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Tex-Isle Supply: becoming a data-first distributor
Tex-Isle Supply distributes energy tubulars, the pipe used in large oil rigs. It is a long established business in a sector where margin depends on holding the right inventory in the right place at the right time, and where getting that wrong is expensive in both directions. The company decided to become a data-first organisation and selected ThirdEye Data to lead that change.
LOCATION
Houston, Texas, United States
COMPANY SIZE
Mid-scale Enterprise
INDUSTRY
Energy & Utility › Explore solutions for this industry
Data lake, governance and inventory optimization
The starting position is one we see often in established businesses. Data existed in quantity but it lived in the systems that created it, on network drives, and in databases that had grown up around individual functions. Any question spanning more than one of those was answered by somebody manually, slowly, and differently each time. There was no shared basis for a decision.
The first phase built the foundation. We brought the company’s datasets together into a single lake, including everything held on network drives and in its databases, and put them through cleansing, preparation, enrichment and transformation so they could actually be used downstream rather than merely stored. Just as importantly, we defined and implemented the security structure and the governance policies, because a data lake without governance becomes an expensive place to lose things.
Later phases built on that foundation. Machine learning models now support inventory optimization, which is the commercial heart of a distribution business. Predictive maintenance serves the manufacturing division. Sales forecasting serves the sales and marketing teams. Each of those was feasible only because the first phase had been done properly.
Part of the engagement was not technical at all. We worked with employees on using the platform, because a data culture is something people practise rather than something a company installs.
More than 200 data sources brought together, ingested in batch, real time and incrementally.
Related solution: data lakes and data governance
A data lake is the easy part. Governance is what determines whether it is still useful in three years or whether it has become a swamp that people work around. The questions that matter are unglamorous: who is allowed to see what, which version of a dataset is the one to trust, what happens when a source system changes, and who is accountable when a number is wrong.
ThirdEye Data builds both together. We have done this for distribution businesses where inventory is the margin, for manufacturers, for a coaching business with two decades of accumulated customer data, and for a nonprofit whose data carries legal weight. The pattern that works is the same: establish the foundation and the rules first, prove value with one commercially important use case, then extend. The pattern that fails is building the lake, announcing it, and hoping demand appears.
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