Companies and supply chains continue to face unprecedented challenges and, in some cases, unprecedented opportunities. The post-COVID-19 (if we can claim to be post COVID) “new normal” will continue to be defined by new challenges and more importantly by the ability of the supply chain executives to manage disruption and their ability to power organization strategy and growth. To be successful in this volatile environment leaders must focus on supply chain planning and more specifically Integrated Business Planning (IBP).
Traditionally, planning processes are designed to serve specific time horizons – Sales & Operations Execution (S&OE) for short term horizon, Sales & Operations Planning (S&OP) for the mid-term horizon and Integrated Business Planning (IBP) for long term strategic horizon. In its ideal form, IBP should help leaders align strategy, financial considerations, supply chain strategy to balance customer service with profits and margins. In a recent article on Forbes, Steve Banker points out that less than 25% of executives believe that their IBP process helps decision making and effective cross functional trade-offs that help the P&L of the company.
The subsequent discussion outlines what the key problems areas with the traditional approach to IBP versus a suggested approach and some of the key capabilities that an organization should look for when starting a digital transformation journey centered on IBP.
Processes vs. Decisions
The traditional approach to IBP usually consists of a monthly process & reviews consisting of multiple steps. This approach was suitable for a time where disruptions were rare, supply and demand variability were limited, and the supply chain was optimized to lower costs and low complexity. This is no longer the case, current level of volatility and complexity requires prioritizing agility and decision making over a process.
Capabilities you should be looking for to enable decision focus.
Event-driven IBP – technological capabilities to monitor internal and external events (Supply Chain Control Tower) in real time. Contextualize and quantify event impact and be able to trigger re-plan in an integrated supply chain planning solution to create an executable and feasible plan.
Composable Applications – different events or disruptions will require different set of capabilities to create a resolution. Capabilities that are structured as true SaaS microservices (and not a monoliths) will allow the creation on composable fit for purpose applications.
Process Orchestration – different stakeholders and decision makers will need to contribute analysis, approvals and decisions at different times in the decision making processes and sub-processes – this requires process orchestration that enable collaboration across multiple regions, multiple products, multiple supply chain nodes and organization levels.
Limitations in modeling the real world
Over the years products, consumers and markets have grown complex and this trend was accelerated by COVID-19 in terms how and where customers want to interact with brands and products. An increase in the focus on ESG, new intricacies of government regulations and shifting trade agreements further complicates global operations. Majority of IBP solutions in the market have significant limitations in granularity and variety of data that can be ingested and modeled – hampering the ability to model real world and leading to ineffective decision making.
Capabilities you should be looking to real world data modeling.
Modern Data Management Systems – technology capabilities that allow you pull in data at highest granularity, aggregate and disaggregate data on demand (as per the decision requirements) and make data available to different applications without data duplication (increase costs) and data latency (reduce performance) leading to scalability issues.
Extensible Logical Supply Chain Model – a logical supply chain data model that is not limited by rigid definitions but is based on industry best practices that can be extended to accommodate unique business requirements. Please note, an extensible model is different from a custom model – which are built from scratch for each implementation and require changes throughout the solution and can significantly extend implementation times and increase risk.
Digital Risk & Opportunity Framework – the ability to record, store and improve (over time) risk and opportunity assumptions with qualitative and quantitative data within the IBP solution and make available for analysis to both planners and executives.
Ineffective Scenario Planning
A limitation being able to model the real world convincingly also impacts the effectiveness of scenario planning. Most scenario planning requires a high level of manual input and processing; planners need to create multiple scenarios manually to solve one problem – this isn’t scalable when planners face multiple issues every day. With the current shortage of talent at all levels of supply chain, it is not feasible to hire more planners to solve increasing disruptions.
Capabilities you should be looking for effective scenario planning.
Automation of scenario plan creation – planners face multiple disruptions events every day; a manual scenario plan creation process cannot support decision making in any meaningful way. A planner will spend all their day just creating and running scenarios and not be in position to take a decision. Scenario plan creation should be automated based on planner selection of objective, the various parameters, and ranges for individual parameters.
AI powered scenario plan evaluation – an AI powered scenario plan evaluation solution that run and assess 100s of scenarios based on the objective and the parameters and provides recommendations and prescriptions to planners for faster and more agile decision making.
Real time simulations – in addition to automation scenario planning, organizations should also look for solutions that offer simulations and the underlying technology to run simulations in real time to further support effective decision making.
A strong and mature IBP process can significantly help organizations achieve their financial results and reduce the impact of disruptions on their supply chain and business. However, a traditional approach to IBP that is focused only on a time-bound process and deeply limited by technology short comings is no longer a value add in a volatile and complex business environment. Organizations should continue to improve on process capabilities and further enhance their IBP capabilities by creating a focus on decision making supported by the AI powered scenario planning, digital risks & opportunity framework and the ability to model the real world within their IBP solution.
Mathieu Linder is Vice President at Blue Yonder Inc. In his current role in Product Management, he leads strategic innovations programs in the supply chain planning segment with a special focus on productized AI/ML, cognitive decision making, UI/UX and SaaS platforms. Mathieu has more than 21 years of industry and supply chain experience with more than 15+ years at Blue Yonder across Product Management, Presales & Consulting.
Robin Bhatnagar is a seasoned supply chain and technology professional with over 13 years of experience is product marketing, demand generation, pre-sales and consulting. As a Product Marketing Director at Blue Yonder, Robin’s specializes in Supply Chain Planning for Discrete Manufacturing industries. Before joining Blue Yonder, Robin held several leadership positions at Bristlecone (A Mahindra Group Company) including Head of Product Marketing, pre-sales for AI & Advanced Analytics solutions and managing strategic product partnerships.
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