Resource allocation data analysis for staffing levels

Big data analysis: Resource allocation budgets for manufacturers benefit from data about where product development occurs.


Figure 1: A cluster chart of all industries and countries shows the largest verticals in the largest country markets in the upper right. Courtesy: CambashiSoftware tools for engineering and design, such as computer-aided design (CAD), computer-aided manufacturing (CAM), computer-aided engineering (CAE), product-lifecycle management (PLM), represent a substantial market. Market figures analyzing usage and integration show more than just sales opportunities for a software tools provider. Such figures show where product development is happening and can help manufacturers interested in specific markets decide where to allocate resources.

If a business involves:

  • Components that might be selected for use in these products
  • Systems that might be chosen to manufacture these products
  • Services for distribution and maintenance.

Then figures like these can help find the development teams in software and other industries, as the following example shows.

Resource allocation can be among the more contentious issues in market planning. Country and industry managers will explain the need for more resources, often without hard data. Results can be informative but influenced by historic resources applied and the length of time they have been addressed. Newer countries or industries could be unfairly represented. An independent data source can help to avoid these problems. 

Global overview

To illustrate the need for accurate marketing data, examples are provided using a fictitious technical applications vendor. The vendor needs to decide where limited resources will be applied across target countries and industries.

Using data supplied by an independent specialist, represented in the following graphs and charts, can provide an overview of spending trends on technical applications across countries and industry sectors.

Figure 1 shows the data by country (vertical axis) and sector (horizontal axis), with data points shown in U.S. dollars. The chart has been sorted so that the biggest countries are at the top and biggest industries are on the right. The top 10% of country/industry intersections have been shaded in green.

In Figure 1, a cluster chart of industries and countries, it's no surprise to see the green area in the top right hand corner, showing the largest verticals in the largest country markets. Moving down, or left in this chart, shows the outliers, the smaller markets. For any of these to make it into the top 10%, there has to be something interesting about these markets. A couple are highlighted for later analysis.

Both examples trigger thoughts about the economy. Mining support service activities, for instance, are likely to be related to the large commodities industry in Chile. Is construction of roads and railways in Brazil just a blip triggered by the World Cup and the 2016 Olympics, or a long-term feature of the market? The chart can raise such discussions.

Figure 2: Argentina country data shows detail appropriate for a country manager. Courtesy: Cambashi

A data set of 6,000 data points is far too much detail for most planning tasks, but it is easy to simplify the data by aggregating the verticals into the higher level industry groups of interest, then only the countries of interest. 

Country summary

Country managers might want to see a simpler view of country data and target industry sectors. Figure 2 shows data for Argentina, based on the same data as Figure 1, but only 50 of 111 industry sectors have been selected and grouped into five segment definitions used by the company.

Choosing sectors that match a company's definitions is easier with 111 sectors. As shown, local currency can be used; in this case, Argentinean pesos. Forecast industry growths are shown for 2014-2015. Information in Figure 2 will allow the country manager to think about how to deploy resources. The goal is to allocate people and budgets into the right areas.

Country managers can add value knowledge of the local buying cycle, which can define roles for the in-country team.

In Argentina, automotive is second only to machinery but has the highest growth, so it seems likely to be important in the plan.

The same dataset for country managers will match the numbers shared with industry managers. 

Figure 3: Technical application software used for the automotive industry segment data can show year-over-year growth and help with resources allocation when targeting specific markets, as this example shows. Courtesy: CambashiIndustry summary

The industry managers will require a similarly simplified set of charts, in this case showing the industry segment across the target countries in Figure 3. To compare across different countries, U.S. dollars are used, rather than operational currency, to make it easier to compare absolute sizes. Currency changes can affect growth.

The automotive sector in Argentina, in Figure 2, is one of the larger sectors, with large growth. In context of other countries, it has lower growth than some and is a relatively small overall opportunity.

So it's going to be hard for Argentina to be a special focus for automotive initiatives. But the growth is high enough, and compared to other sectors in Argentina, a set of automotive industry initiatives focused on growth would make sense for Argentina.

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