In today’s retail environment, the value for brand manufacturers of using downstream data to understand true demand is becoming increasingly clear. However, implementing an effective solution to take advantage of that data is not a simple “one size fits all” decision.
Generic business intelligence tools often don’t accommodate the specific needs of consumer goods companies. Even within platforms that are more purpose-built, different metrics might be more or less important depending on a brand’s business model, and not all forecasts are created equal. There are many different solution types to choose from, not to mention the decision of whether to use an external partner like Alloy or to handle it in-house.
Even with all of this variety, there are several core characteristics that any demand management platform should have. As you evaluate different options, keep these points in mind to help guide your decision.
Most brands, regardless of how long they’ve been in business, are looking to grow market share. This growth can take several forms, including expanding to new regions, adding new product lines, increasing your employee headcount, and selling through more channels. As your brand grows in any of these ways, it’s important that your solution can easily scale alongside it. Choose a platform that will keep growing pains to a minimum — it’s a smart investment that will pay dividends now and down the road.
In our conversations with sales and operations managers at various brands, we’ve found that many times their challenge isn’t just obtaining data, but also analyzing it and identifying insights in a timely and accurate fashion. Rather than dispatching a team of analysts to crunch numbers all day, choose a solution that can take on this heavy lifting and surface insights automatically. A platform that makes smart recommendations and proactively flags potential issues and opportunities will free up your team’s time to concentrate on strategic solutions. Spend time solving the problems, not discovering them.
Not everyone in your company has a PhD in data science, but everyone can benefit from making data-driven decisions. That’s why it’s important to have a platform that is both easy to use for non-experts and robust enough for experts. You wouldn’t purchase a solution that gave results only in a foreign language and then hire one or two translators to explain everything the entire company, so don’t put your analysts or data scientists in that position by using a complex system. To take things a step further, choose a platform that’s simple for non-experts to actually work in — empower all your team members to query custom metrics and create their own data visualizations. This will improve the adoption of data-driven thinking among all business levels.
You don’t want your solution to be picky about the types of data it can ingest or the format it uses to make results available. If using the tool is perceived as too much of a hassle, team members are less likely to bother with it. The ideal platform can ingest data in any format and then automatically clean and harmonize it. You may also want your solution to integrate with your ERP, planning tools, or other supply chain systems in order to maximize the value of any insights and automate actions that meet a certain threshold. The platform you choose should ultimately make your life easier, not harder.
Unlike a jigsaw puzzle, half the fun of adopting a new solution is not assembling it yourself. Instead, look to take advantage of pre-built integrations into retailers and distributors for fast time-to-value, as well as built-in best-practice models to guide users. It should also be cloud-based, so any software updates or new features are pushed automatically, instead of requiring manual downloads. If installation or maintenance of your solution requires its own special team, it’s probably not a best-in-class platform.