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Bu Bubb bble ba bath ths and and be better da data Getting a better understanding of replacement rate for workforce analyses 11 September 2017 Adam Barker: adam.barker@scarlatti.co.nz Hannah Binnie: hannah.binnie@scarlatti.co.nz

Di Disclaimer Access to the data used in this study was provided by Statistics New Zealand under conditions designed to give effect to the security and confidentiality provisions of the Statistics Act 1975. The results presented in this study are the work of the authors, not Statistics NZ. 2

Con ontents ts Overview of study Our approach Results I: Dairy Farming Results II: Comparison with other industries Conclusions 3

Overvie iew of of study 4

̶ ̶ ̶ ̶ ̶ Con ontext t for or this his research • Lots of organisations do workforce analyses Tertiary providers Industry groups Government departments • Used to: Create policy e.g. for immigration settings Set investment levels in tertiary training 5

An An ide deal wor orkforce is like a ni nice ce bat bath • Enough workers • With skills • With experience 6

Flows into, and out out of of, the he ba bath th Bubble bath Just one tap mix poured (cold water) right into the bath Bubble bath mix into the cold water at the tap Slow, steady heating The plug is out 7

Sou ources of of de demand in n the he wor orkforce Workf orkforce grow owth (the bathtub needs to be more full) Skill growth (need more bubble bath mix to get a frothier bath) Replacem emen ent dem demand (water, heating and soap to replace that lost down the plughole) 8

Wh What t do do we want t to to kno now? • How long do employees stay around for in an industry? • How likely are new employees to stick around? • What age are employees when they enter an industry? • How are these answers impacted by age, gender or ethnicity? 9

Our ur ap approach 10

Illustrative only (not derived from IDI data) What Wh t we are analysing Work orkforce at a po point in n time = March 2008 2008 This person works intermittently in the industry This person works continuously for 10+ years in the industry 11

Illustrative only (not derived from IDI data) Tenure as a mea measure Time to to go Time so o fa far 12

Results ts I: Da Dairy farming 13

Ho How lon ong does does it ta take som omeone to to wor ork for or 1 year? Time ta taken to to comp omplete e 12 12 mon month ths of of te tenure in n the he da dairy iry fa farm rming ind ndustry try 61% 60 60% of of new rec recruit its s are e ret retained for or less ss tha han one one year 15% 13% 5% 2% 2% 2% Never Exactly 1 1-2 2-3 3-4 4-5 5+ 1 Time ta taken (yea ears) 14

Ho How mu much ch experience does does the wor orkforce ha have? Tenure pro profi file e of of ind ndiv ividuals s in n the he da dairy ry fa farm rmin ing ind ndustr try in n 2013 2013 (% of of tota total work orkforce) 26% A flatter r pro profil file = mor more e ex experi rienced work orkforce. Stee teeper r pro profil file e = less ess ex experi rienced work orkforce. 15% 10% 8% 7% 7% 7% 5% 5% 5% 5% 0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10+ Yea ears of of ex experi rien ence 15

Illustrative only (not derived from IDI data) Segm gmentati tion of of wor orkforce “Casual segment” “Core workforce” 16

Fabricated data for illustration purposes only – this image is Replacement t rate not derived from IDI data A rate = 𝐁+𝐂 Tot otal l ne net t re replacemen ent ra 𝐁+𝐂+𝐃 B C This is the net replacement of individuals with any level of tenure so far. rate = 𝐂 Co Core e net net re replacement t ra 𝐂+𝐃 This is the net replacement of individuals that have accumulated more than one year of tenure so far. 17

Net t replacement t rates in n the he da dairy farming ind ndustr try Size e of of cor ore e work orkforce (000 000s) s) Core Cor e net net re repla lacem emen ent ra rate 40 30 20 13.7% 12.0% 11.7% 11.9% 10 0 2010 2011 2012 2013 2014 2010 2011 2012 2013 Workforce Leavers Recruits Size e of of tot total l wor orkforce (000 000s) Tot otal l ne net t re replacement t ra rate 40 33.1% 30 28.8% 28.2% 28.6% 20 10 0 2010 2011 2012 2013 2014 2010 2011 2012 2013 18

Coh ohort retention Ret eten enti tion of of ind ndiv ivid iduals ls enter erin ing the he da dairy iry fa farm rming ind ndustry ry in n the he pe peri riod 2005 2005-2015 2015 100% Thi his s is the he pro proport rtio ion of of new new ind ndiv ividuals s enter erin ing the e ind ndustry ry tha hat t go o on on to to accumula late e a given nu number of of years of of ten tenure 42% 29% 23% 18% 14% 11% 8% 5% 3% 0 1 2 3 4 5 6 7 8 9 Tenure (yea ears) 19

Ag Age at first t emp mployment Age e pro profil file of of da dairy iry fa farm rming ind ndustry try entr trants ts App pproxim imatel ely 50% 50% of of ind ndustry ry 24% 23% entr trants s are re ov over er 25 25 wh when en they hey fir irst t sta start t da dairy iry fa farm rmin ing 14% 8% 5% 5% 4% 3% 2% 1% 2% 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+ Age 20

21 Mo Month 1000 1200 1400 1600 200 400 600 800 0 th of Jan-12 of init Feb-12 nitial emp Mar-12 Apr-12 May-12 Jun-12 mployment Jul-12 Aug-12 Sep-12 Num umber Oct-12 Nov-12 er of Dec-12 of re Jan-13 recru Feb-13 ruits Mar-13 ts into Apr-13 to da May-13 dairy Jun-13 iry fa Jul-13 farm Aug-13 rming per Sep-13 Oct-13 per mon Nov-13 month Dec-13 Jan-14 th Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14

Resu sults s II: : Compa pariso son n wi with other er indus ustries es 22

Comparing te tenure pr prof ofiles be betw tween ind ndustries Dairy iry fa farm rming 26% 15% 10% 8% 7% 7% 7% 5% 5% 5% 5% 32% Beef Be f and nd shee heep 14% 9% 7% 6% 6% 6% 6% 5% 5% 5% For ores estry ry 27% 17% 11% 9% 6% 6% 5% 5% 5% 5% 4% 0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10+ Years of experience 23

Comparing te tenure pr prof ofiles of of non non-primary ry ind ndustr tries Carp Ca rpen entr try 27% 16% 10% 7% 7% 6% 6% 6% 5% 5% 5% 36% Gener Ge eral pra ractice ice me medical l serv ervice ices 11% 9% 7% 6% 6% 6% 5% 5% 4% 4% 0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10+ Years of experience 24

Con onclusions 25

So o what t ca can we con conclude from om thi his? • Tenure is a useful measure of movements to and from an industry. • We need a robust measure of replacement rate. • Retention of new recruits is low. • A large number of new recruits are aged 25+. • Further work is required to refine this measure. 26