In this article, learn about:
Why SPS Analytics is now Decision Intelligence
The three decisions the new experience supports at launch
What is changing in the analytics experience, and what is staying the same
Every week, someone on your team has to make a call. Do you push more inventory to a retailer or hold it for later? Should you flag a slow-moving item before the buyer does? How do you decide which region gets your limited supply? The reports these decision-makers rely on tell them what happened in the past. The difficulty lies in figuring out how to apply those lessons to the future.
That gap between knowing and deciding is why SPS Analytics is now Decision Intelligence. Analytics tells you what is happening, but Decision Intelligence is about helping you decide what to do next.
Here is what to expect from Decision Intelligence: The trusted retailer data, reporting, and cross-retailer visibility your team relies on remain in place. The experience around them, however, has been modernized. The new name more accurately describes what customers were already doing with SPS Analytics.
Why Change the Name?
SPS Analytics described the capability. Decision Intelligence describes what customers can do with it.
SPS Analytics started where most analytics products start: reports, dashboards, and cleaned-up retailer data, which was the hard part. Retail data arrives in different formats, on different schedules, with different definitions of the same metric, and must be reconciled before anyone can use the numbers. SPS helped to complete that work, and for years the name SPS Analytics matched what customers valued most.
Today, teams use their analytics solution to understand what is happening across their retail business, determine where attention is needed, and enter the next conversation with retail data they can trust. The reports are still there, but they are no longer the sole point.
SPS Commerce is focused on better reporting, and is building toward a broader goal, by helping customers make the best possible decision for their business and execute it efficiently, rather than stopping at identifying what should be done. Decision Intelligence names that full journey.
What Decision Intelligence Is
Decision Intelligence gives brands trusted retail sales, inventory, and supply chain information in a modernized experience. Teams can see how products are performing across retailers, product lines, regions, and individual stores, wherever that data is available, and use what they find to make important decisions.
The value shows up in four steps:
The platform provides data you can trust.
Trusted data becomes insight.
Insight points to a decision.
The decision produces business value.
That first step is the one most teams underestimate. Retail data is only useful if it's trusted, and trust is expensive.
SPS Commerce receives data from more than 4,000 retailers, distributors, and grocers on behalf of over 53,000 suppliers, across more than a million supply chain connections. Between 10% and 15% of that trading partner data needs intervention every week before it is fit to use. SPS handles that work so your team does not have to reconcile a mismatched file at the last minute.
What your team sees is one consistent view of retail performance. The ability to use that information to support decision-making is a large part of why the platform has a new name.
Turning Retail Data Into Action
At launch, the new analytics experience supports three core use cases. Each one starts with a question teams ask and ends with a decision they can defend.
Identify missed revenue and margin opportunities
Where is performance falling short for each product, retailer, or region, and how much of that is still recoverable?
Comparing sell-through, revenue, margin and performance across products, retailers and regions helps teams identify which gaps deserve attention and where to focus.
Improve in-stock and on-shelf availability
Where is demand showing up without product to meet it?
Store-level inventory and sell-through data can show where shelves are running empty while units sit elsewhere, helping teams decide what to replenish and where.
Inform inventory allocation strategy
Given limited supply, where should the next units go?
Weeks of stock and sell-through velocity by retailer and region give planners a defensible basis for allocation, instead of splitting inventory evenly or by whoever asked loudest.
What Sunday Golf Can Now See
Sunday Golf makes lightweight golf bags and accessories and sells through more than 1,000 retail accounts. The team uses retailer sell-through and inventory data to decide what to recommend for assortment and inventory at each account.
Sunday Golf can now see retailer-specific sell-through, inventory, and weeks-of-stock information before making a recommendation. Before, the team had to infer most of it.
Building a retail recommendation used to mean assembling the picture from whatever was available. For instance, shipment history showed what left the warehouse, not what sold. Retailer data could be requested, but those requests take time and arrive in the retailer's format. The remaining gaps were filled with assumptions.
Now the team can look at what actually sold, at which retailer, and how many weeks of stock are left, then make assortment and inventory recommendations based on that. The team can walk into a buyer meeting with the data already in hand, which changes the recommendation from something to be justified into something to be discussed.
"It's been a phenomenal tool to make decisions quicker and more efficiently and help grow our relationships with retail customers."
— Galen Brunelle, Co-Founder, Sunday Golf
What Is Changing Beyond the Name
The analytics experience has been modernized so teams spend less time getting to the data and more time acting on it.
In practice, that includes:
Faster access to data, without the legacy cube-processing delays that used to delay answers
More intuitive navigation and filtering, so finding a retailer, product, or region takes fewer steps
Personalized home-page metrics and dashboards, so the numbers each team checks first are the ones they see first
More consistent cross-retailer data through standardized canonical mapping
Exporting for further analysis, for the teams who take the data into their own tools
Integration into the SPS Commerce Platform, alongside the other solutions customers already use
A stronger technical foundation for continued development
What Is Staying the Same
The core capabilities your team relies on remain in place:
Trusted retailer data, and the data operations work behind it that makes it trustworthy
The reporting and dashboards your team runs on
Cross-retailer visibility, so performance at one account can be read against another
Exports into your existing BI tools and the workflows built around them
SPS support and the analytics experts your team already works with
This is an evolution of SPS Analytics, not an unrelated new product. The name changed because it describes the work better, not because the solution was replaced.
Where Decision Intelligence Goes From Here
"Decision Intelligence" was selected as a top-level solution name, which means it can hold additional capabilities underneath it as the solution grows.
The name is also intended to fit the whole analytics maturity journey. That journey runs from descriptive insight, which is understanding what happened, toward more advanced recommendations and action. Most organizations are somewhere along that pathway rather than at the end of it, and the same is true of analytics solutions.
The Takeaway
Decision Intelligence is the evolution of SPS Analytics. It is a name that better reflects how SPS helps customers turn trusted retail data into clearer insight and more confident business decisions.
Learn more about SPS Decision Intelligence.