Four steps to achieving successful demand forecasting
The Grocery Code Adjudicator states that suppliers to UK grocery retailers deserve to receive timely and accurate forecasts. Its Grocery Store Supply Code of Practice (GSCOP) defines what is expected, and its latest annual report states that all regulated retailers achieved compliance.
Despite this, forecasting remains one of the top three issues suppliers face. The report highlights suppliers reporting poor forecasts from retailers, significant variations between forecasts and orders, and penalties for failing to meet service levels.
In part, the problem lies in the lack of definition of ‘a forecast’; even GSCOP does not make clear what it means. Consider the following forecasts:
An annual prediction of the volume of every product which will be purchased from a supplier (a joint business plan?)
A 3-month prediction of weekly product sales in store (a seasonal forecast?)
A 6-week aggregate weekly order prediction
A 14-day daily prediction of short-term product sales, allowing for weather and promotions
A 7-day demand forecast (not the same as a sales forecast, and more important to a supplier). Is this by depot?
An order, for delivery tomorrow
Which of these is the ‘forecast’ that GSCOP requires retailers to share with suppliers? Which of these is the most useful to the supplier? Which should be measured against actual orders to determine ‘forecast accuracy’?
Furthermore, the GCA June 2018 publication states that:
“It was found that retailers adopted a range of approaches, and used the word “forecast” in a variety of ways. Some made a clear distinction between a forecast and an order; others did not see forecasting as a discrete activity but rather, as an integral part of supply chain management, often proceeding close to real time.”
So, how can retailers and suppliers move forward?
The GCA’s Best Practice Guide  makes 17 recommendations to improve the current process. These include:
Closer collaboration between retailers and their suppliers
Regularly reviewing forecasting performance
Ensuring that suppliers are able to get access to supply chain or buying teams to share intelligence and discuss forecasts or orders
Ensuring that retailers have adequate systems and processes which learn from and take account of known or past issues
Ensuring that suppliers are able to access adequate sales data
The 17 recommendations in the GCA Best Practice Guide are all achievable - only if both sides can make better use of available data, and are willing to share and discuss insights in an easily accessible way.
As such, there are four critical elements to accurate demand forecasting that will help retailers not only comply with GSCOP and the GCA recommendations but, as a result, help transform supply chain efficiency, availability and waste.
Data at a granular level
A forecast’s purpose is to help ensure suppliers meet order expectations, therefore it is important they receive forecast order volume at a granular level of detail:
By product (not by category, and not a total)
By day (important for short-life goods and/or just-in-time logistics)
By depot (essential for appropriate inventory in the right part of the country)
Without this, any other ‘forecast’ is at best a guide to what might be required and when, but won’t help the supplier ensure that appropriate inventory is in the right location at the right time so that orders can be fulfilled to high service-level targets (typically 98% or above).
The ability to quickly interpret data
Some suppliers have hundreds (even thousands) of products going into multiple depots each day. Not only do they need accurate data, but they need to be proactively alerted to changes in forecast.
Analysing changes is time consuming and opportunities can easily be missed. Instead, suppliers need to be able to react quickly to rectify predicted stock-outs, poorly performing promotions and dispatch issues.
The data that is supplied by retailers on a daily basis does not include alerts, analysis or trends. As a result, many suppliers have developed complex spreadsheets to extract the data and provide some analysis, but generally this relies on the knowledge of one or a few people at the supplier. Those complex spreadsheets, by their very nature, are open to error.
Data warehouse or BI software provides an alternative to spreadsheets, but the views of the data have to be specified, built and maintained, and often the knowledge is - again - held by one or a select few people in the supplier’s business. A system in place whereby state-of -the art visual analytics are presented, daily for anyone in the business to see and interact with, allows key interventions to be made with confidence and ease.
Consistency of definition
Forecasting at SKU level by location is critical to most suppliers, but forecasting at the category level may be enough for some retailers. Even those who forecast to SKU level often don’t distinguish between locations or even channels, so a forecast to a retail buyer may simply be a quantity over time, whereas a “good” forecast for suppliers is much more granular.
Retailers and suppliers may use different coding for the same SKU. Suppliers may supply in different units of measure to that used at the retail end. (Cartons instead of units, for example). Suppliers and retailers could even give different names to the delivery depots and branches. All of which make comparing retailer data difficult - both across retailers, and also with your own internal metrics and reports.
It’s really important, therefore, to be able to transform the data provided by retailer into a format that is clear to the supplier. It is only then that the business can make smart and informed decisions that will impact their business.
The ability to challenge forecasts and collaborate
Suppliers can be subject to penalties for not providing the right goods at the right time to the right place. But if the retailer forecast is so short-term or inaccurate that the supplier cannot react, then both parties have an issue. It is imperative that suppliers and retailers forge trusted partnerships which encourage mutually beneficial collaboration.
Similarly, under GSCOP rules, the “retailer must fully compensate the supplier for any cost incurred by the Supplier as a result of any forecasting error in relation to Grocery products”.
So, how should that collaboration take place?
In order for any discussions to take place between retailers and suppliers, there first has to be a trusted source of common data from which to work. In addition, that data should be “humanised” – in other words be presented in a format that is easily understood by both parties. Finally, there has to be a means of sharing that data online as the retail buyer and supplier are likely to be in different locations, which would ensure both parties are ‘singing from the same hymn sheet’.
With this shared view of the data, the supplier can help the retailer to:
Make tactical proactive decisions and interventions on orders and stock levels
Plan and optimise promotions
Review forecasts based on accurate analysis
The net result of this can be seen as:
Fewer stock-outs, improved sales for both parties
More accurate forecasting leading to less waste for both (particularly fresh produce)
Improved service levels and availability
When it comes to achieving successful demand forecasting, we need to eradicate the concept of the supplier vs the retailer. Taking a step back and looking at the bigger picture, both need to realise that it is only through fostering a mentality of genuine collaboration, that everyone can benefit. A platform which both supplier and retailer have full visibility of SKUs and access to key daily information with ease is a must. In doing so, genuine relationships can be built and changes in forecast reacted to with minimal disruption.
By using best-practice visual analytics tools and techniques, supply-chain and sales data can be blended to highlight indicators for demand (such as sales spikes, low-depot stocks etc.), and provide an easily understood picture of recent and historic sales patterns.
In an increasingly competitive retail environment, those retailers that can provide accurate forecasts to their suppliers, will benefit from more efficient supply chains, lower costs, better availability, and happier customers (and a happier Grocery Code Adjudicator).
NTT DATA Services, Remodelling Supply Chains for Resilience
Joey Dean, the man with the coolest name ever and Managing Director in the healthcare consulting practice for NTT DATA and is focused on delivering workplace transformation and enabling the future workforce for healthcare providers. Dean also leads client innovation programs to enhance service delivery and business outcomes for clients.
The pandemic has shifted priorities and created opportunities to do things differently, and companies are now looking to build more resilient supply chains, none needed more urgently than those within the healthcare system. Dean shares with us how he feels they can get there.
A Multi-Vendor Sourcing Approach
“Healthcare systems cannot afford delays in the supply chain when there are lives at stake. Healthcare procurement teams are looking at multi-vendor sourcing strategies, stockpiling more inventory, and ways to use data and AI to have a predictive view into the future and drive greater efficiency.
“The priority should be to shore up procurement channels and re-evaluate inventory management norms, i.e. stockpiling for assurance. Health systems should take the opportunity to renegotiate with their current vendors and broaden the supplier channel. Through those efforts, work with suppliers that have greater geographic diversity and transparency around manufacturing data, process, and continuity plans,” says Dean.
But here ensues the never-ending battle of domestic vs global supply chains. As I see it, domestic sourcing limits the high-risk exposure related to offshore sourcing— Canada’s issue with importing the vaccine is a good example of that. So, of course, I had to ask, for lifesaving products, is building domestic capabilities an option that is being considered?
“Domestic supply chains are sparse or have a high dependence on overseas centres for parts and raw materials. There are measures being discussed from a legislative perspective to drive more domestic sourcing, and there will need to be a concerted effort by Western countries through a mix of investments and financial incentives,” Dean explains.
Wielding Big Tech for Better Outcomes
So, that’s a long way off. In the meantime, leveraging technology is another way to mitigate the risks that lie within global supply chains while decreasing costs and improving quality. Dean expands on the potential of blockchain and AI in the industry.
“Blockchain is particularly interesting in creating more transparency and visibility across all supply chain activities. Organisations can create a decentralised record of all transactions to track assets from production to delivery or use by end-user. This increased supply chain transparency provides more visibility to both buyers and suppliers to resolve disputes and build more trusting relationships. Another benefit is that the validation of data is more efficient to prioritise time on the delivery of goods and services to reduce cost and improve quality.
“Artificial Intelligence and Machine Learning (AI/ML) is another area where there’s incredible value in processing massive amounts of data to aggregate and normalise the data to produce proactive recommendations on actions to improve the speed and cost-efficiency of the supply chain.”
Evolving Procurement Models
From asking more of suppliers to beefing up stocks, Dean believes procurement models should be remodelled to favour resilience, mitigate risk and ensure the needs of the customer are kept in view.
“The bottom line is that healthcare systems are expecting more from their suppliers. While transactional approaches focused solely on price and transactions have been the norm, collaborative relationships, where the buyer and supplier establish mutual objectives and outcomes, drives a trusting and transparent relationship. Healthcare systems are also looking to multi-vendor strategies to mitigate risk, so it is imperative for suppliers to stand out and embrace evolving procurement models.
“Healthcare systems are looking at partners that can establish domestic centres for supplies to mitigate the risks of having ‘all of their eggs’ in overseas locations. Suppliers should look to perform a strategic evaluation review that includes a distribution network analysis and distribution footprint review to understand cost, service, flexibility, and risks. Included in that strategy should be a “voice of the customer” assessment to understand current pain points and needs of customers.”
“Healthcare supply chain leaders are re-evaluating the Just In Time (JIT) model with supplies delivered on a regular basis. The approach does not require an investment in infrastructure but leaves organisations open to risk of disruption. Having domestic centres and warehousing from suppliers gives healthcare systems the ability to have inventory on hand without having to invest in their own infrastructure. Also, in the spirit of transparency, having predictive views into inventory levels can help enable better decision making from both sides.”
But, again, I had to ask, what about the risks and associated costs that come with higher inventory levels, such as expired product if there isn’t fast enough turnover, tying up cash flow, warehousing and inventory management costs?
“In the current supply chain environment, it is advisable for buyers to carry an in-house inventory on a just-in-time basis, while suppliers take a just-in-case approach, preserving capacity for surges, retaining safety stock, and building rapid replenishment channels for restock. But the risk of expired product is very real. This could be curbed with better data intelligence and improved technology that could forecast surges and predictively automate future supply needs. In this way, ordering would be more data-driven and rationalised to align with anticipated surges. Further adoption of data and intelligence and will be crucial for modernised buying in the new normal.
These are tough tasks, so I asked Dean to speak to some of the challenges. Luckily, he’s a patient guy with a lot to say.
On managing stakeholders and ensuring alignment on priorities and objectives, Dean says, “In order for managing stakeholders to stay aligned on priorities, they’ll need more transparency and collaborative win-win business relationships in which both healthcare systems and medical device manufacturers are equally committed to each other’s success. On the healthcare side, they need to understand where parts and products are manufactured to perform more predictive data and analytics for forecasting and planning efforts. And the manufacturers should offer more data transparency which will result in better planning and forecasting to navigate the ebbs and flows and enable better decision-making by healthcare systems.
Due to the sensitive nature of the information being requested, the effort to increase visibility is typically met with a lot of reluctance and push back. Dean essentially puts the onus back on suppliers to get with the times. “Traditionally, the relationships between buyers and suppliers are transactional, based only on the transaction between the two parties: what is the supplier providing, at what cost, and for what length of time. The relationship begins and ends there. The tide is shifting, and buyers expect more from their suppliers, especially given what the pandemic exposed around the fragility of the supply chain. The suppliers that get ahead of this will not only reap the benefits of improved relationships, but they will be able to take action on insights derived from greater visibility to manage risks more effectively.”
He offers a final tip. “A first step in enabling a supply chain data exchange is to make sure partners and buyers are aware of the conditions throughout the supply chain based on real-time data to enable predictive views into delays and disruptions. With well understand data sets, both parties can respond more effectively and work together when disruptions occur.”
As for where supply chain is heading, Dean says, “Moving forward, we’ll continue to see a shift toward Robotic Process Automation (RPA), Artificial Intelligence (AI), and advanced analytics to optimise the supply chain. The pandemic, as it has done in many other industries, will accelerate the move to digital, with the benefits of improving efficiency, visibility, and error rate. AI can consume enormous amounts of data to drive real-time pattern detection and mitigate risk from global disruptive events.”