Written By | Progressive Grocer

How Grocers Can Leverage Technology to Make Delivery a Competitive Advantage

The grocery and retail delivery market is an industry that is poised for growth. We are in the center of online grocery shopping. Companies that position themselves at the forefront of online retail shopping and the delivery market will have a higher chance of gaining favor with consumers as the market continues to mature. Most retailers are ill-prepared to properly scale their delivery operations to handle this rapid growth.

Whether a retailer is building out in-house delivery capabilities or outsourcing to a third party, a key piece of enabling technology can make scaling their last-mile delivery operations significantly easier: delivery management software, which offers end-to-end route planning, dispatch, communication and analytics to provide their company with a top-down view of your delivery operations while helping to streamline the most important areas of those operations. Check out LS Central, the retail solution that can meet all the needs listed above. As well as Dynamics Mobile, proven solutions enabling businesses to transform their daily field operations to fully automated, connected and well-defined state-of-art business processes.

The type of software you choose should integrate seamlessly with other software solutions you are running. You may feel its necessary to consider an ERP system, like Dynamics 365 Business Central, which integrates seamlessly with LS Central for retail businesses. This will help facilitate a better experience for customers, companies, drivers, and all stakeholders in the ordering and delivery process. Specifically, delivery management can help retailers:

Ensure fast, on-time delivery with route planning/optimizing

Successful route planning relies on a sophisticated analysis of customer addresses, promised delivery times, traffic, driver schedules, vehicle capacity, and more.

With stiff competition pushing turnaround times down (2+ days, same day, within hours) and shorter delivery windows (1 hour versus 2 hours versus 3+ hours), legacy route sequencing tools can’t keep up.

A state of the art routing system can factor in these dynamic constraints, allowing a nimble organization to experiment with delivery models and service levels that filter their unique requirements. These are several essential elements:

Pick/pack & service time efficiency

A system that can rapidly generate complex routing will drive efficiencies in the pick and pack process and warehouse operations.

For example, orders can be combined by the route and staged near vehicle docks in reverse delivery order, creating a load plan that streamlines customer interactions and reduces physical effort.

Route capacity & route efficiency

A modern routing engine can improve capacity by more than 50% over manual and legacy route sequencing methods. This reduces labor and fuel costs while expanding customer servicing capability. Programmatically factoring in historical data yields and even higher efficiencies.

On-time delivery rates

On-time delivery is a key factor in customer retention. An optimized route plan is only valuable if it can accurately predict delivery times and ensure deliveries are made within the promised window.

A sophisticated ERP tool will not only provide initial estimates but also update these estimates as conditions on the ground change.

Dynamic ETAs provide drivers, dispatchers and customers with up to date, predictive information, allowing brands to take proactive steps to improve performance. Static ETAs provided from legacy systems leave brands reacting too late deliveries, with little preventing a single event from negatively affecting an entire route.

Improve driver & customer relationships with real-time communication tools

An essential part of a modern retail solution is an internal communication tool that connects dispatchers and drivers, operations and customer service, and more.

While SMS text and chat applications like Messenger, Hangouts or Slack have low barriers to entry, they lack context, adding unnecessary steps to an already complicated communication process.

But internal communication is only half of the equation – the most critical channel is with your customer. Modern consumers are accustomed to unprecedented levels of visibility into real-time delivery status. Customers expect to receive confirmation that the delivery is scheduled, when it has let for delivery, and exactly when it has arrived.

The right retail solution will provide these events and more, including intermediate time and distance-based triggers. Easy configuration and customization allow customer service and operations teams to adapt to rapidly evolving requirements without engaging in scarce development resources.

Machine learning and artificial intelligence also allow retailers to effectively look into the future with “predictive ETAs” so customers can be notified well in advance of their scheduled delivery. The most advanced delivery platforms update this prediction as real-life events change conditions on the ground, enabling a progressive and dynamic delivery estimate. Routing tools alone can’t provide this robust of an estimate as they lack visibility into what happens after the driver leaves the warehouse. Only a fully integrated system with advanced machine learning can achieve this optimal customer experience.

Finally, once delivery is complete it is critical that feedback from customers be collected quickly and efficiently. A robust retail platform must include the ability to request and review customer feedback. Including this key performance metric with other delivery analytics provides a full picture of performance and allows rapid impact analysis after operational changes. Should an issue occur, an instant feedback channel allows for service teams to resolve complaints when they happen, improving their ability to build and retain customer relationships.

Make data-backed decisions with in-depth reporting and analytics

Data-backed decisions are at the heart of any successful delivery operation. A successful, expanding delivery operation requires a clear and accurate picture of what is happening on the ground.

In a world where competitors are moving at break-neck speeds, anecdotal evidence and verbal accounts aren’t good enough. Analytics should include more than completion rates. With the right data collected, operations can measure delay rates, service times, idle vs. active driver time, mileage, batching efficiency and more. Robust filtering allows for comparison between drivers, teams, regions, and customer segments.

Technology helps level the retail delivering playing field

The cost of inaction in the retail delivery market is steep. It’s an industry where customers tend to stick with brands that they are comfortable with. With the market growing quickly, of the market share, it’s critical that small and medium-sized brands are able to secure a foothold in the retail delivery space, as it will only get tougher as time goes on.

By starting now to build relationships with customers in their local area and establishing themselves as reliable grocery delivery providers, the cost of inaction is much more than the sales retailers and grocers miss out on – it’s the market share and industry standing that will pass them by as customer habits change in the evolving retail space.

Blog Written By | Progressive Grocer

Getting Seasonal Adjustment Right in Your Inventory Purchasing

From soups to nuts, seasonal profile adjustment is an important – but often overlooked – part of inventory forecasting. Are your organization’s forecasting models keeping up?

For inventory managers, predicting sales for products with seasonal, slow or otherwise intermittent demand is notoriously challenging. In a survey of wholesale suppliers, nearly half (45%) called seasonal profile management a pain point for their businesses. From the freezer case to OTC, seasonal items make up a significant portion of SJUs, which means accurate forecasting is critical. Yet many retailers are falling short, relying on outdated methods that don’t take seasonal dips and spikes into account.

As customer demand becomes increasingly complex in today’s flexible fulfillment environment, forward-thinking organizations are turning to new tools to help solve these challenges. By embracing a data-driven approach to inventory management, retailers can predict what they once considered unpredictable and manage their entire portfolio effectively.

Outdated Tools, Unreliable Results

While new supply chain tools can help dramatically improve forecasting, many retailers haven’t yet moved beyond manual forecasting methods – or even old-fashioned gut instinct. According to the same survey noted above, half of the suppliers haven’t implemented machine learning in their forecasting yet. By depending on outdated methods, retailers face challenges like:

• Forecasts that don’t account for seasonal adjustment appropriately
• Making seasonal adjustments that don’t improve forecast accuracy
• Not being able to calculate whether a seasonal adjustment will improve accuracy

For retailers, inaccurately forecasting seasonal items means getting stuck with excess holiday baking supplies in January or Easter eggs in May. Stockpiling is a common tactic for organizations, the survey found, with more than 60% of wholesalers holding more than one month of inventory. Those high inventory levels don’t translate into higher service levels, however, with more than a quarter of organizations missing at least 4% of sales in 2019. Rather than ramping up inventory across the board, accurate forecasting requires optimizing levels by item – a practice that’s even more important for seasonal or other unpredictable products.

Going Beyond Guesswork with Machine Learning

To manage their inventory effectively, retailers first need to marry the optimal forecasting and replenishment strategy with each SKU, which requires a more advanced forecasting approach. Leveraging machine learning techniques can help retailers identify seasonal items more easily, generate more accurate forecasts and gain an edge on competitors still struggling with elementary demand models. To master seasonal profile management, here are four key areas to keep in mind.

• Determining which items to adjust. Do you know every SKU that should have a seasonal profile? The right demand classification techniques can help you understand how sales are likely to fluctuate across a wide variety of demand behaviors. Using probabilistic forecasting and advanced analytics, you can create an accurate forecasting model for each item – even the most challenging ones.
• Finding the right model. Many businesses rely on a classic exponential smoothing model to predict demand, which smooths sales activity throughout the year into a holistic forecast. But what happens if an item doesn’ have any sales for six months out of the year? Rather than smoothing periods of no sales into the forecast, which doesn’t produce the most accurate results, use advanced forecasting techniques for SKUs with intermittent demand. For example, aggregating sales to a higher level, such as category or location, can help provide a more precise forecast.
• Measuring accuracy. How confident are you that your seasonal forecasts are actually correct? Machine learning-enabled tools can help businesses remove the guesswork from seasonal adjustment. Using pattern-matching algorithms, these tools help ensure that seasonal adjustments will actually improve accuracy before making the change.
• Automating forecasts. The average retailer has thousands of SKUs, which makes it all but impossible to manually create forecasts for each seasonal product. Beyond improving accuracy, inventory forecasting tools can deliver big efficiency improvements by producing product-level forecasts, with no need for user intervention.

As technology continues to evolve, emerging techniques like unsupervised machine learning can help businesses improve accuracy further. Using near human-level intelligence, these tools can identify trends like seasonal pattern clustering, and adjust inventory levels accordingly.

For retailers just beginning to explore advanced forecasting tools, a supply chain partner can help organizations identify and implement the tools that offer the greatest value. By taking a data-driven approach to seasonal profile management, businesses can right-size inventory to meet dynamic, complex demand patterns all year long.

Contact allonline365 today to explore ways to digitally transform your business and manage your supply chain effectively. Call us on  +27 (21) 205 3650 or email info@allonline365.com.

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