Manufacturing, Construction and Utilities Outlook

Continued Strength in 2019

A recent Bloomberg and Institute for Supply Management study predicted that Construction and Utilities (C&U) (NAICS 2XX XXX) and Manufacturing (M) growth (3xx xxx) will continue to be the two strongest US sectors in 2019, with Services (S) growing as well but at a slower rate. This is in line with what we observed with Gazelle.ai’s GScores. We also observed a group of superstar firms leading the charge for these sectors followed by the rest of the pack.

Gazelle.ai clients can observe these results within the platform, and the method can be applied to investigate any sector of interest. This can be useful for identifying which industrial sector to target, or if you have a sector in mind you can gain insight into the relative difficulty of attracting firms from that targeted sector. The advantage of using this method, particularly without preselected sectors, is the efficiency of scheduling meetings with expanding firms. Why? Because your conversion rate will inevitably be higher when going after sectors with the highest probability of expansion.

The method entails tapping into Gazelle.ai’s Company Finder and following these steps:

  • Selecting a broad NAICS code for the sector of interest. For Construction and Utilities (C&U), that would be 2xx xxx industries.
  • Filtering the result by GScores to include only 4, 5, & 6s. The resulting number of firms may be referred to as CUFirms.
  • Selecting all GScores for C&U (we can call this CUAllFirms). The ratio of CUFirms to CUAllFirms is the share of high expansion propensity firms.
  • Comparing this ratio to other sectors by selecting new variables. For instance, for manufacturing, you would select 3xx xxx (MFirms and MUAllFirms).
  • Applying this same calculation to the broad services sector 4xx xxx to 811 999 (or any desired sub-category of services); these may be referred to as SFirms and SAllFirms.

When I ran a test, I observed that the ratio is highest for M (14%), followed by C&U (7%), with S lagging (<1%). This tells us that since M and C&U have the largest predicted shares of high expansion propensity firms, the growth potential is strongest in these two sectors. To put these numbers in context, across all US firms one would expect an expansion value in the 5% range.

For our second leaders of the pack result, the chart below highlights the C&U leaders group compared to the rest of the C&U industries. This histogram represents the unscaled expansion propensities, in the sense that they have not yet been processed through an output activation function for further use by the AI algorithm. Unscaled values are used here for expositional clarity as the output activation functions tend to squash dramatic differences. The vertical axis is the number of individual firms in an x-axis expansion propensity category; higher propensity to expand is to the right.

The results yield in econometric terms, a bimodal or two humped distribution, which typically poses problems for traditional statistics unless using kernel or some other form of step-wise regression. The right hump of firms are the superstars, and the larger left hump is the rest of the pack. This begs the question, who are these superstars?

In this right hump, representing the highest expansion propensity C&U sectors, we find mostly NACIS 211.111 – Oil and Gas Extraction, 212.111 – Mining except Oil & Gas, 213.111 – Support Services for Mining, and more broadly 2213 – Water, Sewage, and Other systems. Checking these specific industrial sectors at Gazelle.ai company finder using only NAICS codes for HQs & Subsidiaries in the US, we observe that there are only a few hits and they have all have actually expanded as predicted. If C&U is a broad sector of interest, you may have an easier time arranging meetings for the above sub-groups, compared to other C&U sectors, possibly compared to broadly defined Manufacturing, and surely compared to Services groups.

Having fun yet? 😊 A more appropriate question is what are the key take-aways? 1) If you are open to target any sector, manufacturing, followed by construction and utilities, and then services should have the greatest conversion for scheduling meetings. 2) If you are targeting a specific sector, the differences in the earlier calculated ratios give you an indication of the relative difficulty of achieving success (e.g. if you target only services you will need to reach out  >14 times more than if you target manufacturing). And, 3) For C&U, focusing on its superstars (mining, oil extraction, and water treatment sectors) are predicted and observed to be most likely to expand.

 

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