MAPI Business Outlook July 2014

Thursday, July 17, 2014


Composite Index at 71, Up From 69 in March;
Most Individual Indexes Increased

Senior Financial Executives Surveyed on
Economic Indicators and Forecasts Used for Planning and Investment Decisions


Need to Know . . .

  • The Composite Business Outlook Index increased from 69 in March to 71
  • Most individual indexes showed continued improvement, including those for current orders, export orders, backlog orders, profit margins, and U.S. investment
  • The Inventory Index's decline from 66 to 59 is a positive sign in that it is a move away from potentially excess inventories and is consistent with increased shipments

This MAPI Business Outlook reflects the views of 51 senior financial executives in member companies on current and future business conditions. The questionnaire was sent out in early June and responses were due June 30, 2014.

Part I: June 2014 Survey Results

Business Indexes
The Composite Business Outlook Index increased from 69 in March to 71 in June. The composite index is well above 50, the dividing line between expansion and contraction, and points to continued expansion over the next three to six months. Further, the composite index has increased steadily over the last six quarters. Figure 1 shows the historical trend in the Composite Business Outlook Index through June 2014. The Federal Reserve’s industrial production index for the manufacturing sector (based on annualized quarterly growth rates) is also shown. In general, the latter closely tracks the Composite Business Outlook Index. A rise or fall in the composite index typically is followed by an even sharper rise or fall in the overall industrial production index for manufacturing.

Composite Business Outlook Index

Most of the indexes based on current business conditions were up in June. The Current Orders Index increased from 71 in March to 78 in June. This index is well above 50, the dividing line between expansion and contraction. The indexes for Export Orders, Backlog Orders, and Profit Margins also increased in June and are above 50. The Capacity Utilization Index slipped from 35.7% in March to 30.0% but remains close to the long-term average of 32%. The Inventory Index decreased from 66 to 59. This decline is a positive sign in that it indicates that threats of an inventory overbuild have decreased. The rise is consistent with increased shipments.

The trends in the forward looking indexes were mixed in June. The Prospective U.S. Shipments Index, based on expected shipments in the third quarter of 2014, slipped from 88 in March to 87. This index, however, remains at a very high level in absolute terms. The Non-U.S. Prospective Shipments Index declined from 81 to 76 while the Annual Orders Index fell from 89 to 81. The U.S. Investment Index jumped from 59 to 67 in June and the Non-U.S. Investment Index continued to improve, rising from 59 in March to 64. Finally, the R&D Spending Index edged down from 69 to 67.

MAPI Forecast of Economic Activity
MAPI updates its economic forecasts four times a year. The most recent (May 2014) forecasts of GDP growth and manufacturing sector growth (total and non-high-tech manufacturing) are displayed below. The forecast of an improvement in the manufacturing sector growth rate is consistent with the results in the current MAPI Business Outlook.

Forecasts of GDP and Manufacturing Sector Growth

Source(s): MAPI

Part II: Current and Forward Looking Indexes

Current Business Condition Indexes
This section presents the current business condition indexes from June 2013 to June 2014. Each is based on comparisons of responses in the current quarter with those of the same quarter one year earlier. The separating point between expansion and contraction is 50. For example, when the Current Orders Index exceeds 50, current orders are up on a year-over-year basis. The charts accompanying each table depict the historical quarterly values for that index.

Current Orders Index—Second Quarter 2014

Export Orders Index

Backlog Orders Index

Profit Margin Index

Inventory Index

The Capacity Utilization Index measures the percentage of companies operating above 85% of capacity.


Capacity Utilization Index

The distribution of companies sorted by their capacity utilization in the March and June surveys is presented in the table below.

Forward Looking Indexes
The indexes in this section are forward looking. The first two are prospective shipments indexes (U.S. and non-U.S.) and are based on a comparison of expected orders in the third quarter of 2014 with expectations of prospective shipments in the third quarter of 2013. The charts that follow each table provide a picture of the historical trends for the forward looking indexes.

Prospective U.S. Shipments Index—Third Quarter 2014

Prospective Non-U.S. Shipments Index—Third Quarter 2014

The remaining forward looking indexes are based on expectations for all of 2014 compared with 2013. Starting in September of each year, survey respondents are asked how annual orders, U.S. and non-U.S. investment, and R&D spending in the current year are expected to compare with the following year. In the current survey, for example, respondents were asked how expected annual orders in 2014 will compare with those in 2013. A comparison of these measures of activity for the same two years continues each quarter until the following September, when the years on which the comparisons are based shift forward.

The tables include responses from the September, December, and March surveys pertaining to expectations for 2014. The reference points in the charts for these indexes are based on results from each year’s June survey.

Annual Orders Index

U.S. Investment Index

Non-U.S. Investment Index

Research and Development Spending Index

Part III: Economic Indicators and Forecasts

This quarter’s wildcard questions focused on the economic indicators and forecasts used for purposes of planning and investment decisions.

  • Industry-specific forecasts and forecasts of GDP growth are the most widely followed forecasts for planning purposes. Almost two-thirds of the respondents (63%) rely on industry-specific forecasts and 57% look at forecasts of GDP growth.
  • Assessments regarding the accuracy of forecasts of U.S. economic activity over the past two years appear to be normally distributed. Twenty-three percent of the respondents said that forecasts have been fairly accurate while 17% reported that the forecasts were not very accurate. In the middle, 60% said the forecasts have been accurate some of the time but inconsistent at other times.
  • Most respondents (74%) rely on internal staff analyses when making investment decisions. Close to half (48%) use leading indicators correlated with company products while the same percentage follow statistics on current business conditions such as factories orders, auto sales, and housing starts.
  • Company factory orders are viewed as being “somewhat correlated” with government data on current business conditions by 63% of the respondents and “closely correlated” by another 6%. Close to one-third of the respondents, however, indicated that company factory orders are not very correlated with government data on current business conditions.
  • Respondents provided a broad list of leading indicators of their companies’ future business activity that staff rely on. Many of these leading indicators appear to be product-specific.
  • Despite much discussion regarding the potential of big data, 80% of the respondents said they have made littleif anyuse of big data. Sixteen percent said that they are starting to mine big data and incorporate it into their forecasts while just 4% are actively using big data.

The detailed responses to the questions on economic indicators and forecasts are as follows.

1. What forecasts of economic activity are most important for your planning purposes? (Check all that apply)


  • Housing starts (2 respondents)
  • Housing starts, municipal spending, nonresidential construction
  • Consumer spending
  • Consumer confidence; the Architecture Billings Index (ABI)
  • Medical/hospital spending
  • Non-farm payroll (especially white collar), high school and college enrollments
  • Consumer confidence, housing
  • Vehicles in operation, unemployment levels, miles driven

2. Which best describes the accuracy over the past two years of the forecasts of U.S. economic activity that you follow?

3. In making investment decisions, what economic data do you chiefly rely on? (Check all that apply)

4. How correlated are your company’s factory orders with government data on business activity?


  • We have a relatively large component of government/municipal spending that drives purchases of our products, and we correlate more closely to that activity
  • Our business lags factory order data by about six months
  • For our industrial orders, it is strongly correlated with PMI. For our medical orders, it is strongly correlated with hospital capital spending
  • We supply office and education products—education is more driven by enrollment numbers than business activity

5. What key leading indicators of your company’s future business activity do your staff rely on the most?


  • There is no published leading indicator that is correlated strongly enough with our business (and reality) to materially affect our decision-making; however, we rely on feedback from our sales force, dealers, and customers to guide expectations
  • Movements in the industrial production index
  • Forecasts from the National Electrical Manufacturers Association (NEMA)
  • Window shipments, housing starts
  • Global PMI, IPI
  • GDP
  • Machine tool consumption
  • Project pipeline and quoting activities
  • Unemployment rates, manufacturing employment, new vehicle sales
  • PMI, hospital capital spending
  • Our own backlog and order rates
  • We utilize a series of leading indicators that have been mathematically correlated to our historical ship to sales
  • Industrial production, infrastructure projects, oil and gas/petrochemical activity
  • Securities prices
  • PMI
  • AIA index, residential and nonresidential construction starts / investments and outlook, scrap steel price outlook (example sources: McGraw-Hill, Reid, IHS)
  • Power demand, natural gas prices, wind turbine development pipeline
  • Housing starts/sales
  • Housing starts, industry-specific data on refrigeration and HVAC
  • Industrial output, nonresidential expenditures (Dodge & Cox)
  • FX and commodity trends/forecasts
  • Vehicles in operation, miles driven, unemployment levels
  • Status of state budgets
  • Varies from business to business
  • CEO confidence, small business confidence, housing starts
  • Transportation and construction activity
  • Housing starts, commercial construction, rig counts for oil/gas exposure
  • Order backlogs
  • It is customer demand–driven and supported by multi-year contracts

6. Where is your company in regard to its use of big data [huge amounts of unstructured and semi-structured real-time data, much of it captured or provided by the internet] to improve upon your economic forecasts?


  • We utilize a series of leading indicators that have been mathematically correlated with our historical ratio of shipping to sales


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