In our last post, we demonstrated how Vendor Productivity Analysis enables more effective supplier benchmarking within Wireline and Perforating Services. Today, we’ll discuss how to scale this analysis across an entire activity set – this time with a focus on drilling. Our goal here is simple: help you expand your analytical reach from one category to dozens to uncover more inefficiencies and drive greater cost reduction.

How to Execute this Analysis

To conduct Vendor Productivity Analysis across all of your drilling categories, first export into a data analysis tool (e.g., Excel) your last four quarters’ spend and well data tied to drilling AFEs. Include categories, descriptions, spend amounts, suppliers, total measured depths, fields, well names, and drilling dates. Then, within and across fields, calculate the cost per drilled foot (i.e., total measured depth) for every category within every well in your dataset.

Once this is done, you can begin to make intra-field comparisons across categories to see which wells are the most and least efficient in certain areas. For instance, you might make a dollars-per-foot table like the one below:

Furthermore, you can develop composite well profiles for each of your fields by averaging, or taking the median of, category values. This will allow you to conduct the same category comparisons across fields that you did within fields:

Attacking Inefficiencies

Okay, so you know which of your wells and fields are the most and least efficient – now what? In order to drive savings through this analysis, you’ll need to investigate why certain assets are costlier on a per-unit basis. To do this, you should first compare supplier profiles within any given category across wells or fields. This will help to tease out potential lower- and higher-total-cost suppliers.

For instance, in the figure below, it appears that Supplier 3 may be driving a lower cost per foot for cementing services, given that Field 2 and Field 3’s supplier profiles are otherwise highly similar.

For certain categories with especially detailed line descriptions (usually materials, rather than services), you can take this analysis a step further by comparing item profiles within categories. OCTG is usually a good first place to look here. In the figure below, it appears that Casing Type 1 may be driving Well 4’s comparatively lower cost per foot.

Important Caveats for this Analysis

For this analysis, you should heed the same general caveats laid out in our last post on Wireline and Perforating Services:

1. If your spend data is classified inaccurately and/or vaguely, this analysis will not produce actionable results. Reach out for information on how to drive accuracy and granularity in your data.

2. If your spend data is not cleanly linked to your well data management system, this analysis will not be possible in the first place. Reach out for information on how to best link spend data to well data.

3. Make sure you capture all of your drilling spend for each well you analyze (from Spud Date to Rig Release Data).

4. Consider regional differences when conducting cross-field comparisons. For instance, there may be geophysical reasons for a higher directional drilling cost per foot, whereas there shouldn’t be for categories like cementing services.

How to Leverage the Outputs of this Analysis

Once you are confident a vendor or item set is driving a higher total cost per foot for no justifiable reason (e.g., higher quality), you should leverage the output of your analysis in future supplier negotiations. One option is to drive down your higher cost-per-foot suppliers’ prices. Another is to transfer business with these suppliers to your lower cost-per-foot suppliers. Depending on the transfer size, this may generate an added benefit of volume discounts.

Curious to learn more about Vendor Productivity Analysis? Just tell us so, and we’ll give a more in-depth overview.