Richard Abraham

Posted by:
Richard Abraham
- Sector Lead

In today’s vibrant business landscape, supply chains are increasingly volatile, with rapid and unpredictable changes in demand commonplace. This coupled with labour shortages, fluctuations in stock availability and the profound impact of rapid price inflation are placing significant pressure on supply chain managers to deliver. In order to keep pace, companies are turning to analytics and scenario modelling to enable them to swiftly adapt to the ever-evolving market dynamics. 

The Power of Informed Decision-Making 

We recognise that the manufacturing and construction industry heavily depends on operational efficiency, with technology serving as a pivotal enabler. Significant progress has been made toward achieving these objectives by harnessing the potential of data management, by implementing cutting-edge BI tools, advanced analytics, and streamlined automation. However, the driving force behind this approach remains planning analytics, a transformative force that has redefined how countless organisations achieve superior business outcomes. 

Planning Analytics Unveiled | Extended Planning & Analysis: The Game Changer  

Over the last five years, the market has seen the rise of a concept known as Extended Planning and Analysis (xP&A). It involves connecting data across various aspects of a business, from finance to operations, to create a comprehensive decision-making framework. This extends beyond finance to encompass sustainability planning, strategic workforce planning, market forecasting, and more. 

What does this mean for organisations who rely on an efficient and effective supply chain model? 

Addressing Complex Manufacturing and Distribution Challenges at Tata Steel 

In a recent webinar, steel manufacturer TATA Steel, described how it was possible to navigate complex business challenges in their manufacturing and distribution operations using planning analytics. TATA needed to answer questions related to order scheduling, which was complicated due to a mix of planned and unscheduled production orders, varying order statuses, and production uncertainties. This led to difficulties in informing the commercial team accurately of order fulfilment dates, potentially resulting in lost orders or overcommitting to capacity. 

For distribution, they had to address the challenge of predicting the mix of steel grades required for delivery to production units in six weeks, which was complicated by a mix of regular contract orders and spot orders with short lead times. The forecasting process relied on historic data and Excel-based methods, making it prone to errors and inflexible for any real-time adjustments. The process was also reliant on a single individual. 

TATA ventured into planning analytics to solve these challenges, resulting in: 

  • Multi-user applications to replace manual processes, enhancing efficiency. 
  • Teams dedicating more time to data analysis and decision-making, and reduced time on data preparation. 
  • Streamlined data collection, preparation, and presentation as a result of applying automation to this process 
  • Improved data quality as a natural byproduct. 

Expanding Horizons  

Following the successful application of planning analytics, Tata Steel UK didn’t stop there. They continued expanding their portfolio of planning analytics applications, each contributing to improved efficiency and decision-making. 

“Once you have the forecast, you are able to compare the forecast with what was actually happening to see how good your forecasts are. What are the benefits? These benefits are things that have already been delivered – multi-user applications. You go from having a kind of single person driving this planning to lots of people working on the same planning. People spending about 80% of the time analysing and making decisions versus 20% of the time preparing the data before these applications.” Brendan Hoo, TATA Steel 

The Road Ahead |Tata Steel UK’s supply change strategy is clear 

  1. Expand Applications:  Continuously add new planning analytics applications, focusing on areas where Excel-based processes hinder efficiency. 
  2. Integration:  Link applications for integrated and coordinated planning cycles.
  3. Advanced Analytics:  Explore AI forecasting and optimisation capabilities in planning analytics to enhance decision-making.
  4. Workflow:  Implement workflow processes to streamline planning analytics usage and communication.

TATA Steel UK’s Journey | Lessons Learned  

TATA has embarked on a journey, and what is evident is that the lessons they’ve learned along the way have equipped them with a resilient approach to shaping future business outcomes.

To recap they have: 

  • Overcome internal resistance through proof of concept. 
  • Built trust in planning applications among users. 
  • Balanced time spent on data preparation with time for analysis. 
  • Embraced agile development and incremental delivery. 


In conclusion, Tata Steel UK’s journey with planning analytics highlights the transformative power of intelligent data usage and planning. As the manufacturing and construction industries evolve, embracing these technologies becomes essential for staying competitive and thriving in a dynamic world. 

Solutions like IBM Planning Analytics offer an array of features, including workflow automation, self-service dashboard creation, scenario modelling, data spreading, and more. This solution prioritises self-service and ease of use, allowing models to adapt to specific requirements. It’s not just a one-size-fits-all supply chain solution; it’s a versatile modelling tool tailored to your unique needs.  IBM Planning Analytics provides a comprehensive solution to navigate the challenges of the modern manufacturing landscape. 

ON-DEMAND WEBINAR | Our customer Tata Steel UK walk us through their customer journey


About the author

Richard Abraham is an experienced sales professional, focused on the successful delivery of revenue and solutions for both clients and partners.  Supporting companies with a desire to fulfil their strategic objectives through Business Intelligence, Financial Performance Management and Insight through past, present and future data analytics

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