How IBM and AWS are partnering to deliver the promise of AI for business

In today’s digital age where data stands as a prized asset, generative AI serves as the transformative tool to mine its potential. According to a survey by the MIT Sloan Management Review, nearly 85% of executives believe generative AI will enable their companies to obtain or sustain a competitive advantage. The global AI market is projected to grow to USD 190 billion by 2025, increasing at a compound annual growth rate (CAGR) of 36.62% from 2022, according to Markets and Markets. Businesses globally recognize the power of generative AI and are eager to harness data and AI for unmatched growth, sustainable operations, streamlining and pioneering innovation. In this quest, IBM and AWS have forged a strategic alliance, aiming to transition AI’s business potential from mere talk to tangible action.

Adopting AI in business at scale is not without its challenges, including data privacy concerns, integration complexities and the need for skilled personnel. Scaling AI in business presents unique challenges:

1. Data accessibility: Fragmented and siloed data stifle advancement. Gartner highlights that businesses lose an estimated USD 15 million annually due to inadequate data access.

2. Integration and financial constraints: Merging AI with current systems is intricate. Forrester indicates that 40% of companies face this obstacle. Concurrently, McKinsey points out high expenses limit AI integration in 23% of organizations.

3. Ethical and regulatory barriers: Upholding AI ethics is pivotal. A significant 34% of companies express concerns over fairness, with regulatory hurdles intensifying the landscape.

The AWS-IBM partnership is a symphony of strengths

The collaboration between IBM and AWS is more than just a tactical alliance; it’s a symphony of strengths. IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. AWS, on the other hand, provides robust, scalable cloud infrastructure. By combining IBM’s advanced data and AI capabilities powered by Watsonx platform with AWS’s unparalleled cloud services, the partnership aims to create an ecosystem where businesses can seamlessly integrate AI into their operations.

Real-world Business Solutions

The real value of any technology is measured by its impact on real-world problems. IBM and AWS partnership focuses on delivering solutions in areas like:

Supply chain optimization with AI-infused Planning Analytics

IBM Planning Analytics on AWS offers a powerful platform for supply chain optimization, blending IBM’s analytics expertise with AWS’s cloud capabilities. One of the largest children clothing retailer in the US utilizes this solution to streamline its complex supply chain. Real-time data analytics helps in quick decision-making, while advanced forecasting algorithms predict product demand across diverse locations. The retailer uses these insights to optimize inventory levels, reduce costs and enhance efficiency. AWS’s scalable infrastructure allows for rapid, large-scale implementation, ensuring agility and data security. Overall, this partnership enables the retailer to make data-driven decisions, improve supply chain efficiency and ultimately boost customer satisfaction, all in a secure and scalable cloud environment.

Infuses AI to transform business operations

DB2 PureScale on AWS provides a scalable and resilient database solution that’s well-suited for AI-driven applications. By taking advantage of AWS’s robust cloud infrastructure, PureScale ensures high availability and fault tolerance, critical for businesses operating around the clock. A leading insurance player in Japan leverages this technology to infuse AI into their operations. Real-time analytics on customer data — made possible by DB2’s high-speed processing on AWS — allows the company to offer personalized insurance packages. AI algorithms sift through large datasets to identify fraud risks and streamline claims processing, improving both efficiency and customer satisfaction. AWS’s secure and scalable environment ensures data integrity while providing the computational power needed for advanced analytics. Thus, DB2 PureScale on AWS equips this insurance company to innovate and make data-driven decisions rapidly, maintaining a competitive edge in a saturated market.

Modernizing data warehouse with IBM watsonx.data

Modernizing a data warehouse with IBM watsonx.data on AWS offers businesses a transformative approach to managing data across various sources and formats. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability. By migrating to watsonx.data on AWS, companies can break down data silos and enable real-time analytics, which is crucial for timely decision-making. One of largest asset management company has executed a pilot using machine learning capabilities to further allow for predictive analytics, uncovering trends and patterns that traditional methods might miss. One of the standout features for this company is its seamless integration with existing IT infrastructure, reducing both costs and the complexity of migrating from legacy systems. Whether you’re looking to streamline operations, improve customer experiences, or unlock new revenue streams, IBM watsonx.data on AWS lays the foundation for a smarter, more agile approach to data management and analytics.

As AI continues to evolve, this partnership is committed to staying ahead of the curve by continuously updating its offerings, investing in joint development and providing businesses with tools that are both cutting-edge and practical.

The IBM-AWS partnership is not just a win-win for the companies involved; it’s a win for businesses across sectors. By combining IBM’s prowess in data analytics and AI with AWS’s robust cloud infrastructure, the alliance is breaking down barriers to AI adoption, offering scalable solutions, and enabling businesses to leverage AI for tangible results.

Get ready to harness the power of AI for your business

Explore how the IBM-AWS partnership can offer you tailored solutions that drive results. Join us at AWS re:Invent 2023 from November 27 to December 1 in Las Vegas, Nevada. At booth #930, IBM will spotlight its advancements in AI, demonstrating how we assist clients to scale AI workloads using our comprehensive generative AI stack swiftly and responsibly. This event offers a firsthand look into IBM’s transformative solutions that are reshaping industries. Engage with our experts, partake in live demos, and explore tailor-made solutions for your business needs.

Source: ibm.com

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Transforming financial transparency and trust through integrated resource planning

Athabasca University (AU), Canada’s Open University, is dedicated to removing barriers that restrict access and success within university-level study and increasing equality of educational opportunities for adult learners worldwide.

To support their mission, AU defined their “Imagine” Strategy, which was a five-year plan outlining strategic priority outcomes for the institution. Underpinning the execution and ensuring alignment with their objectives required a collaborative integrated planning process.  The challenge was that the annual planning and subsequent forecasting processes were a major obstacle due to the lack of transparency and access to relevant timely information for decision-making, resulting in a lack of trust and collaboration. To fix this, Long Huynh, Director of Decision Support, was brought on board to work with the team to fulfill two objectives:

• Roll out a Finance Business Partner (FBP) Program, which focused on building a team of finance folks who could collaborate with faculty members and department heads on financial/business plans, transforming finance into advisors to the business as opposed to compilers and producers of reports.
• Streamline the integrated planning and forecasting process, making it easy for users to access information, track variances in spend and initiatives and enable faculty members to re-forecast and ultimately own their numbers.

To assist with this transformation, AU began working with us at ActionKPI—a Performance Management Consultancy specializing in integrated resource planning—to help define a roadmap and phased approach to re-architecting their planning processes and systems. The result was increased trust and collaboration from all faculties and departments while increasing the speed and agility of the financial reporting, budgeting and forecasting processes.  

Challenges faced

◉ Lack of transparency: The data for financial reporting was nested within different platforms with different levels of access. Budget owners struggled to understand their budgets and had difficulty accessing relevant information, understanding variances throughout the month and leading up to the quarter.

◉ Manual and siloed budgeting: The budgeting process relied on an antiquated system that was not user-friendly and disconnected from the main ERP system. Budgets had to be manually uploaded, making it challenging to integrate actuals and forecasts.

◉ Limited access to data: Some data—such as HR and payroll—was difficult to access, hindering financial analysis and decision-making. They were not able to get insights into labour costs and make accurate budgets and forecasts on one of their major cost centres.

Before implementing the solution, the financial data was scattered across different platforms with varying levels of access. Budget owners couldn’t easily access their budget information, which caused them to rely on specific individuals to explain reports due to siloed data and complex nuances.

Additionally, Athabasca University’s budgeting process was hindered by an unintuitive system that operated independently from their ERP system, Banner. Manual uploads and a lack of integration between their old system and Banner added to the complexity and time-consuming nature of the budgeting process.

The journey begins: Improved budget visibility

After initial discussions with ActionKPI, Long Huynh and the finance team saw the opportunity to demonstrate the power of integrated resource planning through IBM Planning Analytics (PA).

The focus at the start was on developing a variance and forecasting model within PA that combined budget and actual data from source systems in a user-friendly solution accessible to various stakeholders across the university. Unlike their old system, PA enabled daily automatic uploads from their ERP and provided timely access to different reporting hierarchies and variances, and it gave the ability to drill down on transactional data. Budget owners could log in and view their budgets at any time, clearly understanding their financial position and empowering them to actively participate in the budgeting process and take corrective action to meet targets. This improvement significantly enhanced transparency, trust and accountability among their various budget owners. 

“It was such a foundational change to how we looked at the budgets—from a manual upload of data that is a month old or even a quarter old to every night. It changed the speed at which we can make decisions and see what is happening.” — Long Huynh

The second phase: Workforce and HR integration

Once the initial model was built and data from Banner was integrated directly with IBM Planning Analytics (PA), the focus turned to HR (specifically workforce) to better understand one of the university’s major cost centres. 

Previously, HR tightly guarded payroll information due to privacy requirements, resulting in limited access and insufficient granularity.

To overcome this challenge, AU and ActionKPI developed a workforce variance model within PA that encompassed the FTEs and positions at the university, as opposed to employees. Actual faculty payroll data by position was incorporated into the model, providing visibility into labour costs, vacancy cost savings and headcount, while still maintaining data security and privacy. 

Having this workforce detail allowed faculty members and departments to revise their FTE plans and subsequent labour costs, creating a rolling forecast. This not only improved the forecast accuracy but enabled AU to become more agile within the decision-making process.

“Payroll is the biggest piece of the expense pie, and a thorough and accurate understanding of it is required for an accurate forecast. Now, we can forecast by each position and see the impact in-month and into the future.” — Long Huynh

To address privacy and data security concerns, the finance team collaborated with HR to determine the appropriate salary detail each budget owner could access. Each manager can only see salary details for employees within their hierarchy and only position numbers are shown rather than names. This allows managers the transparency and detail required to make informed decisions while maintaining adequate security and privacy.

Integrated resource planning: A holistic approach

The journey continued with a focus on integrated resource planning. The university aimed to transition from closed-door decision-making to inclusive, integrated resource planning that involved stakeholders from across the organization.

Prior to this initiative, resource plans and proposed budget changes were submitted as separate Excel files, leading to collaboration challenges, version control issues and manual data entry.

ActionKPI integrated the budget and resource planning processes into IBM Planning Analytics (PA), allowing for a streamlined approach. This also enabled a democratized process where budget owners collaborate with their Finance Business Partners to update their budget entries. This supported greater ownership and eliminated the process of budget owners sending numbers to finance and finance doing the entry.

Previously, inconsistent finance knowledge across different faculties and departments led to poor or inaccurate forecasting and budgeting practices.

The rollout of the Finance Business Partner Program contributed to the success of the integrated resource planning process by providing personalized finance support and advisory to each department. It was the financial acumen, passion for customer service and data-driven decision-making skills of the FBP team—combined with the streamlined planning processes and systems—that made it possible.

“Before, a lot of decisions were made behind closed doors. Now, the university has moved to integrated planning, so it is very inclusive. Almost every budget holder is involved in the process versus just finance.” — Long Huynh

Finance Business Partners, assigned to each department, worked closely with budget owners to demonstrate how PA could be utilized to enter, track and visualize budget changes over time.

This integration fostered collaboration, transparency and informed financial decision-making throughout the university.

Through this model, Athabasca University achieved improved forecasting consistency and quality. The FBP model would not have been successful without the implementation of PA, as it provided the necessary infrastructure for effective collaboration and support between finance and budget owners.

Conclusion

The journey to enhance transparency and trust within the university’s financial processes resulted in significant improvements.

By implementing IBM Planning Analytics and integrating budgets, actuals and resource planning, the university achieved better visibility, streamlined processes and increased stakeholder involvement.

The initiatives undertaken by Long and his team not only transformed financial decision-making but also contributed to a cultural shift towards data-driven decision-making and collaboration.

Source: ibm.com

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What is zero-based budgeting?

Zero-Based Budgeting (ZBB) is like solving a financial puzzle. Instead of relying on the previous year’s budget, ZBB requires you to evaluate and justify every expense from the ground up, justifying its necessity and alignment with strategic goals. It’s like starting with a blank canvas and carefully selecting each budget item based on its value and contribution to your financial objectives. This approach ensures that every piece of your budget fits together harmoniously to create a clear and purposeful financial picture.

In this blog post, we will delve into the concept of zero-based budgeting, exploring its definition, advantages, disadvantages, implementation steps, and tools needed.

What is Zero-Based Budgeting? 

The zero-based budgeting process is a strategic budgeting approach that mandates a fresh evaluation of all expenses during each budgeting cycle. Unlike traditional budgeting, where previous spending levels are typically adjusted, ZBB requires individuals or organizations to justify every expense from the ground up. The aim is to optimize resource allocation by ensuring funds are allocated to activities that align with strategic objectives and generate the highest value. 

Peter Pyhrr, an accountant and consultant, is credited with developing the concept of zero-based budgeting (ZBB) in the 1970s. Pyhrr recognized the limitations of traditional methods of budgeting that relied on incremental adjustments to previous budgets. He believed that organizations needed a more rigorous approach to budgeting that would ensure resources were allocated efficiently and aligned with strategic objectives.

Pyhrr introduced the idea of starting the budgeting process from a “zero base,” meaning that every expense had to be justified from scratch. This approach challenged the assumption that previous spending levels were automatically justified, requiring individuals and departments to provide a detailed rationale for each expenditure.

By requiring a fresh evaluation of all expenses, Pyhrr aimed to eliminate unnecessary costs, identify inefficiencies, and promote a more focused use of resources. His goal was to instill a sense of accountability and ownership among budget holders, encouraging them to critically analyze and justify their budget requests.

Advantages of Zero-Based Budgeting

Zero-based budgeting offers several advantages for both businesses and individuals. Some key benefits include: 

• Cost Savings: ZBB requires a thorough evaluation of all expenses, challenging the assumption that last year spending levels are justified. By scrutinizing each line-item expense from scratch, ZBB helps identify unnecessary or redundant costs, preventing overspending. This process allows for cost-cutting and setting savings goals, leading to lower costs and improved financial efficiency. 
• Enhanced Efficiency: ZBB encourages resource reallocation towards high-impact activities. By evaluating expenses based on their value and alignment with strategic objectives, ZBB ensures that resources are allocated to areas that generate the highest return on investment. It promotes a more focused and effective cost management.
• Increased Accountability: With ZBB, individuals or departments must justify their budget requests and align them with organizational financial goals. This fosters a culture of accountability, as each expense must demonstrate its purpose and value. ZBB creates a sense of ownership and responsibility among budget holders. 
• Flexibility and Adaptability: Traditional budgeting systems often rely on historical data and incremental adjustments. ZBB, on the other hand, is not bound by past spending patterns. It allows for better adaptation to changing circumstances, emerging priorities, and new opportunities. ZBB promotes agility in resource allocation, enabling organizations to respond effectively to evolving market conditions. 
• Cost-Conscious Culture: ZBB can foster a cost-conscious culture within an organization. By instilling a mindset of questioning and justifying expenses, ZBB encourages employees to think critically about costs and seek more efficient alternatives to cut back. This culture of cost-consciousness can lead to continuous improvement and a focus on value creation. 
• Improved Decision-Making: ZBB provides a comprehensive view of expenses and their impact on organizational goals. By evaluating each expense category, decision-makers gain better visibility into the cost structure of the organization. This enables informed decision-making, as leaders have a clearer understanding of the trade-offs involved and can make strategic choices based on reliable data. 

How to implement Zero-Based Budgeting?

Implementing zero-based budgeting (ZBB) in an organization involves careful planning and execution. Here are the key steps to follow:

1. Identify Objectives: Clearly define the organization’s goals and strategic direction to establish the foundation for the budgeting process. Ensure that budget allocations align with these objectives and prioritize them accordingly.

2. Evaluate Expenses: Review each expense category, including recurring expenses such as subscriptions, and question their necessity and relevance. Scrutinize both fixed expenses like rent and utilities, and variable expenses such as marketing and travel. Identify areas where costs can be optimized and potential savings can be made.

3. Build Budgets: Create new budgets from scratch, ensuring that each item serves a clear purpose and directly supports the organization’s strategic goals. Consider the importance of each expense category, allocating resources accordingly to maximize their impact. To ensure sufficient funds are available for unforeseen circumstances an emergency fund can be set up.

4. Prioritize Resources: Allocate resources based on their importance and their contribution to the organization’s objectives. Give priority to high-value activities and projects that align with strategic goals. Take budget constraints into account and make informed decisions on resource allocation.

5. Monitor and Review: Regularly monitor the budget implementation, track expenses, and assess performance against objectives. Keep a close eye on spending and make adjustments as necessary to maintain alignment with the organization’s goals. This ongoing monitoring and review process ensures that the budget remains effective and adaptable to changing circumstances.

By following these steps, organizations can successfully implement zero-based budgeting, optimize their resource allocation, and achieve greater financial efficiency while aligning with their strategic objectives.

Disadvantages of Zero-Based Budgeting

While zero-based budgeting can be a powerful tool for organizations, there are several important considerations and potential challenges to be aware of:

• Time and Effort: Implementing zero-based budgeting can be a time-consuming process, especially short-term during the initial stages. It requires a significant investment of effort to thoroughly evaluate and justify every expense from scratch. Adequate planning, data collection, and stakeholder involvement are crucial for a successful implementation.
• Change Management: Adopting a new budgeting method like zero-based budgeting often requires a shift in organizational culture and mindset. Employees may need to adjust to a more rigorous and detailed approach to budgeting, which can lead to resistance or discomfort. Change management practices, such as communication, training, and engagement, are important to facilitate a smooth transition and ensure widespread adoption.
• Complexity: Zero-based budgeting can be more complex than traditional budgeting, especially for large organizations or individuals with diverse financial obligations. The process requires meticulous documentation and tracking systems to ensure accurate evaluation, allocation, and monitoring of expenses. Managing the complexity of ZBB may require additional resources, expertise, and technology to support the budgeting process effectively.
• Resource Allocation Challenges: Zero-based budgeting may pose challenges in resource allocation, particularly when dealing with competing priorities and limited resources. The thorough evaluation of expenses from scratch can sometimes lead to difficult decisions and trade-offs between different activities, projects, or departments. Balancing strategic objectives, budget constraints, and the need for cost optimization requires careful consideration and decision-making.
• Initial Disruption: Implementing zero-based budgeting may cause initial disruption within the organization as existing budgeting practices and processes are replaced or modified. This disruption can impact the workflow, roles, and responsibilities of individuals involved in the budgeting process. Adequate communication, training, and support are essential to minimize disruption and ensure a smooth transition.

By understanding and addressing these potential challenges, organizations can better prepare themselves for the implementation of zero-based budgeting and mitigate any potential negative impacts on the budgeting process and organizational dynamics.

What are the best tools to use for zero-based budgeting?

• Spreadsheets: Traditional spreadsheet applications like Microsoft Excel or Google Sheets can be used to create and manage zero-based budgets. They provide flexibility in organizing budget data, performing calculations, and generating reports. Spreadsheets allow for customization and can be a cost-effective option for smaller organizations.
• Financial Planning and Analysis (FP&A) Software: Offer dedicated features for budgeting, forecasting, and financial analysis. These tools provide a centralized platform for top-down and bottom-up budgeting creation, collaboration, scenario modeling, data integration, and reporting. They often come with advanced analytics capabilities, enabling organizations to make data-driven budgeting decisions.
• Enterprise Resource Planning (ERP) Systems: ERP systems integrate various financial processes, including budgeting. These systems offer modules specifically designed for budget creation, tracking, and reporting. They provide a comprehensive view of financial data, facilitate data integration, and support collaboration among different departments.
• Budgeting and Planning Software: Dedicated budgeting and planning software are designed to streamline the budgeting process. These tools provide features like budget templates, workflow automation, data consolidation, scenario modeling, and reporting. They often offer user-friendly interfaces and enable collaboration among budget stakeholders.
• Data Visualization Tools: Data visualization tools enable organizations to visualize budget data and financial insights. These tools create interactive charts, graphs, and dashboards that enhance the understanding and communication of budget information. Data visualization tools can help identify trends, patterns, and anomalies in the budgeting process.
• Project Management Software: Project management tools like Asana, Trello, or Jira can be utilized to track budgeting tasks, deadlines, and milestones. These tools help manage the workflow, assign responsibilities, and ensure accountability during the budgeting process. They enhance collaboration and provide transparency into the progress of budget-related activities.

How can IBM Planning Analytics help with zero-based budgeting?

IBM Planning Analytics is an integrated business planning and analysis solution that can greatly assist with zero-based budgeting (ZBB) initiatives. Here’s how IBM Planning Analytics stands out and provides value in implementing ZBB:

• Advanced Functionality: IBM Planning Analytics provides robust features specifically designed to support ZBB, such as data collection, analysis, scenario modeling, and budgeting capabilities. It also offers integration with spreadsheets, allowing organizations to leverage existing spreadsheet data and seamlessly transition to a more sophisticated budgeting solution.
• Collaborative Environment: IBM Planning Analytics fosters collaboration among stakeholders involved in the budgeting process. It allows teams to evaluate expenses, allocate resources, and justify budget requests based on strategic objectives. This collaborative environment enhances transparency, and accountability, and ensures that budget decisions align with organizational goals.
• AI-Infused Capabilities: IBM Planning Analytics utilizes artificial intelligence (AI) and machine learning capabilities to provide advanced analytics and forecasting. These AI-infused features help organizations gain deeper insights into their budget data, identify trends, and make more accurate predictions, enabling them to make data-driven budgeting decisions.
• Integration Capabilities: IBM Planning Analytics integrates seamlessly with other systems and data sources, such as accounting platforms or ERP systems. This integration ensures the availability of accurate financial data for budgeting decisions, eliminating the need for manual data entry and reducing errors.
• Scalability and Flexibility: IBM Planning Analytics is highly scalable and suitable for organizations of all sizes. It can adapt to changing business needs and accommodate complex budgeting requirements. Whether it’s a small organization or a large enterprise, IBM Planning Analytics can effectively support the ZBB process.
• User-Friendly Interface: IBM Planning Analytics offers a user-friendly interface that simplifies the budgeting process. Its intuitive design and interactive dashboards allow users to navigate through budget data, perform analyses, and generate reports with ease.

While there are other tools available for zero-based budgeting, IBM Planning Analytics stands out due to its powerful and flexible platform that allows for comprehensive functionality, AI-infused capabilities and user-friendly interfaces. These factors make IBM Planning Analytics a preferred choice for organizations seeking to implement ZBB effectively and achieve cost optimization and accountability throughout the budgeting cycle.

Zero-based budgeting is an innovative type of budgeting that challenges conventional financial practices. By reevaluating expenses from scratch and aligning them with strategic objectives, ZBB promotes cost optimization, efficiency, and accountability. While implementing ZBB requires significant effort and change management, the benefits of this approach can outweigh the challenges.

Source: ibm.com

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It’s 2023… are you still planning and reporting from spreadsheets?

I have worked with IBM Planning Analytics with Watson, the platform formerly known as TM1, for over 20 years. I have never been more excited to share in our customers’ enthusiasm for this solution and how it is revolutionising many manual, disconnected, and convoluted processes to support an organisation’s planning and decision-making activities.

Over the last few months, we have been collecting stories from our customers and projects delivered in 2022 and hearing the feedback on how IBM Planning Analytics has helped support organisations across not only the office of finance – but all departments in their organisation.

The need for a better planning and management system

More and more we are seeing demand for solutions that bring together a truly holistic view of both operational and financial business planning data and models across the entire width and breadth of the enterprise. Having such a platform that also allows planning team members to leverage predictive forecasting and integrate decision management and optimisation models puts organisations at a significant advantage over those that continue to rely on manual worksheet or spreadsheet-based planning processes.

A better planning solution in action

One such example comes from a recent project with Oceania Dairy. Oceania Dairy operates a substantial plant in the small New Zealand, South Island town of Glenavy, on the banks of the Waitaki River. The plant can convert 65,000 litres of milk per hour into 10 tons of powder, or 47,000 tons of powder per year, from standard whole milk powders through to specialty powders including infant formula. The site runs infant formula blending and canning lines, UHT production lines, and produces Anhydrous Milk Fat. In total, the site handles more than 250 million litres of milk per year and generates export revenue of close to NZD$500 million.

Oceania Supply Chain Manager, Leo Zhang shares in our recently published case study: “Connectivity has two perspectives: people to people, facilitating information flows between our 400 employees on site. Prior to CorPlan’s work to implement the IBM Planning Analytics product, there was low information efficiency, with people working on legacy systems or individual spreadsheets. The second perspective is integration. While data is supposed to be logically connected, decision makers were collating Excel sheets, resulting in poor decision efficiency.”

“CorPlan”, adds Zhang, “has fulfilled this aspect by delivering a common platform which creates a single version of the truth, and a central system where data updates uniformly”. In terms of Collaboration, he says teams working throughout the supply chain managing physical stock flows are being connected from the start to the finish of product delivery. “It’s hard for people to work towards a common goal in the absence of a bigger picture. Collaboration brings that bigger picture to every individual while CorPlan provides that single, common version of the truth,” Zhang comments.

The merits of a holistic planning platform

While the approach of selecting a platform to address a single piece of the planning puzzle – such as Merchandise Planning, or S&OP (Sales and Operational Planning), Workforce Planning or even FP&A (Financial Planning and Analysis) – may be a organisations desired strategy, selecting a platform that can grow and support all planning elements across the organisation has significant merits. Customers such as Oceania Dairy are realising true ROI metrics by having:

 

◉ All an organisation’s stakeholders operating from a single set of agreed planning assumptions, permissions, variables, and results

◉ A platform that supports the ability to run any number of live forecast models to support the data analysis and what-if scenarios that are needed to support stakeholder decision-making

◉ An integrated consolidation of the various data sources capturing the actual transactional data sets, such as ERP, Payroll, CRM, Data Marts/ Warehouses, external data stores and more

◉ Enterprise-level security

◉ In the cloud, as a service delivery

My team and I get a big kick out of delivering that first real-time demonstration to a soon-to-be customer, showing them what the IBM Planning Analytics platform can do. It is not just the extensive features and workflow functionality that generates excitement. It is that moment when they experience a sudden and striking realisation – an epiphany – that this product is going to revolutionise the painful, challenging, and time-consuming process of pulling together a plan.

What is even better is then delivering a project successfully, on time and within budget, that delivers the desired results and exceeds expectations.

If you want to experience what “good planning” looks like, feel free to reach out. The CorPlan team would love to help you start your performance management journey. We can help with product trials, proof of concept or simply supply more information about the solution to support your internal business case. It’s time to address the challenges that a disconnected, manual planning and reporting process brings.

Source: ibm.com

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Approaches to long-term planning with IBM Planning Analytics

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

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

Different plans for different needs

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

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

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

The essentials of long-term planning

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

◉ How can we expand the company?

◉ How can we look into acquisitions?

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

◉ What products no longer make sense?

◉ How do debt payments impact cash flow?

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

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

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

Growth percent approach

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

Driver-based approach

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

Mitigate risk with long-term planning

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

Source: ibm.com

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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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Turning insights into actions with IBM Business Analytics

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

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Moving beyond spreadsheets with IBM Planning Analytics

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

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