B2B Distribution Case Study4
CASE STUDY 04 · B2B DISTRIBUTION · EXECUTIVE KPI & DATA PIPELINE AUTOMATION The Board Pack Took Seven Days to Build. It Was Outdated Before Anyone Read It. A fast-growing technology products distributor had a reporting process that scaled with headcount, not data. Every board pack was seven days of manual effort. DataVines replaced the entire process with an automated pipeline that delivers board-ready KPIs every morning — built by no one.
The Challenge
Every month, the CFO and COO prepared a board pack. It covered reseller performance, subscription attach rates, pipeline health, fulfillment SLAs, and renewal tracking. Building it required pulling data from five separate systems — their distribution platform, Salesforce CRM, NetSuite ERP, a renewal tracking tool, and a vendor rebate portal — and manually assembling everything into a PowerPoint deck. The process took seven working days. Three people were involved at peak. By the time the deck was finalized, the operational data in it was between 14 and 21 days old. The CFO would present numbers in the board meeting that the COO knew were already out of date — and both of them knew it, but neither had an alternative. The board was making strategic decisions based on a picture of the business that was three weeks in the past. The renewal tracking situation was the most operationally damaging part. Subscription renewals were tracked in a standalone spreadsheet maintained by one person on the operations team. If she was out — traveling, sick, or on leave — the renewal tracking stopped. In one instance, 11 reseller account renewals expired during a two-week period when the tracker was not being actively maintained. Eight were recovered after the fact. Three were not.
The breaking points: • Seven-day manual board pack process producing data 14–21 days stale before it reached the board • Five source systems — distribution platform, Salesforce, NetSuite, renewal tracker, vendor rebate portal — with no automated connections between them • Renewal tracking dependent on one person maintaining a spreadsheet — creating a single point of failure that had already caused operational losses • No standardized KPI definitions across finance, ops, and sales — loss rates, attach rates, and renewal rates were calculated differently by each function • Leadership operating on monthly data in a business where reseller activity, fulfillment SLAs, and subscription statuses changed daily • No early warning system for underperforming reseller accounts — problems were discovered in the board pack, not before it
The DataVine Solution
The Solution
- We came in with a clear principle: every number the board sees should be produced by a system, not a person. Not faster by a person — by a system. The finance team's job was to interpret outputs and make decisions. The pipeline's job was to produce the outputs, on time, every day, without being asked. Building agreement before building anything • Ran a cross-functional definition workshop with finance, operations, and sales leadership to establish agreed methodologies for every board-level KPI — renewal rate, subscription attach rate, fulfillment SLA compliance, reseller activation rate, and nine additional metrics • Documented every definition with methodology notes, calculation logic, and data lineage so any board member — or auditor — could reproduce any number from its source data in five minutes • Established a single date logic standard across all KPIs — subscription terms use activation date, fulfillment SLAs use ship confirmation timestamp, renewals use contract expiry date, all with explicit handling rules for multi-year and auto-renew contract structures Automating the data connections • Built API integrations pulling daily data from the distribution platform (Ingram Micro API), Salesforce CRM, NetSuite ERP, the renewal tracking tool (Gainsight), and the vendor rebate portal into a centralized Google BigQuery warehouse • Built Python ETL scripts with full error handling — if any source fails, the pipeline retries automatically, logs the failure with the specific error, and sends a Slack alert to the data ops lead before anyone starts their day • Orchestrated all five pipelines through Apache Airflow with scheduled runs beginning at 3:30 AM — everything loaded into BigQuery before 5 AM, before any member of the leadership team starts their morning • Built dbt transformation models to clean and standardize raw data from each source into consistent, business-ready tables, with automated data quality checks at every layer and documented transformation logic from raw source to final metric Building the executive reporting layer • Built a Looker Studio dashboard suite with five role-based views: a CFO financial operations summary, a COO fulfillment and SLA view, a CRO reseller pipeline and renewal view, a vendor rebate tracker, and a board-ready executive summary covering all critical KPIs on one screen readable in under 60 seconds
- Built an automated monthly board pack generator that populates itself from live BigQuery data
- and is ready by the first business day of every month — no manual compilation, no PowerPoint
- assembly, no three-person coordination effort
- Built a reseller health scoring system surfacing any account with declining order frequency,
- deteriorating renewal rates, or SLA complaints — routing daily alerts to the relevant account
- manager before the account reaches the board agenda as a problem
- Replaced the standalone renewal spreadsheet with an automated renewal pipeline tracker —
- every subscription expiring in the next 90 days is visible in the dashboard, with outreach status,
- renewal probability score, and assigned owner, updated every morning
Operational Impact
The CFO described the first board meeting after go-live as the first one in two years where she walked in confident that every number was current. The board pack had generated itself the night before. She had reviewed it that morning in 90 minutes instead of coordinating seven days of effort across three people. The seven-day board pack process was retired permanently. The three team members who had been involved in building it were redeployed to actual financial and operational analysis — variance investigation, reseller profitability modelling, and vendor rebate optimisation. The finance team recovered more than 60 hours a month that had previously gone into manual report production. The renewal tracker migration had an immediate operational impact. Within the first 30 days of the automated system being live, the team identified 34 subscriptions in the 60-day renewal window that had no outreach logged. All 34 were assigned and actioned within 48 hours. The COO's comment: "We didn't change how many renewals we were winning — we just stopped losing ones we hadn't noticed."
Board pack preparation time reduced from 7 working days to 90 minutes — entirely automated
100% of board KPIs updated automatically every morning, with data current to the prior day's
close of business
Five source systems integrated into one warehouse with zero manual intervention — no exports,
no copy-paste, no format conversion
Renewal tracking converted from a single-person spreadsheet to an automated pipeline covering
all 90-day renewals with zero single points of failure
Reseller health alerts now surface account deterioration 30–45 days before it would have
appeared in a monthly report
Zero data incidents in the first 8 months post-launch — every pipeline failure caught and
recovered automatically before business hours
WHAT COMES NEXT
DataVines is now building a reseller segmentation and growth scoring model for the distributor — using order frequency, product mix, renewal rates, and support ticket patterns to classify each of the 1,100 active reseller accounts into growth, stable, and at-risk tiers. The goal is to give the account management team a daily, data-driven call list that prioritises time toward the accounts most likely to grow or most likely to churn — not the ones who emailed most recently.
Seen enough? Let's build yours. DataVines is a boutique data analytics company that builds tailored dashboards and automated data pipelines for B2B distribution companies across manufacturing, FMCG, building materials, technology, and more. W e don't do retainers without proving value first. Start with a free 5-day Proof of Concept. W e build something real with your data. You decide if it's worth continuing. www.data-vines.com Mumbai, India · Serving clients across North America & Globally
More Success Stories
Explore how we helped other brands in the B2B Services sector.
B2B Distribution: Sales & Order Intelligence
Four distribution businesses. Four data crises. How DataVines helped B2B distributors replace manual chaos with real-time intelligence — and start mak...
B2B Distribution: Marketing ROI Analytics
CASE STUDY 02 · B2B DISTRIBUTION · MARKETING ROI & TRADE SPEND ANALYTICS They Were Spending $2.1M on Trade Promotions With No Idea Which Ones Were Wo...