There was a time when inventory management used to be as simple as tracking everything in a handwritten notebook, while auditors would go around stores manually reviewing things like on-shelf availability (OSA). However, as technology has evolved, along with consumer habits, retail supply chains have grown much larger and more complex. Supermarkets are now selling a wider variety of products than ever before, while also juggling a rising number of fulfilment options along with increasing disruption to global supply chains.
The situation has reached a point where CPG supply chains have grown ungovernably large, at least for those relying on manual processes. Fortunately, there are now ample opportunities to gather data and automate a raft of routine processes like inventory management.
Easily the biggest challenge today is making sense of these increasingly large data sets, in which data comes from multiple sources ranging from POS systems to smart store shelves equipped with RFID technology.
These challenges combined have made clear the need for CPG analytics and metrics, which transform the data into insights that drive informed decision-making. Forward-thinking retailers and suppliers are now investing heavily into platforms that use machine learning to track and make sense of CPG metrics and analytics and ensure planogram compliance.
In this post, we’ll look at which CPG and FCPG metrics and analytics you need to be tracking, and how to turn them into insights that can help maximise your return on investment.
What are CPG analytics, and why do they matter?
CPG analytics refers to the collection of data from various data points, such as point-of-sale systems and smart store shelves. In the case of traditional retailers, this is largely a matter of emulating the data-related advantages that online retailers have. After all, every digital activity generates actionable data, which is why everything starts with digitisation.
Focusing on data helps CPG retailers take the information they’re collecting and transform it into actionable information. In other words, if data refers to different points on a graph, CPG analytics are the insights you gain from looking into that graph. That’s where machine learning comes in as a way to make sense of the sheer quantity of data available.
There are three primary sources of data CPG retailers need to pay attention to:
- Activity data
Activity data refers to the actions taken by your team and your customers. For example, one data point might refer to how much time customers spend in the store, while another may refer to the actions they take – such as how long they spend looking for a particular product. Other activity metrics pertain to your team itself, such as how long it takes them to audit shelf space.
- Observational data
Observational data is the information your team records when carrying out routine operations like shelf-space auditing. Tracking observational data gives you an overall picture of how much your planogram aligns with the real state of your store shelves, for example. Among the most important CPG and FCPG metrics are those pertaining to stock levels and competitive activity.
- Sales data
Sales data refers to how many SKUs sold over a specific period of time in each store location. It’s a relatively straightforward metric to track, since your POS systems already record sales data. That said, tracking activity and observational data helps you understand the why and the how behind your sales data, thus allowing you to get to the root cause of any problems.
What are the most important CPG metrics to track?
Key performance indicators (KPIs) aren’t always universal in terms of importance, and which ones are of most value to you depends on your situation. For example, there might be some metrics that don’t align with your business goals, either directly or indirectly, in which case you can safely ignore them. It’s also important not to try to track everything, since doing so might cause you to lose your focus on what’s most important. Also, FCPG metrics differ slightly when compared to CPG metrics, simply because they have a habit of collecting more data in less time.
That said, there are certain metrics that you absolutely must track, or at least be aware of and have the infrastructure in place to collect them. Moreover, it’s important to have a framework in place for making sense of your data at scale. For example, you might measure sales by the product category, by channel or branch, or by geographical region. After all, there’s little value in consolidating and tracking all sales across dozens of branches if you don’t also have lower-level audits and reports to uncover localised opportunities and challenges.
Once you’ve established your framework for collecting data, you can start measuring the KPIs over a given timespan. Typically, this will be shorter in the case of FCPG analytics. Here are some of the most meaningful KPIs, and how you can obtain them:
- Number of SKUs sold – this is a simple and direct count of the number of SKUs sold within the report’s timeframe. This data should be recorded by your POS systems, and should be easily separable by product category, supplier, and brand.
- Sales change over time – to boost resupply efficiency and reduce wastage, you need accurate demand forecasting. Analysts should look at trends over months and years.
- Weeks of inventory on hand – according to the latest sales metrics, you should know how much stock you have left and roughly how long it will last. Also, take into account how much stock you have already on order. This data is recorded by your warehouse and supply chain management systems.
- Out-of-stock (OOS) percentage – to mitigate OOS incidents, you need to know which SKUs are routinely out of stock, and how long they’re out of stock for. Manual auditing can make this extremely time-consuming, hence the value in using smart store shelves equipped with image recognition cameras and RFID technology to capture the data.
- Inventory loss – spoilage and shrinkage are unavoidable if you sell perishable goods, but being able to account for it can help keep wastage to a minimum.
- Foot traffic – every retailer knows that more people in a store usually translates into more sales, which is why it’s such an important metric to track. You can track foot traffic by using something as simple as a clicker, or by using cameras and beacons.
- Shopper dwell time – knowing how long a shopper spends viewing a display or stays in a specific area can provide insights into the effectiveness of your product placement and store layout. This data can be collected using intelligent people-sensing units that ensure privacy while also giving you actionable CPG insights.
- Gross margins return on investment – GMROI measures your profits alongside the amount you invest in keeping your product inventory in stock. It’s more specific than regular sales and profit margins, since it tells you what’s worth keeping in stock and what isn’t. Your POS systems should collect all the data you need to obtain GMROI.
The above are some of the most important metrics that you absolutely need to track to obtain essential CPG data insights. On top of those, you’ll also want to track more general metrics that apply to any kind of business, such as average transaction value, conversion rate, and customer retention rate.
Building a cycle of continuous improvement with CPG data insights
Once you’ve collected your data, the next step is to feed it into a system that can translate it all into actionable insights. These insights will then fuel a cycle of continuous improvement. However, before that can happen, you need to connect your data sources into a platform that can overcome the challenges of scale. For this, the only practical solution is a machine learning-powered solution that provides a detailed, real-time analysis of your store environment.
That way, you can:
- Derive insights from your data. These insights are indications that there is a problem or an opportunity that you can address to have a positive impact on your CPG metrics.
- Analyse past performance to draw comparisons and formulate a long-term strategy for increasing inventory turnover, reducing OOS incidents, and minimising wastage.
- Finally, it’s time to act. At this point, your team can put your plan into motion and ensure your planogram aligns perfectly with the real situation on the retail floor.
This cyclical process is highly effective because it draws upon data rather than emotions and guesswork to drive more effective decision making.
Inspector Cloud is changing the CPG sector with its award-winning image recognition solution. Our powerful, AI-driven software slashes retail audit times, eliminates human error, and offers a detailed analysis of store efficiency. Get in touch today to find out more.