Revolutionising operations and customer interactions

In today’s fast-paced and competitive business landscape, organisations are constantly looking for innovative ways to enhance efficiency, improve customer experiences, and make data-driven decisions. One of the most transformative technologies that is making waves across industries is the AI assistant.

AI assistants—powered by natural language processing (NLP), machine learning, and automation—are transforming how businesses operate. From streamlining internal workflows to enhancing customer engagement, AI assistants are offering tangible benefits for organisations of all sizes.

In this blog, we’ll explore how AI assistants can help businesses improve operations, drive growth, and stay ahead of the competition.

1. Enhancing customer support and service

One of the most powerful ways AI assistants are impacting business is by transforming customer support. AI-driven chatbots and virtual assistants can handle a wide range of customer inquiries in real time, without the need for human intervention.

Benefits:

• 24/7 availability: AI assistants can work around the clock, ensuring that customers can get the help they need at any time, even outside of regular business hours.
• Instant responses: AI assistants respond quickly to common queries, providing immediate assistance and improving overall response times.
• Consistent customer experience: AI assistants can ensure consistent responses across all customer interactions, eliminating discrepancies that might occur with human support.
• Scalability: During peak periods or holidays, AI assistants can handle a high volume of inquiries without the need to hire additional staff, ensuring that businesses can scale their support operations efficiently.

2. Automating repetitive tasks and workflows

AI assistants are highly effective at automating routine, repetitive tasks that take up valuable time for employees. By taking over menial tasks, AI can help businesses streamline operations and free up human workers to focus on more strategic activities.

Examples of tasks AI assistants can automate:

• Scheduling and calendar management: AI assistants can schedule meetings, set reminders, and send invites, reducing the administrative burden on employees.
• Data entry and documentation: AI can automate data collection, entry, and report generation, ensuring accuracy while saving employees' time.
• Customer feedback collection: AI assistants can automatically send surveys or request feedback from customers, gather responses, and analyse the results for businesses.

Benefits:

• Improved efficiency: By automating time-consuming tasks, employees can focus on high-value work that drives innovation and business growth.
• Reduced human error: AI assistants follow programmed instructions without making mistakes, ensuring that repetitive tasks are completed accurately.
• Faster response times: Automation allows tasks to be completed faster, increasing the overall speed of business processes.

3. Enhancing Data Analysis and Decision-Making

AI assistants, when integrated with business intelligence tools, can help businesses make better decisions based on data-driven insights. AI assistants can analyse large volumes of data in real time and provide recommendations that guide business decisions.

Examples of AI-driven insights:

• Sales trends: AI assistants can analyse sales data and identify trends or patterns in customer behaviour, helping businesses forecast demand and optimize inventory management.
• Market Insights: AI can analyse competitor data, customer preferences, and market conditions, providing businesses with insights that help shape marketing strategies.O
• Operational efficiency: AI assistants can identify bottlenecks or inefficiencies in workflows, providing recommendations for process improvements.
  

Benefits:

• Better decision-making: AI assistants provide real-time insights, helping managers and executives make informed decisions faster.
• Predictive analytics: AI-powered tools can forecast future trends, helping businesses anticipate market changes and adjust strategies accordingly.
• Cost savings: By identifying inefficiencies or underperforming areas, AI assistants can help businesses reduce waste and optimize resource allocation.

4. Improving marketing and personalisation

AI assistants can significantly improve marketing efforts by offering a higher level of personalization and delivering targeted content to the right audience. By analysing customer preferences, behaviour, and interactions, AI assistants can help businesses create customised marketing campaigns that drive engagement and conversions.

Examples of AI-driven marketing activities:

• Personalised recommendations: AI assistants can analyse customer browsing and purchase history to recommend products or services tailored to individual preferences.
• Automated content creation: AI assistants can help businesses generate content, such as emails, product descriptions, and blog posts, based on customer interests and previous interactions.
• Social media monitoring: AI assistants can track social media mentions, sentiment, and trends, helping businesses adjust their marketing strategy in real time.

Benefits:

• Increased customer engagement: Personalised experiences resonate more with customers, leading to hi
• Better targeting: AI can segment customers based on their preferences and behaviors, allowing businesses to target the right audience with the right message at the right time.
• Enhanced ROI: With improved targeting and personalisation, businesses can see a higher return on marketing investments.

5. Enhancing employee productivity and collaboration

AI assistants are not only beneficial for customer-facing tasks but also play a vital role in improving internal productivity and collaboration within organisations. By providing employees with access to real-time information, helping them manage tasks, and facilitating communication, AI assistants can improve overall team performance.

Examples of how AI assistants can help employees:

• Project management: AI can assist with project tracking, reminders, and deadline management, ensuring that projects stay on track.
• Internal communication: AI assistants can help employees quickly find the information they need by searching through internal knowledge bases, documents, and databases.
• Collaboration tools: AI assistants can integrate with tools like Slack, Microsoft Teams, and Google Workspace, providing employees with intelligent support and facilitating team collaboration.

Benefits:

• Time savings: Employees can quickly access information, receive reminders, and automate tasks that would otherwise take time, allowing them to be more productive.
• Improved communication: AI can enhance communication and reduce delays in getting answers or collaborating on projects.
• Task prioritisation: AI assistants can help employees prioritize tasks based on urgency and importance, ensuring that critical work gets done first.

6. Boosting sales and lead generation

AI assistants can help businesses improve their sales processes by identifying new leads, nurturing existing prospects, and automating customer interactions during the sales journey.

Examples:

• Lead qualification: AI can help qualify leads by engaging with prospects through chat, analyzing their responses, and scoring their likelihood to convert into paying customers.
• Automated follow-ups: AI assistants can automate email follow-ups, schedule calls, and send reminders, ensuring that no leads slip through the cracks.
• Sales forecasting: AI assistants can analyse past sales data and predict future sales trends, helping sales teams plan their efforts more effectively.

Benefits:

• Increased sales: By automating lead generation and nurturing processes, AI helps sales teams focus on high-priority leads, improving conversion rates.
• Efficiency gains: Automated tasks like follow-ups and lead qualification free up time for sales teams to focus on closing deals and building relationships with customers.
• Data-driven insights: AI assistants provide real-time insights into sales performance, helping teams make data-driven decisions that optimize their efforts.

7. Boosting employee training and development

AI assistants can also be leveraged for training and employee development, especially in large organizations with a continuous need for skill enhancement.

Examples:

• Training modules: AI-powered platforms can recommend training materials and courses based on an employee’s current role, interests, and skill gaps.
• Onboarding assistance: New employees can interact with AI assistants to learn about company policies, procedures, and workflows, ensuring a smooth onboarding experience.
• Performance feedback: AI assistants can track employee performance and provide actionable feedback to help employees improve and grow.

Benefits:

• Personalised learning: Employees receive tailored training recommendations based on their specific needs, leading to more effective learning.
• Faster onboarding: AI assistants help new employees get up to speed quickly by providing them with essential resources and answering common questions.
• Continuous development: AI enables businesses to offer continuous learning opportunities, fostering a culture of growth and improvement.

AI assistants are reshaping the way businesses operate by automating tasks, improving customer engagement, providing real-time insights, and enhancing productivity. Whether it’s through streamlining workflows, enhancing personalisation, improving decision-making, or

offering round-the-clock customer support, AI assistants bring immense value to organisations across industries.

As businesses continue to adopt AI-driven solutions, those who leverage AI assistants will likely see significant improvements in efficiency, customer satisfaction, and overall business performance. By embracing this transformative technology, organisations can stay competitive, boost innovation, and achieve long-term success.

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In a world where speed, scale, and trust define success, Octane has emerged as a leader in enterprise AI-driven transformation. Honoured with the 2025 IBM Partner Plus Award in APAC for automation, Octane’s groundbreaking use of IBM Watsonx Orchestrate is setting a new benchmark for how intelligent automation can empower business users and scale human productivity.

The Award: Increasing performance through automation

The IBM Partner Plus Award for Automation celebrates business partners who are delivering new levels of performance with speed, scale and security, enabling systems, business processes, and people to be more efficient.

For Octane, this means:

• Speed: Accelerating workflows by over 70% through AI orchestration.

• Adaptability: Designing solutions that flex with business demands.

• Security: Ensuring compliance through enterprise-grade automation guardrails.

“This award reinforces our belief that automation should be intuitive, intelligent, and human-first,” said Amendra Pratap, Managing Director. “Our collaboration with IBM brings this vision to life.”

IBM Watsonx Orchestrate: A new paradigm in intelligent automation

Watsonx Orchestrate is IBM’s enterprise-ready solution that helps create, deploy, and manage AI assistants and agents. It blends AI and workflow automation, enabling users to interact with systems using natural language prompts, representing a powerful step toward fully autonomous agentic AI systems. It enables multi-step, goal-driven task orchestration and integration with existing business systems, connecting to multiple proprietary and third-party AI models and automation tools.

How Octane leverages Watsonx Orchestrate:

• Skill-based AI execution: Prebuilt “skills” automate repetitive actions—like sending emails, updating records, or scheduling interviews.
• No-code integrations: Plug-and-play connections to enterprise tools like SAP, Salesforce, and Workday.
• Conversational interface: Users trigger complex workflows through Slack, Teams, or email with simple prompts.

“Watsonx Orchestrate isn’t just for building chatbots—it’s an AI-powered teammate,” says Amendra Pratap, Managing Director, “Watsonx Orchestrate is your next hire. By orchestrating tasks across various assistants, agents and systems, it helps boost workforce efficiency and reduces manual load by surfacing the right tools when you need them."

Real-world impact:

What we achieved:

What sets Octane apart: Augmented intelligence, not just automation

Traditional automation follows rules. Octane uses AI to understand goals, context, and next best actions.

With Watsonx Orchestrate, Octane delivers:

• Adaptive workflows: Adjusts based on real-time data (e.g., re-routing approvals during outages).
• Multi-agent collaboration: Skills collaborate (e.g., sentiment analysis + ticket escalation).
• Continuous learning: Models improve from feedback to streamline operations over time.

“We don’t just automate tasks—we augment thinking,” says Steny Sebastian, Principal - Data and AI Platforms. “That’s how we deliver smarter outcomes, not just faster ones.”

Ready to orchestrate intelligence into every workflow?

 Explore how Octane’s award-winning AI solutions can help you scale with confidence.

Learn how advanced your organisation is with AI adoption and how Orchestrate can help. - Take the next step. Try IBM Watsonx Orchestrate at no cost, or book a consultation with an expert

Learn more about the IBM Partner Plus Awards: https://www.ibm.com/partnerplus/awards

#AgenticAI #EnterpriseAutomation #OctaneSolutions #WatsonxOrchestrate #IBMPartnerPlus #DigitalTransformation

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In today’s fast-paced business environment, companies are constantly looking for ways to streamline their operations, improve decision-making, and stay ahead of the competition. One of the tools that has gained significant attention in the world of business intelligence and analytics is IBM Planning Analytics, which harnesses the power of AI to enhance financial planning, forecasting, and reporting. One of the standout features of IBM Planning Analytics is its AI Assistant, an innovative tool that leverages artificial intelligence to provide smarter, more efficient planning and analytics capabilities.

In this blog, we’ll dive into the key features of the IBM Planning Analytics AI Assistant and explore how it is transforming business planning for organizations around the world.

What is IBM Planning Analytics AI Assistant?

IBM Planning Analytics is a cloud-based solution designed to help businesses automate their planning, budgeting, forecasting, and analysis processes. The AI Assistant embedded within the platform brings cognitive capabilities to the table, making it more intuitive and user-friendly.

The AI Assistant uses natural language processing (NLP) and machine learning algorithms to understand and respond to user queries in plain language, enabling business users—whether financial analysts, planners, or executives—to interact with the system in a more natural way. Instead of relying on complex formulas or spending hours running reports, users can simply ask questions like, "What was our sales growth in Q3?" or "How much did our expenses increase year-over-year?" The AI Assistant then processes these requests and provides quick, data-driven insights.

Key Features of IBM Planning Analytics AI Assistant

1. Conversational Analytics

   One of the most impressive features of the AI Assistant is its ability to enable conversational analytics. Traditionally, getting insights from business intelligence tools involved navigating through multiple layers of data, setting up reports, or writing complex queries. The AI Assistant eliminates this complexity by allowing users to ask questions in natural language, just like they would talk to a colleague or consultant.

   For example, a user can ask, "What were our sales for last quarter?" and the AI Assistant can instantly pull up relevant data, graphs, or reports. This conversational interface makes it easier for non-technical users to engage with analytics and access valuable insights without having to be data experts.

2. Data-driven Decision-Making

   The AI Assistant doesn’t just provide static answers—it actively helps users analyse trends, identify anomalies, and make data-driven decisions. For instance, the Assistant can compare historical data, identify seasonal patterns, and even suggest potential adjustments to forecasts based on changing market conditions. This empowers decision-makers to quickly assess different scenarios and make informed choices.

   Additionally, the Assistant can provide context behind the data, such as explanations of why certain numbers are trending upward or downward. This deeper level of understanding enables organizations to plan with greater confidence.

3. Predictive Analytics and Forecasting

   In addition to assisting with retrospective analysis, the AI Assistant is also equipped to help users with predictive analytics. Using historical data, market trends, and other variables, the Assistant can generate forecasts for various business aspects like sales, revenue, and operational costs.

   For instance, planners can ask the AI Assistant, "What is the projected revenue for the next quarter based on current trends?" The Assistant then leverages machine learning models to provide accurate, forward-looking forecasts. By incorporating AI-driven insights, businesses can improve their planning accuracy and reduce the risks associated with manual forecasting.

4. Automated Insights and Recommendations

   One of the standout benefits of AI in business planning is its ability to go beyond simple reporting. The IBM Planning Analytics AI Assistant is capable of delivering automated insights and recommendations that are tailored to the needs of the organization. By analyzing past performance, the Assistant can highlight areas of opportunity or potential risk that may require attention.

   For example, if expenses are increasing faster than revenue, the Assistant might recommend strategies for cost-cutting or optimizing operations. These automated recommendations allow planners and analysts to quickly address potential issues and capitalize on emerging opportunities.

5. Seamless Integration with IBM Planning Analytics Workspace

   The AI Assistant is fully integrated with the IBM Planning Analytics Workspace, which is the central hub for business users to manage and analyze data. This integration ensures that users have a smooth experience when interacting with their data, whether they are leveraging the AI Assistant for ad-hoc analysis or using the broader tools available in Planning Analytics for long-term strategic planning.

   The seamless integration between the Assistant and the workspace also means that businesses can continue to rely on traditional data management and reporting workflows while taking advantage of AI-powered insights without disruption.

Benefits of IBM Planning Analytics AI Assistant

• Faster Decision-Making

  The AI Assistant accelerates decision-making by delivering insights in real-time. Users can ask questions and get answers instantly, without having to manually sift through large datasets or run complex queries. This speeds up planning cycles and ensures that decisions are based on the latest data.

• Empowerment of Business Users

  With the AI Assistant, business users who may not have deep technical expertise can now access analytics and make informed decisions. This democratization of data ensures that all teams—finance, marketing, operations—are equipped to contribute to planning processes and drive organizational success.

• Reduced Errors

  Since the AI Assistant uses machine learning models to predict and analyse data, the likelihood of human error in forecasting and planning is significantly reduced. Automated insights and recommendations are based on sophisticated data analysis, helping to eliminate mistakes caused by manual data handling.

• Scalable Insights Across Teams

  The AI Assistant enables businesses to scale their analytics capabilities across teams and departments. Whether a team is working on financial forecasts, sales targets, or operational efficiencies, the Assistant can be used to generate insights that are relevant to each department’s specific goals and objectives. This scalability ensures that AI-powered decision-making benefits the entire organization.

Real-World Use Cases

1. Finance Teams

   For finance teams, the AI Assistant is a game-changer in managing budgets, forecasting, and scenario planning. It can quickly identify deviations from expected results, recommend corrective actions, and forecast the financial outlook based on real-time data.

2. Sales and Marketing Teams

   Sales and marketing teams can use the Assistant to gain quick insights into customer behaviour, sales trends, and marketing ROI. By understanding which campaigns are driving results and which aren’t, they can adjust strategies on the fly and optimize their efforts.

3. Operations and Supply Chain

   Operations managers can use the AI Assistant to forecast demand, optimize inventory, and predict potential supply chain disruptions. By understanding these dynamics earlier, businesses can mitigate risks and improve operational efficiency.

Conclusion

The IBM Planning Analytics AI Assistant represents a significant leap forward in the world of business analytics. By combining artificial intelligence, natural language processing, and predictive analytics, it transforms the way businesses plan, forecast, and make decisions. With its ability to provide faster insights, automate recommendations, and empower users across the organization, the AI Assistant is not just a tool—it’s a strategic asset that helps businesses become more agile and data-driven in their operations.

As businesses continue to face increasingly complex challenges, tools like IBM Planning Analytics AI Assistant will become indispensable for navigating the future of planning and decision-making.

Ready to take AI to the next level? Talk to us! 

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The world of finance is evolving rapidly, and AI is no longer a futuristic concept—it’s a practical tool that can transform how finance teams operate. But for many organisations, the idea of integrating AI into their workflows can feel overwhelming. Where do you start? How do you ensure success? The answer lies in taking a gradual, strategic approach. With Watson Orchestrate and IBM Planning Analytics, you can start small, prove the value, and confidently scale your AI initiatives. At Octane, we guide you through this journey, from exploring use cases to delivering impactful projects.

Why Start Small with AI in Finance? 

AI has the potential to revolutionize finance by automating repetitive tasks, enhancing decision-making, and improving accuracy. However, diving headfirst into a full-scale AI implementation can be risky. Starting small allows you to test the waters, build confidence, and demonstrate tangible results before committing to larger investments. This is where Watson Orchestrate shines—it’s designed to integrate seamlessly with your existing tools, like IBM Planning Analytics, and automate specific tasks without disrupting your workflows. 

Step 1: Explore Use Cases with Octane’s Workshops 

The first step in your AI journey is identifying where it can add the most value. We work closely with IBM client engineering team and run interactive workshops to help you explore potential use cases for Watson Orchestrate within your finance team. These workshops are designed to: 

• Understand Your Pain Points: We work with your team to identify repetitive, time-consuming tasks that are ripe for automation, such as data consolidation, report generation, or budget reconciliation. 

• Brainstorm Solutions: Together, we brainstorm how Watson Orchestrate can address these challenges, leveraging its AI capabilities to automate processes and enhance efficiency. 

• Prioritise Opportunities: Not all use cases are created equal. We help you prioritize the ones that offer the quickest wins and the highest impact. 

Step 2: Prove the Value with a Proof of Concept (POC) 

Once we’ve identified promising use cases, the next step is to validate them through a Proof of Concept (POC). A POC allows you to see Watson Orchestrate in action, delivering real results in a controlled environment. Here’s how it works: 

• Define Success Metrics: We work with you to define clear objectives and success metrics for the POC, ensuring that the results are measurable and aligned with your goals. 

• Build and Test: Our team builds the POC, integrating Watson Orchestrate with IBM Planning Analytics to automate the selected use case. We test the solution rigorously to ensure it meets your requirements. 

• Evaluate Results: After the POC, we evaluate the results together. Did it save time? Improve accuracy? Enhance productivity? These insights help you decide whether to move forward with a full-scale implementation. 

Step 3: Deliver the Project and Scale 

If the POC demonstrates value, we move into the  project delivery phase. Our team works closely with yours to implement the solution, ensuring it’s tailored to your specific needs and integrated seamlessly into your workflows. Once the initial project is delivered, you can scale the solution to address additional use cases, gradually expanding the role of AI in your finance operations. 

Real-World Impact: A Gradual Approach to AI 

Many organizations have successfully adopted AI in finance by starting small and scaling strategically. For example, a airline participated in one of Octane’s workshops and identified report generation as a key pain point. Through a POC, they automated the process using Watson Orchestrate, reducing the time required from 2 days to just 30 minutes. Encouraged by the results, they expanded the solution to automate budget reconciliation, achieving even greater efficiencies. 

Why Choose Octane? 

At Octane, we specialise in helping organisations like yours navigate the complexities of AI adoption in Finance teams. Our phased approach—starting with workshops, moving to POCs, and then delivering projects—ensures that you can dip your toes into AI without taking on unnecessary risk. We bring deep expertise in Watson Orchestrate and IBM Planning Analytics, along with a commitment to delivering measurable results.  

Take the First Step Today 

AI is no longer a distant dream—it’s a practical tool that can transform your finance team. By starting small with Watson Orchestrate and IBM Planning Analytics, you can explore the potential of AI, prove its value, and scale your initiatives with confidence. Ready to get started? Contact Octane today to schedule a workshop and begin your AI journey. Email us at  media@octanesolutions.com.au  to learn more. 

The future of finance is AI-powered, and the journey starts with a single step. Let Octane guide you every step of the way. 

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The holiday season is a time for joy, relaxation, and quality time with loved ones. However, for many finance teams, it’s also a period of intense activity. Year-end closings, budgeting, and reporting deadlines can pile up, creating a stressful and demanding environment.

Imagine spending your holiday season worrying about potential system outages, data load failures, or urgent user queries. It’s a scenario that can disrupt your well-deserved break and compromise your team’s productivity.

Leverage Dedicated TM1 Support During the Holidays

• Engage a reliable TM1 support partner to handle system maintenance, troubleshooting, and year-end processes so your team can enjoy a well-deserved break without stress.

Automate Routine Tasks and Processes in TM1

• Use TM1’s automation capabilities to schedule recurring tasks like data loads, reconciliations, and report generation, ensuring everything runs smoothly while minimizing manual effort.

Ensure Proactive Monitoring and Downtime Prevention

• A TM1 support team can proactively monitor your environment, identify potential issues before they escalate, and ensure critical systems remain up and running during the festive season.

Outsource Last-Minute Reporting and Forecasting Support

• Avoid scrambling to meet year-end deadlines by outsourcing TM1 reporting tasks to a team that can handle changes, corrections, and urgent requests with expertise and speed.

Plan Ahead with a Holiday Support Coverage Model

• Partner with a TM1 managed services provider who offers holiday-specific coverage, ensuring your team has access to skilled resources when needed, without disrupting workflows or personal time.

Why TM1 support (Octane Blue) is the Perfect Solution 

That’s where Octane Blue comes in. Our comprehensive support service is designed to alleviate your holiday stress and ensure business continuity. With 40 hours of dedicated support, you can rest easy knowing that your TM1 environment is in expert hands.

What Does Octane Blue Offer? 

1. Proactive System Monitoring: Our team will keep a watchful eye on your TM1 environment, identifying and resolving potential issues before they escalate. 

2. Rapid Incident Response: Should any issues arise, our experienced support engineers will be on hand to diagnose and fix them promptly. 

3. Data Load and Reconciliation Support: We’ll assist with data load processes, ensuring accurate and timely data integration.

4. Security and Access Management: Our team will help maintain the security of your TM1 environment and manage user access rights. 

5. Security and Access Management: Our team will help maintain the security of your TM1 environment and manage user access rights.

6. Technical and Functional Support: We’ll provide expert guidance on a wide range of TM1 topics, from technical troubleshooting to functional best practices.

7. User Support: Our team will be available to assist your users with any questions or issues they may encounter. 

Frequently Asked Questions

• 40 hours. 

• Unused hours will be rolled over for one additional month. 

• No, Octane Blue is available on any TM1 site. 

• No, you can purchase Octane Blue on a one-time basis or as needed. 

• https://www.octanesolutions.com.au/tm1-support#switch

• Purchase now

• Book a meeting with us

Don’t let the holiday season stress you out. Let Octane Blue take care of your TM1 environment so that you can enjoy a peaceful and productive holiday. 

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Attending IBM TechXchange in Mandalay Bay, Las Vegas was an exhilarating experience that showcased the cutting-edge IBM technologies shaping various industries today. The conference brought together technologists, IBM Champions, thought leaders, industry experts, and innovators eager to share insights and explore the latest advancements in IBM's technology portfolio. From AI to cloud computing, the event highlighted how these tools are transforming businesses, making operations more efficient, and ultimately driving better decision-making.

As an IBM champion we were treated as VIPs with row seats in all keynote sessions, special champions lounge and special dinners and networking sessions. It was great to see IBM champions sporting the blue jackets throughout the conference.

One of the standout moments for me was the opportunity to present alongside Ashika Singh from Fiji Airways. Our session focused on their usage of IBM Planning Analytics, which allowed Fiji Airways to navigate the challenges posed during the COVID-19 shutdown. The pandemic created unprecedented obstacles for the airline industry, with travel restrictions and safety concerns leading to a dramatic decline in passenger numbers. However, Fiji Airways leveraged IBM Planning Analytics to make data-driven decisions that prepared them for the eventual reopening of global travel.

During our presentation, we shared how the airline utilised forecasting and scenario planning capabilities in the tool to assess various outcomes and devise strategies for recovery. By analysing all drivers and generating up to 60- what-if scenarios at a time, Fiji Airways was able to predict future demand and align their resources accordingly. This proactive approach not only ensured they were ready when the skies reopened but also positioned them to adapt quickly to changing circumstances, ultimately enhancing their resilience. This led to numerous awards and Fiji Airways is now ranked 14^th in the world in Skytrax ranking 2024. They have overtaken Qantas and Air New Zealand which traditionally dominated the rankings in the region.

The discussions throughout the conference were incredibly enlightening. Industry leaders spoke about the importance of digital transformation and how organizations must prioritise agility and innovation to thrive in today's fast-paced environment. There was a strong emphasis on how leveraging AI and analytics can unlock new opportunities, streamline operations, and create a more personalized customer experience. These insights resonate deeply, especially in sectors like travel and hospitality that have been profoundly affected by global events.

Networking opportunities were plentiful at TechXchange, allowing me to connect with other professionals who share a common goal of harnessing technology for business growth. Conversations flowed about the challenges and triumphs faced during the pandemic, highlighting how collaboration and knowledge-sharing have played vital roles in overcoming adversity. Each conversation reinforced the idea that we are all part of a larger community that supports each other's journeys toward transformation. There were lots of opportunities to network with other TM1 specialists from around the world.

The event was also filled with hands-on labs and demonstrations, showcasing IBM's latest products and solutions. Exploring new functionalities and engaging with the technology firsthand enhanced my understanding of how these tools can be applied in various contexts. It was exciting to envision how businesses can harness these innovations to optimize their operations and improve overall performance. IBM also used the conference to announce the launch of the Granite 3.0 AI model. (Read more here Granite 3.0)

Looking back on my experience at IBM TechXchange, I am inspired and optimistic about the future. Planning Analytics has a range of new functionality to improve performance, deployment options and integration of IBM AI onto the platform will cement its position as a leader in the XP&A space. Presenting with Ashika was a highlight that illustrated not only the adaptability of Fiji Airways but also the potential of data-driven decision-making for all of our clients. There was a lot of interest in how we integrate Watson Orchestrate with Planning Analytics to boost the AI functionality in finance teams.

In conclusion, attending IBM TechXchange has provided a great platform to see where IBM is going in the future – and it's looking exciting. As AI becomes more mainstream and use cases continue to evolve it was interesting to see how our peers and IBM are harnessing this technology to deliver business value for clients. The dates for 2025 Techxchange in Orlando are already announced and Octane will once again attend along with our clients. (More details IBM Techxchange conference)

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Planning Analytics Workspace (PAW) offers a robust suite of visualizations, enabling users to create rich and compelling reports and dashboards with remarkable flexibility. However, even with these capabilities, you may occasionally encounter requirements that push the limits of what PAW provides out of the box. 

One such scenario I encountered was the need to create a column chart comparing Actual vs Budget variance. The twist? Any negative variance should be highlighted with a red bar, while positive variance should be displayed in green, as shown below: 

PAW’s default settings don't currently offer this kind of custom conditional formatting for visualizations. However, with a little MDX magic and a few formatting tweaks, you can achieve this effect in just five simple steps. 

Step-by-Step Guide to Creating Custom Visualizations in PAW 

Step 1: Position the Version Dimension in the Column 

Start by positioning the Version dimension in the column of the Exploration view. This is where we will apply the MDX logic to derive the desired results. 

Step 2: Use MDX to Create Calculated Members 

Next, you'll need to update the MDX query by creating three calculated members to represent Actual vs Budget (AvB), Positive Variance, and Negative Variance. 

Here’s the MDX code: 

MDX code: 

WITH  

MEMBER [Version].[Version].[AvB] AS [Version].[Version].[Actual] - [Version].[Version].[Budget]  

MEMBER [Version].[Version].[Positive] AS IIF([Version].[Version].[AvB] > 0, [Version].[Version].[AvB], "") 

MEMBER [Version].[Version].[Negative] AS IIF([Version].[Version].[AvB] < 0, [Version].[Version].[AvB], "") 

Note: The AvB calculation could also be done using a consolidated member in the Version dimension, where the Budget has a negative weight. 

Step 3: Replace the MDX in the Row Axes 

Now, replace the MDX in the Row Axes relating to the Version dimension to show only the Positive and Negative calculated members, while excluding the AvB calculation (and any other member): 

MDX code: 

{ 

    EXCEPT( 

        { 

            [Version].[Version].[AvB], 

            [Version].[Version].[Positive], 

            [Version].[Version].[Negative] 

        },  

        { 

            [Version].[Version].[AvB] 

        },  

        ALL 

    ) 

} 

This MDX will generate a view that displays only Positive and Negative members in the Version dimension, leaving the non-relevant member (whether positive or negative) as blank, depending on the AvB value. 

Step 4: Convert the Exploration View into a Column Chart

Once the MDX has been applied, convert the Exploration view into a Column Chart. By default, PAW will show the columns for positive and negative values with its standard color scheme.  

Step 5: Apply a Custom Color Palette 

To finalize the visualization, we’ll apply a custom color palette. Navigate to the visualization properties and create a color palette that includes only two colors: green for positive values and red for negative values. 

Conclusion 

With just a few lines of MDX and a bit of customization, you can significantly enhance PAW visualizations. This technique allows you to move beyond the standard out-of-the-box options, giving you the flexibility to create more intuitive and visually effective reports. Whether you're comparing Actual vs Budget or any other metrics, these methods help you build visuals that not only convey the necessary information but do so in a way that is easy to interpret at a glance. 

By leveraging MDX and PAW’s formatting tools, you can push the boundaries of your reporting and create dynamic, insightful dashboards tailored to your business needs. 

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In the realm of digital transformation, the concept of digital labor has emerged as a game-changer for businesses seeking efficiency, agility, and innovation. IBM WatsonsX Orchestrate, a powerhouse in the AI and data orchestration space, takes center stage in this digital evolution. This blog explores the pivotal role played by WatsonsX Orchestrate in reshaping digital labor and how it empowers organizations to harness the full potential of artificial intelligence (AI) and data science.

Orchestrate allows you to add and train new automations from a variety of sources, enabling users to easily work across existing systems using a single UI.

Understanding Digital Labor:

Digital labor refers to the use of digital technologies, including AI, automation, and robotics, to augment or replace human tasks and processes. It's a paradigm shift in how work is done, leveraging technology to enhance productivity, reduce errors, and enable humans to focus on more strategic and creative aspects of their roles.

"Companies that effectively apply intelligent automation across the enterprise expect to outshine peers in profitability, revenue growth, and efficiency over the next 3 years."

IBM WatsonsX Orchestrate and Digital Labor:

1. Workflow Automation for Operational Efficiency: One of the key pillars of digital labor is workflow automation, and WatsonsX Orchestrate excels in this domain. By automating intricate AI and data science workflows, the platform significantly reduces manual effort, streamlining processes and enhancing operational efficiency. This allows organizations to accomplish more with less, freeing up human resources for high-value tasks.

2. Collaboration for Enhanced Productivity: Digital labor is not about replacing human workers but augmenting their capabilities. WatsonsX Orchestrate fosters collaboration among cross-functional teams, bringing together data scientists, developers, and domain experts. This collaborative environment accelerates problem-solving, decision-making, and innovation, creating a synergistic relationship between digital labor and human expertise.

3. Scalability to Meet Growing Demands: As organizations scale their digital labor initiatives, scalability becomes a critical factor. WatsonsX Orchestrate provides the flexibility to scale horizontally and vertically, ensuring that the platform can seamlessly adapt to the growing demands of AI and data science projects. This scalability is essential for organizations aiming to expand their digital labor capabilities without compromising performance.

4. Model Monitoring and Management for Continuous Improvement: In the era of digital labor, continuous improvement is paramount. WatsonsX Orchestrate includes robust tools for monitoring and managing AI models in production. This ensures that digital labor processes based on AI models deliver consistent and reliable results over time. The platform's capabilities contribute to the iterative refinement of digital labor processes, optimizing outcomes and enhancing overall performance.

5. AI Explainability and Ethical Digital Labor: Transparent digital labor practices are crucial for building trust and ensuring ethical use of AI. WatsonsX Orchestrate provides tools for explaining AI model decisions, addressing the interpretability challenge often associated with complex AI systems. Additionally, the platform includes features for detecting biases, aligning digital labor practices with ethical standards and promoting fairness in decision-making.

   
   

   

   There are more than 2,000 activities that make up 800 full-time occupations that are part of knowledge work. However, only 5% of these full-time occupations could be fully automated using existing technology. That means that the 95% of remaining occupations require cognitive abilities.

Benefits for Businesses:

1. Accelerated Time-to-Value: By automating and streamlining AI and data science workflows, organizations can significantly reduce the time it takes to move from ideation to deployment, ultimately accelerating their time-to-value for AI initiatives.

2. Improved Collaboration: The collaborative features of WatsonsX Orchestrate facilitate better communication and knowledge sharing among teams, leading to more effective and impactful AI solutions.

3. Enhanced Governance and Compliance: The platform provides robust governance and compliance features, ensuring that organizations can meet regulatory requirements and maintain a high standard of data ethics.

4. Cost-Efficiency: With the ability to scale and the flexibility of deployment options, WatsonsX Orchestrate helps organizations optimize costs by aligning infrastructure with project requirements.

In the era of AI and data-driven decision-making, IBM WatsonsX Orchestrate stands out as a powerful solution for organizations looking to harness the full potential of their AI and data science initiatives. With its automation capabilities, collaborative environment, and emphasis on ethical AI, WatsonsX Orchestrate is poised to become a key player in the journey towards building intelligent, transparent, and scalable AI solutions. As businesses continue to navigate the complexities of the digital age, platforms like WatsonsX Orchestrate provide the tools needed to turn data into a strategic asset and drive innovation in the ever-evolving landscape of AI.

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IBM Watson™ Studio is a platform for businesses to prepare and analyse data as well as build and train AI and machine learning models in a flexible hybrid cloud environment.

IBM Watson™ Studio enables your data scientists, application developers and subject matter experts work together easier and collaborate with the wider business, to deliver faster insights in a governed way.

Watch the below for another brief intro

Available in on the desktop which contains the most popular portions of Watson Studio Cloud to your Microsoft Windows or Apple Mac PC with IBM SPSS® Modeler, notebooks and IBM Data Refinery all within a single instal to bring you comprehensive and scalable data analysis and modelling abilities.

However, for the enterprise, there are also the versions of Watson Studio Local, which is a version of the software to be deployed on-premises inside the firewall, as well as Watson Studio Cloud is part of the IBM Cloud™, a public cloud platform. No matter which version your business may use you can start using Watson Studio Cloud and download a trial of the desktop version today!

Over the next 5 days, we'll ensure to send you use-cases and materials of worth for you to review at your earliest convenience. Be sure to check our social media pages for these.

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As business implements more and more technology to streamline their operations the benefits of saving time, minimising costs, increasing productivity and better accuracy are starting to be realised. This means this is hardly a trend that will fade anytime soon. If you or your business are not 'there yet' it’s better to catch up now rather than being left behind with the rest of the competition.

We've moved on from the times when cloud technology was an unknown territory for especially for Accounting and Finance but the industry players are now fully aware, prepared or in cloud. This leaves us to ponder where to next? I think people are now starting to set their attention to the adoption of artificial intelligence (AI) and we can see that this is happening at a much faster pace.

Both Data and work as we know it will be strongly affected by AI. With bots now able to determine and sort the information into different accounts by themselves, meaning AI is already delivering solo performances in the field. Further to this, Bots can tell and organise data coming from the same source into different categories, so if you have a monthly subscription and or one off purchases coming from the supplier, bots will automatically understand that they are of a different nature and will set them under different chart of accounts. Machine learning is also observable since these bots can learn from various human inputs to make better judgments and to adapt to accounting professionals’ behaviour patterns.

The effect or major changes due to AI on the typical Accounting and Finance role will have one of two observable outcomes:

• The menial / administrative tasks as they stand right now are slowly becoming scarcer, even some operational tasks traditionally performed by accountants, such as dedicated accounts payable and accounts receivable ones, are already being performed by AI or are outsourced.
• The other observable is the way accounting and finance will be structured within the organisation more than likely a small footprint but they have a greater impact.

The results of the above inevitably are better performance and enhanced cost reductions and although AI is already finding its way into the finance and accounting industry, it’s not been fully adopted quite yet. Without a doubt, the accounting industry has a bright future ahead with a focus more on value add than the menial.

Part 2 of this article might be a review of the tools avaialble. What do you think? Was my assessment fair? Leave comments, or feel free to reach out on social media.

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