In this article, learn about:
Why retail data gets treated as one team's tool, and what that costs
What sales, BI, planning, and leadership each ask of the same numbers
What changes when four teams share one aligned data foundation
Retail sales and inventory data usually gets filed under analytics. It arrives as a feed owned by the data team, and everyone else submits requests to view it.
That setup, however, has unintended costs. The analytics team becomes a queue, working through questions other people could answer themselves. Meanwhile, the sales manager, the inventory planner, and the account lead wait for numbers that could arrive after a long delay.
The brands that get the most from retail data are not necessarily the ones with the best tools, but rather are the ones where teams can each ask their own questions of the same numbers, with no request ticket holding things up.
However, this isn’t as easy as it might seem. Retailers report on different schedules, with different item numbers and different location structures. A comparison between two accounts means something only after that data has been aligned — which is where SPS Analytics comes in. SPS Analytics helps clean, normalize, and align retailer sales, inventory, product, and location information, so one view can serve teams asking very different things of the data.
In this article, we analyze what four different teams in one brand might ask of the same data, and what changes when each of them can ask it directly.
The Sales and Account Teams
The Questions
Sales teams usually know what shipped, but much less about what sold through. The questions they ask of the data are account specific.
How is this specific retailer actually performing?
Which items are worth pushing with this specific retailer rather than across the board?
What can be brought to a line review that the buyer will not wave off?
What They Look At
The useful measures for these teams are the ones tied to a single account.
Sell-through shows what the retailer's shoppers actually bought.
On-hand inventory and weeks of stock at that account show whether a slow week is a demand problem or a supply one.
Item-level performance at a retailer separates a product that is slow everywhere from one that is slow in a single place.
Assortment depth shows how much of the catalog the account carries, which is often where the largest gaps sit.
What Changes With SPS Analytics
Using SPS Analytics, the team arrives at buyer meetings with its own evidence instead of simply responding to the retailer's numbers. You can filter sales, inventory, sell-through, and weeks of stock to the single relevant account. Additionally, you can compare these against how they perform across the rest of the business, and assortment depth can be compared across accounts. Data can be exported for use in meeting preparation and presentations.
Sunday Golf, a lean team managing roughly 120 SKUs, found one major account carrying 14 items while another carried the full catalog across 104 locations. That difference became something the team could act on once both accounts were seen in the same view.
Business Intelligence (BI) and Analytics Teams
The Questions
The first questions for BI and analytics teams tend to be about capacity, since so much of their time is taken up by preparing the data for analysis.
How much of the week goes to cleaning retailer files rather than analyzing them?
Why does every team hold a slightly different version of the same number?
What does it take to add a retailer without rebuilding everything downstream?
What They Look At
BI and analytics teams look for item and location keys that reconcile across retailers, as well as coverage and history deep enough for a real comparison and a refresh schedule steady enough that a missing file gets flagged rather than averaged in. Most of all, they want standardized data they can work with consistently across the reporting and analysis tools their company already uses.
What Changes With SPS Analytics
SPS Analytics helps to standardize the mapping before the data reaches a dashboard, so supplier and retailer items and locations line up across accounts. Custom attributes and hierarchies let the structure follow the business rather than each retailer's filing system. The standardized foundation makes it easier to add retailers, metrics and future capabilities without requiring customers to rebuild their reporting experience.
Much of the cleanup happens upstream as well. Roughly 10-15% of weekly retailer data needs some fix before it is usable, and SPS monitors data receipt, checks for duplicates and gaps, and translates retailer language into one set of terms.
Demand Planning and Supply Chain Teams
The Questions
Planning teams work from a forecast, and a forecast is only as good as the demand signal behind it. Their questions tend to be about the gap between the plan and what is actually happening at retail.
Is the plan matching what is selling through?
Where is inventory building while demand develops somewhere else?
When supply is constrained, where should the next units go?
What They Look At
These teams often consider sell-through to be a primary signal, because it reflects what shoppers bought rather than what shipped into a retailer's network. Weeks of supply sets sell-through against the inventory already in place, separating a real demand shift from a stocking decision.
They also analyze store and SKU patterns where the retailer supplies store-level data, since a regional problem and a national one call for different responses. When units have to be split across accounts, performance by retailer, region, channel, and product is what makes the comparison possible.
What Changes With SPS Analytics
With SPS Analytics, demand planning and supply chain teams can check what sold rather than what shipped, as weeks of supply sit next to on-hand inventory and current sales. They can also spot imbalances between stock and demand while there is still time to move units or raise the issue with the retailer. That signal is an input to the forecast, not a replacement for it. SPS Analytics gives the planning team a current read on what is selling, but building the plan remains their work.
Related Reading: Why More Supply Chains Are Pairing Forecasting and Demand Sensing
Executive Leaders
The Questions
What leaders need to know is whether the process underneath the numbers is working, so their questions tend to be about timing and alignment rather than any single metric.
Are issues surfacing early enough to act on, or are we learning about them at the end of the quarter?
Are the teams working from the same numbers?
When something moves, how long before someone owns it?
What They Look At
Leaders tend to look at revenue and unit performance by retailer and by channel as the starting point, which shows which relationships are growing and which have gone flat. Sell-through across the portfolio answers whether the shoppers are buying the product, and category and brand-level views matter more than SKU detail at this level.
Leaders also pay attention to account concentration, since a business where two retailers carry most of the volume runs a different risk than one spread across twenty. Where the retailer data supports it, executives often want a year-over-year comparison and portfolio margin.
What Changes With SPS Analytics
SPS Analytics provides the measures a leader checks most often, with fills that can be filtered by retailer, product, region, and other available dimensions.
The larger change is in the meeting of the teams. When sales, planning, and analytics are working from the same aligned data, a review can start from a shared picture rather than settling whose number is right first.
What Changes When Everyone Is Using the Same Data Foundation
Four different teams will have different priorities and ask four different sets of questions. The difference is whether those questions run against one aligned dataset or four separate versions of the truth. With SPS Analytics, the questions stay different, but the answers reconcile.
The most visible difference is that meetings can start from a shared view instead of first working out whose number is right. This is made possible by standardized mapping and shared definitions, because a comparison means the same thing to everyone in the room.
and weekly for many others. Store-level visibility is available only when the retailer supplies store-level information, and margin visibility depends on retailer data or supplier-provided cost information.
Related Reading: What Are Revenue Recovery Metrics?
Where To Start With SPS Analytics
The four sections above describe the same underlying data serving an account manager, a BI lead, a planner, and an executive, each asking questions that the others may not think to ask. That is business visibility, not a reporting product for the data team.
SPS Analytics supports the investigation and supplies the evidence. The decisions stay with the teams who know the accounts, the plan, and the business.
Ready to see where your team fits? Explore the SPS Analytics use cases most relevant to your role.