Optimizing hatchery performance requires good data management. Data can be stored in various ways, ranging from simple Excel sheets to sophisticated data management software. It is also not uncommon for a large part of the hatchery’s data to still only be on paper. That's a pity, because this data is much more valuable for data analysis when it is digitally stored in the right way.

 

Basic data entries

Here we look at the most basic hatchery data collection. We assume that in each hatchery for each batch of eggs the following is known:

  • Flock number, farm, house number, flock age, breed
  • Egg production date
  • Arrival date in hatchery
  • Setting and hatch date
  • Number of eggs set
  • Number of clears detected during candling
  • Number of saleable chicks (and ideally also number of culled chicks)

 

These data can be used to calculate hatch results such as hatchability of eggs set and hatch of transfer. The data is often recorded on separate pages for each hatch day. This might be a great way to report daily production, but it does not allow for deeper analysis such as identification of the best breeder farms, effect of flock age and egg storage time on hatchability, hatchery performance compared to the previous year, comparison of incubation programs, and so on. One has to flip through endless pages and it is difficult to obtain a good overview of historical data.

 

Design data sheets

Hatchery data sheets that are generated on a daily and/or weekly basis usually have a dual purpose: they serve as data entry tables and as reports. In addition, data from different hatchery production processes and calculations are put together on one page to obtain a summarising table. Although this may seem efficient, it actually makes data management unnecessarily complex. When preparing these data for analysis you will encounter problems such as multiple data repetitions with differences in detail level, copy/paste errors and non-uniform data entries.

 

It is more convenient to separate basic data entry tables from daily or weekly summary reports. An example of a basic data entry table can be found in Table 1. As you can see, amounts (#) are used instead of calculations (%). A separate report should contain calculations, e.g. hatch of eggs set, days of egg storage, % first week mortality, and these can be generated daily or on request. Ideally, for quick analysis using a program such as Excel, data entries like those in Table 1 should be made in one large continuous file instead of a new file for each hatching day.

 

Set date

Hatch date

# Eggs

Setter

Flock ID

Breed

Flock age

Lay date

# Clears

# Saleable chicks

#
Culls

21-2-2019

14-3-2019

57600

2

56

A

45

16-2-2019

5184

49795

150

21-2-2019

14-3-2019

57600

2

41

A

47

13-2-2019

5670

48730

250

25-2-2019

18-3-2019

57600

3

23

B

35

20-2-2019

4608

51402

100

25-2-2019

18-3-2019

57600

3

14

B

36

20-2-2019

4896

51650

95

 

Table 1. Example of a format for basic hatchery data entries

 

Link files together

Very often data is scattered over several files, as it is here in Tables 1 and 2. If you take a closer look at these tables, you will see that the detail level is different. Keep the data in separate files but use a common column to link the two tables together. In this example you can link them with the ‘Hatch date’ and ‘Flock ID’ columns. 

 

 

 

Hatch date

Flock ID

Placement farm

House

# Chicks placed

#7d Mortality

14-3-2019

56

Farm B

1

20000

200

14-3-2019

56

Farm B

2

15000

75

14-3-2019

56

Farm F

1

14000

140

14-3-2019

41

Farm Y

1

35000

196

14-3-2019

41

Farm Y

2

14000

490

18-3-2019

23

Farm A

1

25000

375

18-3-2019

23

Farm A

3

24500

221

18-3-2019

14

Farm D

2

33000

297

18-3-2019

14

Farm D

3

20500

205

 

Table 2. Example of an additional data table

 

Advice

  • Make the names of the data fields consistent when using different files with overlapping data.
  • Do not combine basic data entries and daily production reports in one table.
  • Use amounts and dates when entering data; don’t enter calculations directly.
  • For simple analysis you can use Excel Pivot Tables or Graphs.