Decision Centric Technologies in Supply Chain

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Technology & Automation

Decision Centric Technologies in Supply Chain

The fundamentals of supply chain planning have been around for a long time. They were designed in a way that makes the process the focal point for decisions — whether through strategic planning, sales and operations planning (S&OP), or sales and operations execution (S&OE). Supply chains today need a model that aligns with the demands being placed on their organization. In response, forward-thinking supply chains are turning to decision-centric planning (DCP) for business decision-making. As per Gartner, 95% of supply chains must quickly react to changing conditions, but only 7% are able to execute decisions in real time. Our panel discussion on ‘Decision Centric Supply Chain’ explored the impact of technologies such as digital twins, AI and ML, advanced analytics, etc., for real-time decision execution roadmap. Our panelists emphasized that decision centric supply chain unlocks a new opportunity for supply-chain planners by giving them the ability to automate decisions based on business rules and strategy. Excerpts…

An interesting research by MIT Centre for Transportation & Logistics highlighted that to harness the full potential of supply chain design, organizations can rely on huge amounts of data and employ decision-making tools of various degrees of sophistication. However, that collected data is not always used to support supply chain system decision-making, and that the decision making tools that are employed vary widely across organizations. At the most basic level of decision-making maturity, relevant data is dispersed throughout the organization and basic tools (such as spreadsheet analysis) are employed.

The decision-making process is typically siloed and limited to the supply chain functions. As the decision-making maturity grows, organizations recognize the need for end-to-end decisions and cross-functional collaboration. They invest in tools that allow them to gain visibility across the organization and enable collaboration between different teams.

In highly mature decision-making environments, the research found a move toward a single data repository, which serves as a common source of truth and is embedded into more sophisticated and widely distributed planning tools. These serve as a major enabler of collaboration between different teams. Supply chain innovation design decisions are no longer confined to one part of the organization, but instead emerge from a multi-stakeholder decision-making process.

Being decision-centric means that processes are designed to create the best possible outcome for the business, involving decision-makers and other stakeholders. Decision-centric planning requires a rethink of traditional supply chain planning. Organizations must get better at taking advantage of available data, as well as advanced algorithms and other aspects of modern technologies that promise to make them more flexible and adaptable to change.

A BCG study also highlighted the power of decision centric supply chain  and stated that for companies to succeed, decision-led planning must become the organization’s drumbeat—optimizing decisions across the supply chain and orchestrating activities across functions (finance, R&D, sales and marketing, operations). Technology in supply chain management and platforms have enabled better transparency and connectivity across functions and locations; however, these enhancements are often approached as a systems transformation that is too seldom viewed as a business transformation (which needs to yield financial benefits). At the same time, digital and AI-driven algorithms hold amazing promise when it comes to driving insight to patterns and enabling faster optimization of plans but can be overwhelming in terms of the need for talent.

A Gartner study stated that decision centric planning should be supported by modern, supply chain planning technology that enables the following four capabilities:

Continuous monitoring: In order to make decisions in a timelier manner, companies must be able to quickly detect when an event occurs that requires them to act. A triggering event can be anything that has the potential to disrupt planning and requires replanning, as opposed to cyclic or batch planning that occurs at a regular frequency.

Event impact assessment: When a change in demand or supply occurs, companies must be able to assess its impact. That will guide them in deciding which process to initiate, and which people to involve. Factors to consider in the evaluation include the decision category affected, the impact radius on the supply chain, and performance targets affected by the event in question.

Impact-driven decisions: Next, consideration must be given to whether or not a change is needed — and if so, when. Companies need to weigh business supply chain management policies, rules, targets and thresholds to guide their decisions about when to take action. Based on an assessment of the decision’s urgency, they might need to initiate a process immediately — or, if the urgency level is lower, wait until a new, formal process cycle starts.

A decision-driven composable process: To increase decision-making agility and speed, processes must become more flexible as well as more frequent. This requires breaking down larger processes such as S&OP and S&OE into smaller pieces, so that new processes can be constructed. Most of these processes created on the fly will only have a lifetime equal to that of the specific decision.

According to KPMG research, Data is the key to better decision-making and there’s certainly no shortage of it. It flows in ever-greater abundance from suppliers, logistics providers, point of sale, warehouse operations, production lines and inventories, and increasingly from Internet of Things (IoT) sensors on assets and products, large or small. Some data for supply chain analysis is well structured, but much is unstructured and can overwhelm decision-makers.

Rather than receiving timely insights, they are deluged by information, which is often peripheral or irrelevant to the key decisions that drive value. On top of this, processing such a huge volume of data can also slow down systems. Cognitive decision centers (CDCs) are data rich environments that make decision making as effortless and effective as possible. They go beyond historical visualization of the supply chain to predict performance across products, suppliers, distributors, customers and more. They enable organizations to balance customer service, risk, cost and working capital decisions, using advanced simulations and modeling to identify the optimum performance trade-offs.

CDCs are focused on wide organizational goals, so that decisions — and the incentives of decision makers — are based on what is best for the enterprise. Leaders are able to gain complete supply chain visibility and the ability to make rapid informed decisions to better respond to customer needs and manage performance.

To understand the nuances better and bring to our readers a holistic guide towards adopting and deploying decision centric supply chains, we reached out to domain experts on the criticality of decision-centric supply chain. Here’s what they said…

TENETS THAT MAKE UP FOR A SUCCESSFUL DECISION-CENTRIC SUPPLY CHAIN

Anand Sharma

Anand Sharma, Transportation Technology Lead North America CS&L, Mondelez: New age solution requires integration of technologies. In the world of supply chain, any organization must deal with ERP, TMS, Planning systems like APO, Track and trace solution, Dock scheduling, Yard management, etc. For most companies, it is tough to integrate all the solutions seamlessly. It requires very careful, agile processes and small steps at a time to succeed. Change management is a big challenge and leadership should drive the technology adoption and such initiatives shouldn’t be considered IT initiatives, else there are high chances of failures.

Tannistha Ganguly

Tannistha Ganguly, Global Head - Supply Chain WMS, Kimberly-Clark: Data-driven decision-making is itself a current supply chain management trend and best practice in the industry, especially in the Supply Chain area. The key aspects that we should keep in mind while building a data-driven decision-making system in our companies are as follows:

  • It’s not about just building a tool, its more about the adoption of the philosophy or change in mindset where decision-making at all stages are backed by trustable data.
  • Often, we use our gut-feeling rather than use the data available with us when we must take a decision. While this is not wrong (because we must use our human intuition and past experiences in our decision-making process) we tend to neglect data because we do not always trust the data. So, the first step is always to get data which is massaged enough for use, and which can be trusted.
  • The systems we build that use this data is the second step which ensures that we are presented with a data that we can draw insights from when we make decision.
  • The next step will be building a framework of which decision can be made by what data.
  • Finally, ensure that we have the flexibility of building a balance between system-driven decisions and human intuition and past experiences. Over-dependence on either can give us less optimal results.
Arnab Banerjee

Arnab Banerjee, Director – Supply Chain, Smart Manufacturing & AI, Micron Technology: The key tenets of decision centric supply chain revolve around people, process, and technology. They individually have a key role to play for successful decision making. Apart from these three, access and ability to get clean and quality data and a proficient change management strategy plays a key role. All these must seamlessly come together to provide a successful and well-oiled supply chain to function and transform for further improvements. It is to be noted that people, process, and technology should not be considered separate but rather be made as a part of a holistic methodology or approach as it works out.

Mohammed Arafat Khan, Strategic Alliances and Partnerships, Intugine Technologies: A successful decisioncentric supply chain hinges on strategic supply chain management of goods, information, and resources. Key principles include data driven choices, end-to-end visibility, collaborative integration, risk mitigation, and accurate demand forecasting.

Mohammed Arafat Khan

Efficient inventory practices, agility, and technology adoption enhance adaptability. Ethical considerations, customer-centricity, and continuous improvement boost sustainability. Performance metrics, scenario planning, and skill development refine operations.

This approach forms a dynamic, customer-focused supply chain, driven by data and adaptability. 

Irfan Mulla - National Sales Head, Allcargo Supply Chain: Well, a successful decision-centric supply chain encourages cross-functional collaboration, prioritizes agility and enables data-driven decision-making.

Irfan Mulla

Real-time visibility supported by cutting-edge analytics and decision support technologies enables quick responses to changing market conditions. Resilience and performance optimization are guaranteed through continuous improvement, proactive risk management and metric alignment with strategic objectives. This strategy prioritizes customer demand, harmonizes procedures, fosters a culture of learning and encourages cross-functional alignment, laying the groundwork for a flexible, customer centric, and productive decision-centric supply chain.

Vaideeswaran Sethuraman, Founder, Param Network: A vital foundation for a successful decision-centric supply chain is digital collaboration among the ecosystem’s various participants. By creating a robust digital backbone, data collection becomes not just efficient but integral to every aspect of supply chain management.

Vaideeswaran Sethuraman

Param embodies this philosophy, offering tools to build multi-enterprise workflows for systematic data sharing. This approach ensures that every entity within the supply chain can access real time insights and act in unison, paving the way for intelligent automation and cohesive decision-making. It’s not merely about gathering data; it’s about weaving a network that connects, informs, and empowers every part of the supply chain.

This synergy transforms traditional operations into an agile, adaptive, and proactive system where decisions are not reactions but strategic responses, driven by accurate, real-time information.

BENEFITS OF DATA BASED DECISION-MAKING IN SUPPLY CHAIN & PROCUREMENT

Anand Sharma: Data-based decision making ensures better collaboration, better and accurate decisions, generate actionable insights, etc. In transport operations, you can automate the detention and demurrage invoices based on the real time events coming from carriers and track and trace solutions like Elixia, Four Kites, P44, etc. Real-time ETA can predict what order or shipment is at risk of getting timely pick up or delivery. Business partners’ performance can be measured, and any agreement breach can be predicted.

Tannistha Ganguly: There are several benefits of data-driven decision-making in supply chain & ethical sourcing. It helps us to understand our customer needs better; understand the changes in customer behavior over a period faster; allows us to unearth leakages in supply chain and helps us to optimize end-to-end supply chain and reduce supply chain risks and have early warnings for any future risks/threats. It improves transparency in supply chain processes and seam-less data flow within the supply chain systems/processes. All the above contribute to better customer servicing and better customer satisfaction.

Arnab Banerjee: There are multiple benefits like:

  • Easy and early identification of problem.
  • The data provides insights, anomalies, and trends which normal human eyes cannot catch.
    • Use of these trends or anomalies in business decision making
    • Machines do most of the bull work and help the humans in decision making.
  • Helps the management by exception cause where human intervention is only needed to manage the exception.
  • Helps to control fraud in procurement area.
  • Help to reduce costs or inventory in supply chain area.
  • Help to mitigate risk in procurement or manufacturing.
  • With the bull work being done by machines and humans managing by exception, it frees up bandwidth for employees to improve and think of next.

Mohammed Arafat Khan: Data-based decisions are transforming supply chain and procurement dynamics. Accurate demand forecasting minimizes excess stock, as seen in retailers aligning stocks with seasonal trends. Insights refine transporter relationships and mitigate risks, demonstrated by manufacturers meticulously tracking on-time deliveries to fortify partnerships and manage uncertainties. Inventory management precision is achieved through data analytics, exemplified by e-commerce platforms tailoring reorder points for optimal turnover.

Accelerated procurement processes are observed in the auto industry, where data-driven adjustments curtail lead times. Negotiation strategies reach new heights of precision through supplier cost insights, a strategic practice employed in healthcare procurement. Real-time insights into processes and inventory via data systems ensure transparency, a valuable asset in logistics achieved through GPS tracking. Route optimization significantly cuts shipping costs, as the distribution sector strategically deploys route optimization software for streamlined deliveries. Market agility finds its expression in fashion retail, aligning procurement with emergent trends. Continuous improvement, driven by data insights, elevates product quality in the electronics sector. In sum, data driven decisions revolutionize supply chain and operations management, harmonizing costs, amplifying efficiency, and nurturing innovation.

Vaideeswaran Sethuraman: Param is pioneering a transformation in digital collaboration across the supply chain ecosystem. Through our multi-enterprise workflow builder, a low-code tool designed for efficiency and flexibility, we’re empowering participants to share critical information via a unified digital backbone.

By allowing individual entities to build their own decentralized data lakes, param is laying the foundation for robust analytics and data-driven decision automation. This logistics innovations approach ensures real-time insights and actionable intelligence, connecting every part of the supply chain in a cohesive, responsive network. It’s not just about making decisions faster; it’s about making them smarter, more informed, and more aligned with the ever-changing dynamics of the business landscape.

Technologies like predictive analytics enable demand forecasting with precision, reducing overstock or shortages. Real-time tracking using IoT enhances visibility, while digital twins allow simulations and optimizations without risk. These technologies have led to concrete improvements in inventory management, delivery efficiency, and overall agility, providing a modernized, effective approach to traditional supply chain functions.

Using predictive analytics to identify potential equipment failures or demand trends leads to proactive measures and cost reductions. Real-time data in procurement ensures optimal vendor selection, dynamic pricing, and precise planning. These data-driven strategies have transformed procurement and supply chain operations, making them more streamlined, cost-effective, and adaptable to evolving business needs.

CRITICAL DECISION MAKING SKILLS & CAPABILITIES FOR PROFESSIONALS OVERSEEING A GLOBAL SUPPLY CHAIN

According to the University of University of Tennessee, there are several key decision-making skills that senior supply chain professionals need to be successful. This checklist of thirteen skills provides guidance in the decision-making process as a key stakeholder in the global supply chain:

The ability to identify problems in the supply chain: The best supply chain professionals can spot potential problems before they arise and act before they cause a major rupture in the supply chain. Since it’s not possible to see every problem in advance, you also need to be able to define problems in real time, then quickly formulate and implement solutions.

The ability to develop and communicate solutions: As a supply chain leader in your organization, you not only need to develop solutions to problems that arise, but also communicate changes in supply chain operations to all parties involved. That may mean informing and educating your team members on changes to the process. It can also mean coordinating with outside suppliers in manufacturing, transportation or warehousing. Your aptitude for clearly communicating your decisions is a key asset to your role in supply chain management.

The ability to identify trends and opportunities for greater efficiency, quality and cost savings: Supply chains are dynamic, and your leadership and decision-making process should be as well. Rather than waiting for a challenging situation to arise, keep an eye on trends in supply chain management to make sure you’re aware of current best practices. If you can spot opportunities to improve supply chain operations and create plans to take advantage of those opportunities, your team can behave proactively rather than responding reactively.

The ability to leverage data and technology to analyze problems and opportunities in the supply chain: Data is your friend in supply chain management. When your decision-making process is based on good data, you’re able to make better choices. Supply chain leaders need to stay abreast of the latest software innovations that can improve job performance and help ensure that supply chains run seamlessly.

The ability to generate or source the data you need to make well-informed decisions: Data collection is a key asset for effective decision-making and for developing longterm goals. You’ll want to set up systems that consistently collect and analyze data on the performance of various elements in your supply chain. Accurate and upto- date information is crucial to the problem-solving process and effective allocation of team resources.

The ability to incorporate legal and regulatory considerations into your decision making: Supply chain management is affected by numerous factors outside your operations and often outside your control. As a top supply chain management professional, part of your job is to stay informed about potential and actual changes to the legal and regulatory framework within which each supply chain function. Your long term goals need to account for actual and potential legal and regulatory developments, so your operations are ready to adapt to them.

The ability to synthesize ideas generated by a team and put them into action: Your team is a key asset to your decision-making process, if you know how to use it. The leadership to elicit ideas from your team, to develop the best ideas into actionable plans, and to get all team members on board with operational changes are highlevel skills that will be appreciated by your colleagues.

The ability to elicit collaboration from external elements in a supply chain: Your internal team members aren’t the only piece of the puzzle. As a supply chain professional, your skill at effectively communicating and collaborating with manufacturers, freight carriers, and fulfilment service providers is important to your success in management. People at every stage of a supply chain can be resources to help you with problem solving and implementing your decisions. Leverage your experience with third party partners to create a more robust supply chain for your organization.

The ability to recognize the relative importance of competing priorities: Supply chain managers are called upon to address more problems than they have time to resolve. That is why prioritizing is so essential to making decisions in supply chain management. You’ll have to assign relative value to competing factors in your problem-solving process. The expertise to juggle all the elements of a complex supply chain when you are weighing the pros and cons of a decision is an essential skill as a leader.

The ability to leverage information from past successes and failures to guide future supply chain management decisions: A clear-eyed assessment of past failures as well as successes will help you make betterinformed decisions about the future. It’s the key advantage of experience and will serve your team well the better you are able to draw from your professional history. But it’s important to track problems at every level of the supply chain, even those that can be fixed in the moment, so you can take steps to prevent the same issues from arising again.

The ability to be flexible to events: Thinking on your feet is a huge asset for effective decision-making. When problems arise, nimble thinking and quick decisions may be the only way to avoid interruptions in your operations that can cost money and time. Unpredictability is what makes supply chain management jobs both exciting and challenging. The better you are at making decisions on the fly, the better you can utilize the efforts of your staff and safeguard the goals of the organization.

The ability to know when to stand by a decision and when to change course: A key leadership and decision-making skill in supply chain management is discernment. The willingness to stand by a decision when you feel it’s the right one, even in the face of opposition, is an important asset in supply chain management. However, while understanding when you’ve made the wrong decision and correcting course is not always easy, it’s vital to keeping your operations running smoothly. Those who look to you for guidance will respect your ability to deal openly and honestly.

The ability to build uncertainty and contingencies into your decision-making: Disruption is, always, a fact of life. When you’re making decisions about supply chain management, the best practice is to build in margin to allow for the unforeseen. Each decision should include a backup plan in case circumstances that you can’t predict render your original plan unworkable or inefficient.

Tannistha Ganguly: Key decision making skills for any professional in the supply chain domain will be the ability to identify gaps in the end-to-end supply chain of the company; identify gaps within each specific area of the company’s supply chain, i.e., procurement, planning, logistics etc., identify how the gap or inefficiency in one specific area is affecting the efficiency or KPIs of another area within the company’s supply chain; identify trends & opportunities in supply chain; use data & technology to build solution for increased efficiency; leverage data from various sources (both internal & external) to facilitate decision-making and make well-informed decisions; engage with the human capital employed in the supply chain for improving efficiency; train & retrain/ skill and upskill the human capital in supply chain; build collaboration with external partners and build extended supply chain; build strong relations with supply chain partners; leverage advanced technology to build system that will guide future supply chain management decisions; and build uncertainty and contingencies into the decision-making process, build a flexible and agile decision-making process with added ability to change course with changing environment.

Arnab Banerjee: There are several skills which are crucial for professionals overseeing deployment of decision centric supply chain solutions, these are listed below:

  • Deep understanding of supply chain concepts
  • Knowledge and insights of business process and its pain areas
  • Comfort with data and analysis of data
  • Comfort and broad understanding of how technology can help a process.
  • Curiosity and willingness to explore and not afraid of failure
  • Ability to reframe a problem
  • Problem solving mindset
  • Excellent written and verbal communication skills
  • Transparency with all stakeholders
  • Mindset to change and reorient
  • Aware of new technology and current trends

Irfan Mulla: Driving supply chain excellence requires robust decisionmaking capabilities across various aspects of the supply chain process. Operational excellence is one of the important aspects. Operational excellence is about creating a lean, agile, and adaptable organization capable of quickly responding to changing customer demands, market conditions, and industry trends. It is a continuous journey towards perfection, rather than a one-time achievement. Developing an effective inventory management system can optimize inventory levels while considering demand variability and lead times. It is important to adopt technologies like IoT, AI, and block-chain which enhance visibility, traceability, and decision-making. Real-time data collection and analytics enable quicker and more informed decisions. 

To achieve supply chain excellence, organizations should invest in technology, data analytics, talent development, and cross functional collaboration to enhance their decision-making capabilities across these key areas.

Mohammed Arafat Khan: Professionals overseeing a global supply chain require a multifaceted skill set. They must embrace systems thinking to grasp complex interdependencies and make holistic decisions. Geo-political awareness is crucial, as global politics and trade dynamics can ripple through supply chains. End-to-end visibility, scenario planning, and diversified strategies are vital amid uncertainties. Environmental concerns mandate carbon footprint and sustainability considerations, reflecting evolving consumer preferences.

Balancing local and centralized decisions, adept relationship management across cultures, and navigating diverse regulatory landscapes are imperative. Ethical sourcing, digital integration, and resilience-versus-efficiency deliberations shape modern strategies. Feedback loops drive continuous improvement. In essence, global supply chain leaders blend strategy, geopolitics, technology, and human relations to orchestrate success.

Vaideeswaran Sethuraman: Skills like analytical thinking, adaptability, strategic planning, and technology leverage are essential in global supply chain management. Effective decision-making requires a blend of traditional business understanding with modern tools like AI and predictive analytics. Balancing global market navigation with core business values ensures leadership that’s both visionary and grounded, reflecting the complex dynamics of modern supply chain management. Achieving excellence involves integrating real-time analysis, technology, actionable strategies, and core business values. The use of predictive analytics, real-time monitoring, and digital twins fosters a supply chain that’s both forward-thinking and grounded.

These capabilities enable businesses to be resilient, efficient, and aligned with local and global dynamics, paving the way for supply chain excellence that’s adaptable, informed, and responsive.

DECISION CENTRIC TECHNOLOGIES BEING DEPLOYED TODAY

Anand Sharma: There are various technologies that are at play today. Some of them are:

Digital Twins: Digital twins create virtual replicas of physical assets, processes, or systems. They facilitate seamless visibility of the whole supply chain network without jeopardizing the base ERP or any operation systems of company.

Blockchain for Supply Chain: Blockchain technology can enhance transparency and trust in supply chains. It enables secure digital records of transactions and movements within the supply chain. It also enables the corporate and its business partner to have same view of the raw material sourcing to the vendor payment.

Supplier and customer Collaboration Portals: Many organizations use dedicated portals or platforms to communicate and collaborate with business partners.

Natural Language Processing (NLP): It is a branch of artificial intelligence (AI) that enables computers to comprehend, generate, and manipulate human language. NLP can analyze customer reviews, social media, and other textual data to extract insights about customer sentiment, preferences, and emerging trends. This information can then be used to refine demand forecasting models and adjust inventory levels, order processing, and optimize transportation accordingly.

IoT Platforms: Internet of Things (IoT) platforms enable real-time monitoring of assets like trucks, products, and equipment.

RDBMS to GRAPH database: It’s a new revolution in managing the originations database which enables millions of records to be analyzed in microseconds without having any latency issue.

Tannistha Ganguly: There are many advanced analytics technologies that are available in the market today that can be used to help us build a structured user-friendly data-driven decision making platform. We can choose from many Out-Of-The-Box (OOTB) software that is available in the market and use those as-is in our companies or tweak those to suit our needs. We can also build the capability in-house completely.

This decision depends on company to company depending on their priorities and capabilities. There is no right or wrong answer here. Few examples will be using the SAP suite of tools or the Oracle suite of tools. Or if we choose to use build inhouse, we can use analytics tools such as AWS suite, Power BI, Tableau, R, Python etc. The fundamental building blocks will be building a data warehouse and business intelligence solutions on top of it. Key point to remember is that we need to build an enterprise platform instead of point-2-point solutions. Hence, the first step will always be to build a supply chain analytics strategy before we build the tools themselves.

Arnab Banerjee: There are a lot of decision centric technologies being adopted today in supply chain. Most of it is used for data driven decision making and improvements. There are three aspects to it:

  • Intelligent automation of manual process or workflow using robotic bots is quite popular. This is popularly known as Robotic Process Automation also. This can be as simple as to check whether the report is refreshed after a scheduled job run or automation of process which were dependent on mails from one process owner to another or automation of KPI calculations.
  • Data driven approach is helping us drive many decisions based on descriptive analytics. It also helps in diagnostics purpose to find details on inventory aging or returns analysis, process throughput drops or help in disposing off unwanted inventory. The data approach is also being used with Machine Learning algorithms to predict inventory availability in downstream processes, detect patterns and anomaly in demand or historical sales or providing guidance in optimizing revenue based on available supply.
  • Use of Natural language processing to identify the right set of data in unstructured data set or for development of chat bots for internal partner interactions are some of the other areas.

Mohammed Arafat Khan: Intugine empowers decision-centric supply chains by offering real-time shipment visibility. Intugine enhances efficiency and responsiveness for agile supply chains. The platform connects with ecosystem systems and provides:

  • Predictive Analytics: Forecasts events using historical and real-time data, aiding demand, inventory, and risk management.
  • IoT: Collects real-time data via IoT devices for inventory and asset monitoring.
  • Cloud Computing: Facilitates real-time collaboration and data sharing across partners.

In the realm of supply chain, decision centric technologies yield impactful outcomes. Consider these instances:

Accurate ETA System: A prominent agrochemical manufacturer grappled with production delays and goods spoilage due to unreliable Estimated Time of Arrival (ETA). Intugine’s precise ETA system transformed their operations. With exact ETAs, the manufacturer now activates furnaces timely, reducing spoilage and optimizing production.

Detention Management: A leading glass company battled transportation delays and detention charges. Intugine intervened by ensuring SLA compliance and monitoring detention time. This data-driven approach led to a penalty system, streamlining vehicle flow within the plant and boosting efficiency.

Intugine’s data-driven insights empowered these organizations. From precise ETAs to robust detention management, the technologies ushered in efficiency and effectiveness, exemplifying the potential of decision centric supply chains.

Irfan Mulla: Best practices for implementing data-driven procurement strategies include collecting and managing data effectively, analyzing data, ensuring data quality, leveraging technology, establishing key performance indicators (KPIs), and building a data driven culture.

Vaideeswaran Sethuraman: Ensuring data integrity, embracing AI analytics, fostering collaboration, and continuous evaluation are essential. Practices like using Generative AI for complex data interpretation lead to nuanced insights and adaptable strategies. These practices form the blueprint for a responsive, visionary approach to decision-making that respects core business values while embracing modern efficiency.

OVERCOMING CHALLENGES WHILE DEPLOYING DECISION CENTRIC SUPPLY CHAIN SOLUTIONS

Arnab Banerjee: Any technology driven transformation comes with its challenges and the decision centric supply chain solutions are no different. I find there are several challenges which must be overcome for successful deployment of these solutions. These are listed below and have no order of importance:

  • Communication, clarity on purpose and people onboarding: Communication with stakeholder, having a transparency and making them a partner in the process of change is key. Similarly sharing the vision with all team members, making them feel a part of the journey and having them all to act in unison is key to success. This is possible when the shared vision and the path to achieve the vision is clear to everyone involved.
  • Breaking the siloes: Ability to break the silo and finding partnership across departments to form one team is an important aspect to bring success.
  • Data and data security: As we explore decision centric technology for solving problem or improving process, it uses more and more data to learn and aide in decision making. Access and understanding of data are very important. With open-source platforms the data compliance risk, data privacy risk and data security risk (breaches or exposures) are real threats to be cognizant of while solutioning. So, in our solutions security is predominant and uncompromisable.
  • Agility to reorient: The decision centric solution and the problem statement tend to reorient as the data analysis and patterns starts to emerge. The team needs to have the agility in the mindset to be able to re-orient, restrategize and re-group to solve the actual problem which will benefit the cause.
  • People: Identifying the right skilled and mindset people in the team is extremely important for success. This can be achieved through coaching or mentoring, training and above all respecting the team members. Employee care and mindfulness are aspects which should not be ignored and is an important key for success.

Irfan Mulla: Upskilling and training would be required for new-age technology adoption and deployment. Thus, investing in digital talent and building a pool of talent with strong prowess in technology and solutions are the need of the hour. Successful integration of new age solutions requires a transformation of security, which is a top-most challenge faced by many organizations embarking on a digital transformation journey. When we talk about new age technology solutions, we are addressing three pillars – volatility, alignment and visibility. There is anxiety within demand planning or volatility that businesses are experiencing. So, cross-functional teams need to be aligned to deploy technology for better efficiency and effectiveness. Unless all these factors are addressed on a single platform, the challenges will persist.

Recently we have faced a problem while managing in-city deliveries and the problem was related to the resistance to change when it comes to opting for a mode of transport. Because there was apprehension about delivering bad experiences to their end customers. When we started analyzing the data, we found out that 50% of their deliveries were only contributing 1% to their revenue. Rest 29 distributors were contributing 41%. 

That’s the power of data we are talking about. One of the biggest findings which I have seen in my 3PL career of around 18 years is that we need to have a lot of integration and standardization of the processes which will help us plan better, design better and be futuristic.

EMBRACING THE CHANGE

Traditional cyclic planning has played an important role in helping companies in the early stages of maturity to create processes that are leaner, faster, standardized and less resource heavy. But the ultimate goal is even more ambitious. In today’s volatile environment, companies need planning concepts powered by strong technology support and focused on decisions. By using decision centric planning, supply chains can become more resistant to volatility and changing conditions.

As Mohammed Arafat Khan highlights, “In the realm of supply chain and procurement, data-driven decisionmaking is underpinned by essential practices. Clear objectives guide efforts, while relevant data types inform choices. Data integrity is key, demanding robust validation. Integration synthesizes insights, and advanced analytics techniques uncover hidden patterns. Real-time monitoring of indicators ensures agility, and visual dashboards aid comprehension. Cross-functional collaboration enhances decision quality. Segmentation tailors strategies, and scenario planning charts diverse paths. A culture of refinement and data security are vital. Skill development equips teams, while validation and outcome monitoring refine strategies. Aligning decisions with business strategy ensures coherence. These practices empower organizations to harness data’s transformative potential, elevate operations, foster innovation, and secure a competitive edge.”

As more companies begin to augment and automate supply chain decision making, they’ll begin to see the benefits throughout their enterprise ecosystem — with a level of visibility that goes beyond planning. This investment can scale beyond the business to enable resource optimization, waste reduction, improved customer service and more.

Companies will benefit within mere weeks by reducing complexity and accelerating their decision cycles, while simultaneously reducing their reliance on multiple people, processes, data models and disconnected niche technology investments. Early adoption of decision intelligence will pay dividends by enabling companies to address problems and make decisions they couldn’t consider before or didn’t think were possible with the status quo.

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