In demand planning, there are many steps to take towards improving your demand planning processes, such as granularity, cycle frequency changes, and external data drivers. However, our previous article was just the beginning. More improvement options exist; here are some demand planning best practices around collaboration, exception management, segmentation, and digital transformation.
Significant improvements in demand planning can be gained by breaking internal silos and removing external barriers. Creating collaborative workflows with your partner and customer buying teams will be a huge step forward in understanding ordering patterns and processes. Encourage your partners and customers to provide their forecasts and updates in a format that can be ingested into your planning system.
The next step to consider is creating portals to your planning platform so that partners and customers can add updates directly into the system. This approach not only reduces the data integration effort but increases collaboration. Why not take the external forecasts that are trustworthy and incorporate them into your final consensus forecast?
If partners can access your system and provide forecasts that take precedence over statistical numbers or planner overrides, then why not invite your partners to collaborate with your demand reviews? This is an opportunity not just to improve your demand plans but also to improve their demand plans. Engaging and reciprocal partnerships like this can help achieve inside-out planning. These changes may only require process adjustment, not system upgrade.
Efficient planning with exception
One of the easiest ways to improve demand planning is to convert to an exception-based management approach. This requires exploiting basic User Interface capabilities such as filtering and sorting but it can also require a change of methodology and even culture.
The advice here is to stop looking at every row and column and instead focus on what has changed, what is out of tolerance, or where values are missing. Create exceptions to highlight the big over/under forecasts, trends in bias or forecast value-add. Exception management will reduce manual work for planners and save thousands of hours spent in the monthly forecasting process. The recommendation here is to use systems like o9 for generating dynamic exceptions and using advanced collaboration techniques to keep the planning team informed.
Sharper planning with segmentation
Another powerful method for creating more refined demand plans is to use segmentation which is the organization of data into groups of ‘forecastability’ such as smooth, intermittent, and volatile. These segments can be used with more appropriate forecasting methods and create better ‘best fit’ or blended statistical forecasts.
Segmentation can enhance the exception management options available to planners described above, too. Compiling planning data into forecastability groups and then further segmentation through prioritization of volume, value, and margin enables planners to focus on the data that deserves the greatest attention.
Spreadsheets are by far the most prolific planning tool on the planet. They are easy to use and are often the cornerstone of planning, from small businesses to mega-corporations, who use files for data analysis, manipulation, and reporting and as enablers for further action. This flexibility makes spreadsheets the cheap and easy data bridge between source and destination systems.
But spreadsheets are not collaborative planning tools and they are certainly not controllable. They present security risks, performance issues, formula ownership problems, and version control challenges. Spreadsheets for demand planning become bloated and desperately slow to use, cumbersome to share, and doubt will always remain about who has applied the latest updates.
Integrating or replacing spreadsheets with systems can provide efficiency and accuracy improvements, but the most impactful change is to provide planners with a tool that is specifically designed to help them create better plans. Here is where the digital transformation of planning drives improvement for demand planning teams. The advice here is to graduate from a home-cooked spreadsheet to a professional planning platform that includes dimensions, hierarchies, attributes, dashboards, model engines, calculations, and workflows, all available in a single cloud application. How do you manage a digital transformation? As o9’s co-founder and Chairman Sanjiv Sidhu said, “follow the spreadsheets.” Find out where the spreadsheets are, what they are being used for, and resolve the problems through digitization and automation.
Roles and responsibilities; education and strategy
As planning systems and data needs change, so do the roles, responsibilities, and roadmaps. These are not necessarily quick improvements but they are enablers for huge change when the time comes. Open source platforms and the exponential rise in data availability from temperature and mobility to click views and customer sentiment are offering opportunities for more bespoke statistical generation management.
For machine learning to exploit the advances in technology and information requires data scientists who understand feature engineering, segmentation, model tournaments, and engine tuning. But effective data science requires resources who know your business and industry. Data scientists can be hired, but it’s still better to educate and develop them from within the organization. This way, you retain the business culture and insight that can take an external scientist a long time to absorb. Build an education program to enable career paths for planners to become analysts and scientists.
Undertake action to begin outside-in collaboration, segmentation, and exception management approaches in your demand planning cycle, and analyze those spreadsheets and the processes they facilitate. Next, start planning the replacement of those manual files with a digital transformation program and begin the educational development of your planning resources. These changes will transform the maturity and capability of your demand planning.