Shared data is only as good as the OEM-dealer relationship it travels through. Chris Bartlett, drawing on more than two decades across the automotive, truck and construction equipment sectors, has watched mandated reporting produce modified numbers - and trusted partnerships produce data both sides can act on. His conclusion: repair the relationship first, put an independent provider between the parties so nobody can reshape the numbers midstream, then do the work of turning data into intelligence.
Drawing on more than two decades in leadership positions, working across several global manufacturers and their dealer networks, Chris Bartlett has learned that shared data is only as valuable as the OEM-dealer relationship it travels through. Where that relationship is strong, data drives better decisions for everyone involved. Where it isn't, the numbers quietly bend to suit whoever is reporting them. Chris has spent 22 years coaching manufacturers and dealers, across the automotive, truck and construction equipment sectors. He has sat on the manufacturer side in several global markets and coached dealer networks at every level. He now works as an independent consultant, advising new entrants on how to take on the complicated Australian market. His central point is one that sits at the heart of trust and governance in competitive data sharing: data helps a business only when both sides trust it, and turning that data into decisions is a discipline in its own right.
Trust comes before data
Chris is clear that the quality of shared data tracks the quality of the relationship behind it, not the other way around.
"I've seen the good and the bad across various manufacturers," he says. "The best examples I've seen is where the relationship between the dealer network and the manufacturer was extremely strong. It's critical to have shared visions, shared goals, everyone working as a collective for a cohesive and collaborative partnership to be effective. The data sharing from both ways comes down to that relationship more than anything else."
Where the trust is missing, the consequences show up in the numbers themselves.
"On the other hand, I've seen the relationship be more like a parent to child relationship with authoritative power being key and the trust wasn't really there. The data was mandated to be shared, so it was a demand more than anything, and in some cases the data was modified to tell the story to match the dialogue, meaning the accuracy and the integrity of the data was compromised. At the end of the day, the data is there to produce accurate information so everybody can make the right decisions."
His first move in those situations was always the same: repair the relationship so the information could be trusted, then build from there.
Why an independent source matters
This is where a neutral provider earns its place. When the data sits with a participant who has an incentive to shape it, no one downstream can be sure what they are looking at. An independent source removes that doubt.
"The benefit I always saw with an independent provider was that it gave us a central source of truth, and there was a standard out there," Chris says. "We were comparing apples with apples when it came to what type of equipment was out there. The flow-on effect for the decisions we could make in the business was significant. We needed accuracy to make sure we were going down the right path, so having an independent was critical."
It is a strong argument for routing data access through a neutral platform rather than hand to hand between a manufacturer and its dealers. When the information cannot be touched midstream, the temptation to bend it disappears.
What good data unlocks: earning your share
Once the data could be trusted, Chris used it to make the calls that matter when a brand is finding its feet in a market: which product segments to back first, where the real demand sat and where the gaps were.
The clearest example was introducing new product lines to the Australian and New Zealand markets. "These were globally new products, so the data helped us determine, of the models that were available, what the initial opportunity was, and to make educated decisions on the total investment in parts, training and support before we brought machines in."
The same evidence helped him argue for supply. Australia and New Zealand are small markets by global volume, so local teams are often at the back of the queue for new product.
"There's a rolling assumption overseas that Australia is a huge market. It is a big geographical space, but the market is extremely condensed and highly competitive," he says. "On the other hand, Australia is one of the best proving grounds for new equipment. We're the harshest critics and the harshest users, and when managed correctly, we feed a lot of the information and solutions that improve the product for the global stage."
When a complementary product was held back for testing, Chris used market evidence to push it up the global queue. "We fought very hard to get that product into the country. The factory held off supply due to extended testing timelines, and credit to them for that. However, using the data we had, they could see the market opportunity, which helped us secure our first allocations and once arrived, helped justify a higher price point rather than the traditional entry level pricing which is hard to recover from."
That evidence also protected the business from the opposite problem - stock arrival that nobody ordered. "On occasion, the factory would simply send product to meet their export requirements. I remember dealers asking, where did these come from? We hadn't ordered them! We spent a lot of time and had some strong conversations with the factory to stop that happening, because aged stock burns a hole in any importer's back pocket. Having fresh, up-to-date product in the market was the key."
Why national averages lie
Chris is wary of any number that stops at the national line. A single growth figure can hide a market that is racing ahead in one pocket and going backwards in another. It's all to do with volume.
Drilling into the segment data, Chris could determine which categories would have the biggest impact on share balance between volume and profitability. Focusing on growing 3% in market share nationally, across all segments, only helps status. Whereas drilling down into the different machine segments and geographical regions allowed Chris and his team to determine where to allocate resource and develop the strategy to balance the impact in market share and overall profitability.
Granularity also makes dealer comparisons fair. "Understanding the market size in each region was key for us in setting dealer incentives relative to growth in their market to ensure the targets were achievable and sustainable. Having that information integrity helps with the psychological acceptance and engagement of those dealers. If you set targets based on irrelevant information for their region, they'll never achieve it. Setting realistic targets was key to acceptance and for the overall relationship. Using trusted data helped us make these smart decisions."
It is also why retail data matters more than export figures. "Export data shows you how many machines exit a country. For us as the manufacturer's representative, or the dealer, how many machines land is almost irrelevant - that's just stock levels. What we needed was retail: how many machines were genuinely being sold into the network." Reading both together also showed when the wider market was carrying excess stock and prices were likely to come under pressure.
This is the heart of working with industry market share data at the level where decisions are actually made.
From data to intelligence: aftersales and adoption
Aftersales is Chris's home ground, and the place where the difference between raw data and real intelligence is sharpest.
"Service departments need everything available immediately while realistically for parts departments, this isn't possible," he says. "Knowing where machines actually are, down to location, gives you an insight into total market size, and most importantly, where to hold parts."
Machine age changes the mix too - a one to five-year-old machine needs different parts to one that is five to ten years old - and sales data coupled with telematics and OEM resource lets you plan for that phasing rather than guess at it.
His warning is one PowerStats shares: information is not the same as insight. "Data is useless without converting it into information, and information into intelligence. A lot of manufacturers have had telematics in place for 15 years. They've got all this data, but no one knows what to do with it."
That same gap explains why dealers adopt shared data at very different speeds. "Various dealers have different appetites for it. Some are 100% sales-focused, only considering what's ahead of them. On the flip side, you get people stuck in the data with analysis paralysis." The dealers who engage are the ones who get something they can act on.
"I never send data; I send information and then coach my dealers to deliver insight. I'd say, here's what's happening, and here's what I believe could be causing these trends. It became a discussion point."
Peaks and troughs could be explained, and this insight helped identify opportunities and develop strategies to focus on. "The power of the information relies on someone being inquisitive enough to drill into it and find answers."
Key takeaways
- Data quality tracks relationship quality: mandated reporting invites midstream modification, while trust produces numbers both sides can act on.
- An independent provider gives OEMs and dealers one standard - apples with apples - that no party can reshape on the way through.
- Retail data drives decisions; export data mostly shows stock movements. Read together, they show how much stock the market is carrying.
- National averages hide the pockets that matter; segment and regional granularity shows where to put stock, dealers and support.
- Region-adjusted dealer targets earn buy-in; benchmarks built on an irrelevant market mix set dealers up to fail.
- Data pays off when it is converted into information and intelligence - and put in front of someone inquisitive enough to use it.
Frequently asked questions
Why route dealer sales data through an independent provider?
Because a central, independent standard removes the doubt. When data passes hand to hand between a manufacturer and its dealers, whoever holds it has an incentive to shape it. When it flows through a neutral platform it cannot be touched midstream, and both sides can compare apples with apples and act on the same numbers.
What is the difference between export data and retail sales data?
Export data shows how many machines left a country - effectively stock moving through the channel. Retail data shows how many machines were actually sold into the network. For an OEM representative or a dealer making stocking and investment decisions, retail is the number that matters, and reading the two together shows how much stock the wider market is carrying.
How do you set fair market share targets for dealers in different territories?
Adjust for the market mix in each region. A dealer's territory may be dominated by machine sizes or segments they cannot realistically sell, so a blanket national benchmark sets targets they will struggle to reach. Region-adjusted targets built on trusted data earn psychological acceptance and keep dealers engaged.
How does market data help with parts and service planning?
Knowing where machines are, and how old they are, points to where parts should be held and which parts to phase. A machine that is one to five years old consumes different parts to one that is five to ten years old. Combined with telematics, that location and age picture turns parts stocking from guesswork into planning.
The takeaway
Across two decades on both sides of the manufacturer-dealer relationship, Chris has arrived at the same conclusion every time: the numbers only ever reflect the health of the relationship producing them. That is not a philosophy Chris applies after the fact. It is the first thing he fixes when a relationship is underperforming. Repair the trust, and the accuracy follows.
PowerStats is built around both. We give manufacturers and their dealers a single, neutral view of the market that no participant can quietly reshape - and views that turn rows of numbers into the kind of information teams can act on. If your network is still arguing about whose numbers are right, that is the first problem worth solving - and it is one PowerStats can help you solve.
