliance across the bank, irrespective of the machine learning tools used.

Sometimes an organization’s need is more tied to organizational AI governance. For instance, a multinational healthcare organization wanted to expand an AI model that was being used to infer technical skills to now infer soft/foundational skills. The company brought in members of IBM Consulting to train the organization’s team of data scientists on how to use frameworks for systemic empathy, well before code is written, to consider intent and safeguard rails for models.

After the success of this session, the client saw the need for broader AI governance. With help from IBM Consulting, the company established its first AI ethics board, a center of excellence and an AI literacy program.

In many instances, enterprise-level organizations need a hybrid approach to AI governance. Recently a French banking group was faced with new compliance measures. The company did not have enough organizational processes and automated AI model monitoring in place to address AI governance at scale. The team also wanted to establish a culture to responsibly curate AI. They needed both an organizational AI governance and AI model governance solution.

IBM Consulting worked with the client to establish a set of AI principles and an ethics board to address the many upcoming regulations. This effort ran together with IBM Expert Labs services that implemented the technical solution components, such as an enterprise AI workflow, monitors for bias, performance and drift, and generating fact sheets for the AI models to promote transparency across the broader organization.

Establishing both organizational and AI model governance to operationalize AI ethics requires a holistic approach. IBM offers unique, industry-leading capabilities for your AI governance journey:

◉ Expert Labs for a technology solution that provides guardrails across all stages of the AI lifecycle
IBM Consulting for a holistic approach to socio-technological challenges

Source: ibm.com

Tuesday, 27 September 2022

Is your conversational AI setting the right tone?

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Conversational AI is too artificial


Nothing is more frustrating than calling a customer support line to be greeted by a monotone, robotic, automated voice. The voice on the other end of the phone is taking painfully long to read you the menu options. You’re two seconds away from either hanging up, screaming “representative” into the phone, or pounding on the zero button until you reach a human agent. That’s the problem with many IVR solutions today. Conversational AI is too artificial. Customers feel they’re not being heard or listened to, so they just want to speak with a human agent.

IBM Watson Expressive Voices 


Luckily, there is a way to fix that problem and make the customer experience more pleasant. With IBM Watson’s newest technology of expressive voices, you will no longer feel like you’re talking to a typical robot; you’ll feel like you’re talking to a live human agent without any of the wait time. These highly natural voices have conversational capabilities like expressive styles, emotions, word emphasis and interjections. Not only do these voices relieve the customer frustration of feeling like they’re talking to a bot, but they also contribute to the goal of call deflection from human agents. It’s a win-win for customers and businesses.


Best suited for the customer care domain, the voices will have a conversational style enabled by default; however, the voices also support a neutral style which may be optimal for other use cases (newscasting, e-learning, audio books, etc.). Have a listen to the expressive voice samples below:


Emotions, Emphasis, Interjections


As humans, we convey emotion in the words we speak, whether we realize it or not. We tend to sound empathetic when apologizing to one another. We sound uncertain when we don’t know the answer to something, and perhaps cheerful when we finally discover the answer. The ability to convey emotion is what makes us human. IBM Watson’s expressive voices can express emotion in order to better convey the meaning behind the words, ultimately reducing customer frustration when dealing with today’s phone experiences. Your voice bot will sound empathetic when telling the customer their package is delayed or cheerful when they’ve successfully helped the customer book an airline ticket.

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Emphasis is another important aspect of human speech. Did you say Austin or August? Did you say you lost the card ending in 4876? IBM expressive voices support word emphasis so that your bot can better convey the desired meaning of the text. Users can indicate the location of the stress with four levels – none, moderate, strong, and reduced.

Interjecting with words like hmm, um, oh, aha, or huh is another feature of human speech that IBM expressive voices now support to enable an interaction that feels more natural and human-like. The new expressive voices will automatically detect these interjections in text and treat them as such without any SSML (Speech Synthesis Markup Language) indication. There’s an also an option to disable the interjections when it’s not appropriate (e.g., ‘oh’ can be used to spell out the number 0 or as an interjection).

How to Get Started with Expressive Voices


Expressive voices and features will be available in US-English first in September 2022, followed by other languages in early 2023. The US-English expressive voices are Michael, Allison, Lisa, and Emma. For customers using the V3 version of Michael, Allison, or Lisa, switching to the expressive voices shouldn’t cause disruption as it will still sound like the same speaker, but with a more natural and conversational style. It’s easy to start using the new voices – simply indicate the voice name in the API reference, just like any other voice.

In summary, IBM’s new technology of expressive voices is the next level of conversational AI. It checks the box when it comes to an engaging and natural experience that mirrors that of a human agent. The new voices relieve the customer frustration of feeling unheard and drive call deflection from human agents.

Source: ibm.com

Saturday, 24 September 2022

A modern cloud data platform is the foundation of all intelligent supply chains

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In a world where disruptions and complications are inevitable, strong supply chains are more essential than ever before. As highlighted in the new thought leadership paper “Building intelligent, resilient and sustainable supply chains,” the necessary transformation improvements are not just a question of manufacturing, logistics or transportation. They’re fundamentally a question of timely and accurate data, both from inside the enterprise and from the ecosystem of supply chain partners. For years, enterprise supply chains have rested on the shaky foundations of disconnected, unverifiable and untimely data. When things go wrong, enterprises turn to war rooms with often aged data and competing sources of truth. This approach results in too much executive energy seeking to understand where the business is, and not enough time spent on the forward-looking decisions essential to driving the business.

The transformative results of a digital twin+ unlock significant value, including a 5%–10% decrease in product wasted.

Even when supply chain transformation initiatives consider the implications of data, they often do it too late in the process, as a hygiene issue. This limits improvements to the realm of visibility, rather than surfacing actionable insights, making it harder to achieve operational success and realize value. Every high-performing supply chain is only as good as the data that fuels it. If you want to transform supply chains, you must internalize this truth before you start. Clean, connected data will be the foundation of next-generation supply chain operations. Additionally, if you want accurate and timely data, you need to collaborate across enterprise boundaries. With the right data foundation, you’ll be empowered to build better capabilities, such as capturing real time changes in demand signals, proactively identifying exceptions in orders and deliveries, and dynamically adjusting the business to avoid emergencies and escalations.

To put data at the heart of transformed supply chains, organizations need to take three key strategic actions:

1. Create a unified data fabric as the foundation to exchange supply chain data


In today’s data-rich world, data inherently lives in silos and is not harmonized to easily drive insights and actions. For example, much of the data that supply chain analysts use lives outside of ERP systems in quality systems, manufacturing execution systems (MES) and warehouse management systems (WMS). But you can enable easy data exchange by using the cloud to create a data fabric that instantiates a common data model across the enterprise. Cloud-based data fabrics enable the consumption and publishing of core data through services and APIs. In turn, these support downstream and collaboration tools to visualize data while applying intelligence to workflows and processing.

Beyond these performance improvements, the new data foundation means that supply chains can offer completely new capabilities that support better business models. For example, you can build insight-driven relationships with customers and deliver products “as a service.” IBM Systems does this by supporting long-term engagement with hardware customers. Based on usage data, support professionals can predict when new hardware might be needed and respond more quickly to service interruptions. Many capital-intensive products are good candidates to deliver “as a service,” but only if the provider has sufficient insight to support these products throughout their lifecycle and deliver the service seamlessly.

2. Use a digital twin+ to go beyond data visibility into process orchestration


Visibility solutions and data warehouses have incrementally improved the transparency of supply chain operations, but there is a limit to how much benefit they can provide. The solution is to pair the control tower with a digital twin into a so-called “digital twin+”. This model enables intra- and inter-enterprise data-driven processes, and delivers benefits such as improved accuracy in demand signals and early warning on supply chain disruptions or transportation delays. The result is a platform that thinks, listens, learns and acts, while establishing transparency and trust in the process. The transformative results of a digital twin+ unlock significant value, such as ~1%–3% of cost of goods sold (COGS), 5%–10% decrease in product wasted, and increased speed to market. (Representative results based on IBM Consulting supply chain engagements.)

A digital twin+ leverages the right technologies for each business driver, such as:

◉ Internet of things (IoT) for quality, geolocation and asset performance data

◉ Machine learning and artificial intelligence (ML/AI) for advanced forecasting, dispute resolution and disruption management

◉ API/service to stand up a flexible, componentized architecture

These technologies leverage the rich data from the entire ecosystem to drive insights and processes across the value chain.

3. Use a case-based approach to adopt specific components and score quick wins


Although it’s essential to have an overarching vision for your supply chain transformation and do the work of building a data foundation, don’t overlook the potential for that data to deliver quick ROI in well-defined areas. For example, you can deploy technology accelerators to focus on targeted outcomes:

◉ Leverage IoT and sensor data to improve asset utilization and minimize downtime

◉ Infuse AI/ML to increase the efficiency of operational processes such as purchase order creations, safety stock, and reorder points

◉ Identify and correct master data anomalies that create repetitive supply chain disruptions

Taking a pragmatic approach to solving supply chain disruptions and infusing innovation into the process can drive significant business outcomes. As an example of how these efforts can add up, consider how IBM Consulting recently helped IBM Systems transform the global supply chain that supported their USD 10 billion server business.

◉ Mitigating disruptions in days instead of hours

◉ Resolving persistent supply chain challenges 95% more efficiently

◉ Cutting supply chain structural costs by 10%

To see more about how clean, connected data is the foundation for transformative supply chains, read the new thought leadership paper “Building intelligent, resilient and sustainable supply chains” today.

Source: ibm.com

Friday, 23 September 2022

Eli Manning and the power of AI in ESPN fantasy football

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Eli Manning was the obvious choice. For the last six years, IBM has been working with ESPN to infuse AI-generated insights into their fantasy football platform. But we needed someone who could help us tell the story; someone who could grab the attention of fantasy football enthusiasts, introduce them to the artificial intelligence of Watson, and encourage them to embrace the era of data-driven decision making. (check out Eli’s visit to IBM Research here)

Why Eli? No, it’s not because I’ve been a New York Giants fan my whole life. And no, it’s not because the Giants and IBM are both nicknamed “Big Blue.” While neither of those things hurt, we ultimately chose Eli because he has so much in common with IBM.

Let me explain. Back in 2016, IBM formed a partnership with ESPN. In this relationship, we use IBM’s advanced analytics and AI capabilities to analyze the massive amount of data produced by fantasy football. We then serve up insights that help guide the roster decisions of ESPN’s fantasy football users. Today, those insights take the form of two features:

◉ Trade Analyzer with Watson, which uses AI to analyze player statistics and media commentary to help team managers understand the value of a potential trade.
◉ Player Insights with IBM Watson, which helps fantasy managers estimate the potential upside and downside of a matchup, analyze boom or bust chances, and assess injuries.

Why is IBM in the fantasy football business? Great question. Two reasons: First, we’re solving a very real business problem for a valued partner. ESPN’s Fantasy Football may look like fun and games, but it’s also serious business. More than 11 million people play on ESPN’s fantasy platform. And it’s a critical form of digital engagement for ESPN, one that also drives consumption of related football content, both digital and broadcast. Just like IBM’s other clients, ESPN is operating in a highly competitive market, and requires constant innovation to improve the customer experience. Using AI to produce insight at scale addresses a critical need for ESPN, just as it does for IBM clients in other industries.

The second reason is more self-serving. Simply put, ESPN Fantasy Football offers IBM a powerful platform to demonstrate our capabilities to millions of people. Both Trade Analyzer and Player Insights are produced by transforming vast quantities of data into insights that inform decision making. We’re analyzing the performance statistics of all 1,900 players in the league. But the numbers don’t always tell the whole story. So we’re also using the natural language processing capability of Watson Discovery to mine insights from millions of blogs, articles and podcasts produced by media experts (see here to learn more). Last year alone Watson served up more 34 billion AI-powered insights to ESPN fantasy players.

Which brings me back to Eli. When Eli Manning joined the New York Giants back in 2004 as the number one pick in the draft, many Giants fans thought he would be the second coming of Joe Namath: a big star in the big city. But Eli was more subtle than that, more Ordinary Joe than Broadway Joe. There were no flashy fur coats and movie star girlfriends. Just an understated, workman-like grit that resulted in two championships. An understated assassin who let his actions on the field speak do all the talking.

How is this similar to IBM? Well, it’s been 17 years since IBM sold its ThinkPad business to Lenovo. That was the last time our iconic “eight-bar” logo appeared on a consumer-facing device. But despite this lack of visibility, our work has never been more consequential than it is today. It’s not flashy, but our technology and expertise support the operation of the most mission-critical systems on the planet: electrical grids, airlines, telecommunications networks, banks, government services, and many others.

Technologies like hybrid cloud and AI are powerful, complex, and often difficult for people to comprehend. They operate behind the scenes, in data centers and back offices. But they are critically important to our clients. That’s why we showcase the work of IBM Consulting through partnerships like the Masters, the US Open, and ESPN’s Fantasy Football. And that is why Eli Manning is helping us tell our story.

Source: ibm.com

Thursday, 22 September 2022

Moving beyond spreadsheets with IBM Planning Analytics

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My journey with IBM Planning Analytics started with an early morning phone call to tell me that a member of my team had died, suddenly and unexpectedly. Not only was his loss a personal tragedy, it was a tragedy for the whole organization. Our teams relied heavily on his decades of expertise to help us plan and forecast strategically for the future.

The company had been through tough times overall. An expensive enterprise resource planning (ERP) implementation meant there was no money left for other systems, and we’d been forced to run our budget process on a complicated network of 27 linked spreadsheets. Fred was the only one who knew how they worked and suddenly he wasn’t around.

If there was ever an example of key-person risk, this was it.

A world without spreadsheets 


We stumbled our way through the next budget process as best we could, until we came across IBM Planning Analytics with Watson. We could see, for the first time, a world that could exist without spreadsheets. We could see a world where people worked together on a common tool using a common approach to unite and agree on data-driven decisions for the good of the business. Better still, it was a world that didn’t rely on a single person.

But the story doesn’t end there.

Making sense of the data


Once we’d moved off the spreadsheets, we discovered the power that comes from managing data. We found countless problems with our master data, all of which had been masked through spreadsheet aggregation. We had been blissfully unaware of these challenges for years and now it was time to address them. By having full visibility of our data with IBM Planning Analytics, we could finally make sense of all our data together.

These problems were not trivial. In fact, we found examples where our product costs were materially misstated and discovered we’d been selling some products lower than what it cost to make. Through manual updates to spreadsheets, and working at a high level, errors – even seemingly blatant ones – were hiding in plain sight.

There’s little doubt in my mind that our investment in IBM Planning Analytics paid for itself several times over. Not only did we mitigate the key-person risk, which is honestly all we wanted to do, but we gained so much more. We made the organization value its data and want to put data to work for the good of the business.

Unlocking the value of data with the promise of AI


It’s often hard for leaders to see the value in analytical tools. Spreadsheets seem fine, but they’re not. They lull you into a false sense of security. Not only is the business logic linked with the spreadsheet owner, a risk on its own, but the sheer simplicity of the spreadsheet conceals the countless treasures within.

The promise of AI is tantalizing. It can provide insights that humans could never find. But realistically, can we ever hope to get there if the business still thinks in rows and columns? Our expert colleague’s untimely death was a tragedy, but we thank him every day for his legacy. I encourage business leaders that want to make a true impact on their bottom line to explore a continuous integrated planning solution like IBM Planning Analytics, which eliminates the manual work and helps to:

◉ Enable automated planning processes
◉ Encourage cross-functional collaboration
◉ Embed predictive AI capabilities for more accurate predictive forecasting

If you want to learn more, including how to create multidimensional plans, budgets and forecasts, explore interactive dashboards and reports, and discover pre-built solutions by industry or use case, you can get started today with a 30-day free trial or request a demo of IBM Planning Analytics with Watson.

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

Source: ibm.com

Tuesday, 20 September 2022

How does addressing sustainability change how businesses understand value?


International businesses are under intense pressure and expectation to adjust to sustainable development. This requires them to make sweeping changes to their business models and value propositions. Most recently, the pandemic response has given businesses a window into their level of exposure to external challenges and how innovation and bold strategic change can lead to new markets, transformed ways of working and, importantly, open pathways into new areas of growth.

As we continue to advance our concept of sustainability, businesses must reconsider and broaden their definitions of value.

Changing concept of value


Businesses and organizations have to reconsider how they create and understand value. Traditionally, companies viewed themselves as having a secure position along a value chain, providing the inputs and outputs of raw materials to produce goods to realize their role in adding to the value chain. But modern organizations up and down the ecosystem are increasingly choosing to create new concepts of business value. These new options draw together ecosystem players’ respective knowledge, skills and capabilities across the customer and partnership networks to create new opportunities.

How does being sustainable create value?


There are compelling findings from across industries that sustainability can create a very positive business outlook, but it does require a new way of understanding how businesses can create value. Incorporating sustainability into the heart of operations can support the design and creation of new products and services, improve the brand and deepen customer loyalty. It can also reduce operating costs, increase the support from financial investors, and encourage company pride and commitment among employees.

Companies have started in earnest to create new value, using such strategies as new low-carbon products like steel and meat-free dishes and a transparent supply chain across retail and fast-moving consumer goods (FMCG). Furthermore, investments in green products support the sustainability mission and create whole new pools of value.

Why haven’t more businesses made a move to sustainability?


There are many reasons why businesses are not yet sustainable or whole-heartedly on the sustainability change journey.

Here-to-date success for international businesses has revolved almost exclusively around financial results: substantial revenue, the pursuit of profit, positive returns for the shareholders, and typically focusing on quarterly progress.

The pressure to perform for company shareholders has encouraged a belief that sustainability is a cost and should be managed with a dedicated but isolated corporate social responsibility (CSR) investment. This view has been reinforced by company sustainability reporting not being integral to business unit strategic decisions and P&L business unit operations.

In addition, many sectors with powerful vested interests have deliberately questioned sustainability and climate change research and action, delaying progress across their industry.

Despite decades of campaigns for sustainable development and climate change warnings, most individuals have not altered their behavior. The “intention-action” gap remains wide open; behavior change has been slight due to embedded habits, social norms, optimism bias, a preference for near-term loss avoidance instead of future gain, or a sense of futility. Whether as leaders, customers or employees, individuals have not led the charge for sustainability, so the “intention-action” gap remains.

Sustainability and new value creation


However, there is increasing momentum across global and local organizations towards a concerted business transformation with sustainability at heart. The first movers, be they in retail, FMCG or global consulting, are demonstrating that they can create a greater pool of value for themselves by investing in and fostering the creation of value within the communities in which they operate. Social innovation can help businesses differentiate and save on costs by creating new products, enhancing productivity across the value chain and improving the whole business environment for all customers and companies.

What does this look like in practice?


Companies that are changing their business models to create shared value will be the beacons of international business and the guardians of nascent “pay it forward” momentum over the next decade.

Centering sustainability at the heart of strategic decisions, operations and culture is not just a good thing to do; it is the most astute and economically wise thing to do. That is where future value is and will be found.

IBM is looking at long-term value creation and is committed to building sustainable societies by investing in cultivating the skills of local communities. Building a talent supply chain beyond our current employees makes organizations more sustainable. We believe skills-rich communities encourage fair societies. IBM is committed to being part of the global ecosystem of talent by building sustainable skills in local and global communities. IBM has committed to training 30 million people across the globe by 2030.

Businesses can be sustainable and profitable. The key is to reconsider the definition of value by thinking about creating shared value and seeing the bigger, longer-term richer picture rather than purely the numbers.

Source: ibm.com

Monday, 19 September 2022

Extended Planning and Analysis (xP&A) in action

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Extended Planning and Analysis (xP&A), is not a new concept for IBM clients who use IBM Planning Analytics with Watson, formerly known as Cognos TM1. For the past several years, clients have embraced the need to tie operational decisions to the financial impact from both planning and analysis perspectives. For instance, a Director of Operations may want to increase production for the upcoming selling season, but they must first understand the impact on the business overall.


There are many operational considerations, from labor, staffing and production capacity — such as machinery and warehousing — to ensuring the business has the capital needed. All these factors need to be considered, and fortunately, IBM Planning Analytics with Watson has helped clients do this for years.

Financial and supply planning for a national blood service organization


A national blood service, and long-time Planning Analytics client, has started implementing a financial planning solution to better plan, forecast and analyze the cash flow needs and improve reporting to the leadership team and Board of Directors. Once the team fully understood the capabilities of Planning Analytics, they saw an opportunity to improve salary planning, a key part of the financial planning process. From that the HR team expanded the salary plan to include the components of staff planning including hiring and attrition.

Another way the team used Planning Analytics was to plan for the supplies needed for the collection of blood from donors. They created a planning application that schedules nurses and technicians who collect specimens and accounts for the supplies needed, from orange juice, bottled water, and cookies to medical supplies like tourniquets, blood bags, type testing kits and more.

As this company can attest, extending beyond the core finance function to plan for people, activities, and other areas has been part of Planning Analytics for years.

Financial and HR planning for a television production company


Another great example of Planning Analytics in action is with a television production company that, like many clients, was initially focused on financial planning. After the team had their financial planning and forecasting running well, they turned their focus on how to better-run their business. As a ‘job-shop’, where each TV program is a job, one area of focus was cost planning by job. The team created a job planning application, starting with staff planning as one of the largest cost components. Then they extended to include overhead and expense allocations, and eventually created a weekly Show Cost planning module to understand the contribution of each show to the overall production company’s results.

Supply chain planning for a global contract specialty manufacturer


A global contract specialty manufacturer, with deep expertise in manufacturing know-how, supply chain insights, and product design, uses Planning Analytics for nearly every ‘non supply chain’ use case in their organization. From financial analysis and reporting, forecasting, reserves reporting, aged accounts receivables, and treasury cash balance and forecasting to working capital, HQ allocations, local tax adjustments, and income tax in interim periods, all of these planning analytics solutions are integrated to ensure changes in one area, like cash forecasting, can be reflected in the overall working capital analysis.

No matter the industry, Planning Analytics is a continuous, integrated business planning solution that helps run some of the best companies in the world. Those who use IBM Planning Analytics with Watson understand the benefits of integrated planning that are not realized when doing ‘connected’ planning in spreadsheets or other traditional tools. If you want to learn how to create multidimensional plans, budgets and forecasts, explore interactive dashboards and reports, and discover prebuilt solutions by industry or use case, get started today with a 30-day free trial or request a demo of IBM Planning Analytics with Watson.

Source: ibm.com