Quality control in a public company in Denmark.

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1 Quality control in a public company in Denmark. Per Andersen, Responsor A/S, Denmark When we discuss quality control in a production compagny what we often mean is that the products produced meet the requirements made. However, when we discuss quality control in a public compagny me must also look at the services rendered to the persons or companies using the public compagny. The quality measurement is performed both through questionnaires (the service part) and by extracts of the data being registered. This paper describes some of the quality requirements and how they are measured. Furthermore we will give examples of programmes that follow up on registration (or lack of registration) of data in the edp system, and give examples of how these lists are printed. One of the key words in quality control is: DO IT RIGTH THE FIRST TIME so that you do not have to do it again. Responsor is a Facility Management company in the IBM Denmark Coorporation. The staff are about 500 (1. january 1996) and the turnover i 1995 are about 400 mio. DKR. Responsors head-office are in Herlev (near Copenhagen) and we have department in Lundtofte (near Copenhagen), Hillerød (North Zealand), Aarhus (Middle-Jutland) and Aalborg (North Jutland). In the deparment of Quality and Management Information, where we use the SAS-system, we are 10 person. Responsor is certified by the ISO-9001 standard, and we are a Quality Partner to SAS Institute in Denmark. We have many customers in the Public Service in Denmark. One of our customer are Ministry of Employee, Directorate General of Employment Placment and Vocational Training (called AMS) and below here Employment service/job Centre (called AF). AMS/AF envorinment. AF has a information system where they use the SAS-system from SAS Institute, with 800 SAS-dataset, variables and about 154 mio observations. The information system is called AMI. They use an IBM ES9000/480 main-frame, with 55 RPP, 110GB disk (3380/3390), and there are about 70 SAS-users. The main-frame

2 are also used to a big transaction system (Cobol and DB2/IMS- DLI databases) call AF-Match with about users. The SAS-datasets are from to observations. All SAS-datasets are sorted by 2 or 3 values and they have 2 or 3 single index'es. Quality control This paper tells you about quality control within the job centres in Denmark. The employment service has 140 job centres across the country, which is divided into 14 regions. Each region has a quality-coordinator, who follows up on quality and makes sure the centres live up to the aims and demands from The National Labour Market Authority as well as the regional aims and demands. Quality control includes the following: 1.Lack of registration (Datadiscipline), decentral coordination concerning errors due to registrational procedures. 2.Questionnaires referring to services, these are discussed locally. 3.Centralised and decentralised sampling. 4.Central follow-up concerning paragraphs from the quality handbook. Poor registration The individual consultants working at the job centres must use the correct procedures for registration in order to passing down the best service towards unemployed workers and companies. The registration system is very complex, it holds many applications and about 1000 variables. Due to this fact, it often occurs that some variables are left missing. Partly because the consultant does not find it necessary or he does not know the particular functionalities in the system. If the registrations take place correctly, other consultants have the opportunity to make use of information, when for example they have to find the right person for a job. I will try to illustrate the above with a small case: Case 1 Per Andersen, Responsor A/S, Denmark 2

3 A company asks the job centre for a mechanic. In the database three unemployed workers would like to work in the field, but non of these workers have a qualifying education. So the job centre can not help the company. Meanwhile two out of these three unemployed workers do have the qualifying education, but this has never or incorrectly been registered in the database. WHAT CAN WE DO TO AVOID/IMPROVE THIS SITUATION? We have made programs which look upon the fit between the registered educational skills and the employment codes set by the consultants. These programs make lists containing: Social security number, name, employment code(s), etc. Lists are distributed to each job centre (to which the person is connected) Apart from this, we make weekly lists containing information about unemployed workers going for an interview at the job centre the following week, which makes it possible to update the database after the interview. This program find all person there have YES in the education field on a jobcode but the education background is not registred Develop AF: PA/RESPONSOR Develop date Last modified : PROGRAMNAME: ISCPA.TESTAF.PROGRAM(fagud01) %inc var(finddato); (find create date from contents) footnote "program: FAGUD01, ajourf &ajour"; her indtastes intervaller på fagkode husk at udfylde alle 5 cifre, og der skal være fnytter/glyffer %let stkode = '12000'; %let slkode = '12099'; her findes personer der har ja registreret i uddannelse til fagkoden data fagkode; set as1015.as1015 (keep=arcprnr arfagkd arfagudd arfagerf arfagvgt); where arfagkd between &stkode and &slkode and arfagudd = 1; her findes ud af om personen er registreret i AS1041 (tidl.udd) data harejud1; merge fagkode (in=a) as1041.as1041 (in=b keep=arcprnr); if a and not b; ej1041 = 'Nej'; label ej1041 = 'Tidligere uddannelse'; proc sort data=harejud1 nodupkey; Per Andersen, Responsor A/S, Denmark 3

4 her findes ud af om personen er registreret i ERHVUDD data harejud2; merge fagkode (in=a) erhvudd.erhvudd (in=b keep=arcprnr arerhgrp where=(arerhgrp not in(1,3))); if a and not b; ejerhv = 'Nej'; label ejerhv = 'Hovederhverv uddannelse'; proc sort data=harejud1 nodupkey; her flettes oplysningerne sammen data fagkode1; merge harejud1 harejud2; if ejerhv = ' ' then delete; her hentes oplysninger fra AS1000 data fagkode2; merge fagkode1(in=a) as1000.as1000 (keep=arcprnr cprnr arnavn arafkt araktpas arakgr in=b); if a and b; her sorteres efter arkontor proc sort data=fagkode2; by arafkt arfagkd cprnr; her dannes liste options nobyline; proc print data=fagkode2 l n width=min; where araktpas = '1'; by arafkt; pageby arafkt; var cprnr arnavn arfagkd ej1041 ejerhv; title1 "Personer der har registreret JA til uddannelse på fagkode"; title2 "og som ikke har registreret tidligere uddannelse eller"; title3 "Hovederhvervsuddannelse. Fagkodeinterval &stkode - &slkode"; title4 "Aktive personer. Udskrevet for #byline"; run; The result: Personer der har registreret JA til uddannelse på fagkode og som ikke har registreret tidligere uddannelse eller Hovederhvervsuddannelse. Fagkodeinterval '12000' - '12099' Aktive personer. Udskrevet for AF-KONTOR NR.=02000 Tidligere Hovederhverv OBS CPR-NUMMER ARBEJDSSØGENDE NAVN FAGKODE uddannelse uddannelse DONALD DUCK Nej Nej Per Andersen, Responsor A/S, Denmark 4

5 FRED FLINTSTONE Nej Nej LUCKY LUKE Nej PER ANDERSEN Nej Nej N = 4 As you see from the program above, we have used a traditional SAS-code. The hard part is getting to know how the data have been registrered and the cohorence between the variables. Questionnaires In connection with various services from the employment service to unemployed people and companies, questionnaires are handed out, which makes it possible to do a follow-up. The results are being processed with the ACCESS-, SPSS- or the SAS-system. At the offices where they use ACCESS or SPSS there is no possibility of downloading data from the employment service database. Where as at the offices they use the SAS-system they do have this opportunity which makes it possible to merge data from the questionnaires with the employment service database. Of course this gives a much better basis in decision-making. The questionnaires are being processed locally. Four times a year lists are being sent to the 14 regional offices containing information about 25 people who have received a service(s) from the employment service. These people have filled in a questionnaire themselves. The answers are processed locally. The result is handed in to The National Labour Market Authority (NLMA). The NLMA compares the 14 regional results using the ACCESS system. Central follow-up on quality Quality within the job centres is being followed by the NLMA. Each year the NLMA chooses areas which need to be looked at more closely. Programs are made on a national level as well as for each region. Sums and percentages are made to measure the areas in focus. Case 2 One area in which the quality check occurs, is if a date has been registered, showing for how long the job centre has to keep looking for a worker to a specific job with a company. Per Andersen, Responsor A/S, Denmark 5

6 Per Andersen, Responsor A/S, Denmark 6

7 / PROGRAMNAVN...: ISC.R00.HFJ.KVASTYR(RORDKVA1). PROGRAMTYPE...: Delelement til kvalitetsstyringsprojektet. PROGRAMMETS FUNKTION: At danne en table, der viser antallet af åbne ordre, hvor der er registret er bort- faldstidspunkt. UDTR#KSGRUNDLAGET...: Ordretype (kode 15). TÆLLINGSPRINCIP...: Hændelser. PROGRAM-BEMÆRKNINGER: Ingen. SPECIFIKATIONSANSVL.: 7. Kontor. UDVIKLET AF...: PA/Responsor. UDVIKLET DEN...: 26/10/94. SIDST AJOURFØRT DEN.: 02/12/94 - (HJF/AMS) PROGRAMANSVARLIG...: Teknologikontoret. AFVIKLINGSHYPPIGHED.: Kvartalsvis. LEVERS TIL...: 7. kontor. AFLEDTE VARIABLE, GENERELLE OPTIONS M.V.: / %LET STARTDT = '01apr95'D; %LET SLUTDT = '31may95'D; %INC VAR(RELLET); %inc var(finddato); / henter ajourføringsdatoen / %inc var(reluge); / henter relativ uge / %inc var(relmd); / hent relativ m}ned / %inc var(relkvt); / henter relativ kvartal / options ps=70 ls=132; / matrixprinter / options ps=72 ls=80 ; / laserprinter / options ps=66 ls=80 ; / laserprinter / options ps=72 ls=132; / laserprinter (12 cpi.) / footnote1 "Program: isc.r00.hfj.kvastyr(rordkva1), ajourf: &ajour"; P R O G R A M U D V I K L I N G E N S T A R T E R H E R F R A ; Egne formater. proc format; value $region '01' = 'København' '02' = 'Roskilde' '03' = 'Frederiksborg' '04' = 'Vestsjælland' '05' = 'Storstrøm' '06' = 'Bornholm' '07' = 'Fyn' '08' = 'Sønderjylland' '09' = 'Esbjerg' '10' = 'Vejle' '11' = 'Ringkøbing' '12' = 'Aarhus' '13' = 'Viborg' '14' = 'Nordjylland' '15' = 'Hele landet'; Her findes oplysninger fra as1100, åbne ordrer (ortilskd=15) og bortfaldstidspunkt data ordrer; set as1100.as1100 (keep=ornr ortilskd orbortdt ormoddt arregion); by ornr; kontor = substr(ornr,1,5); where ortilskd = '15' and ormoddt between &startdt and &slutdt; Per Andersen, Responsor A/S, Denmark 7

8 ordre = 1; if orbortdt ne. then bort = 1; Her tælles op hvor mange ordrer der er modtaget og hvormange der har bortfaldsdato proc means data=ordrer noprint; class kontor; var ordre bort; output out=ordrers sum=; her beregnes procenter data slut; set ordrers; kontort=put(kontor,$arafkt.); if _type_ = 0 then kontort = 'Hele regionen'; procent = bort/ordre; her dannes tabellen proc tabulate data=slut missing order=data; class kontort; var ordre bort procent; table kontort, ordref=commax8. bortf=commax8. procentf=percent8.2 /misstext='0' box='åben formidling (2).'; keylabel n = ' ' sum = ' '; label ordre = 'Modtagne ordrer ialt' bort = 'Heraf bortfalds dato' procent = 'Heraf i procent'; title1 "Antal modtagne åbne ordrer (kode 15), med bortfaldsdato."; title2 "Modtaget i perioden &ovskr"; run; The Result. Antal modtagne åbne ordrer (kode 15), med bortfaldsdato. 1 Modtaget i perioden 01/01/96-31/03/96 11:12 Monday, April 1, !Åben formidling!modtagne! Heraf!!!(2).! ordrer!bortfal-!heraf i!!! ialt!ds dato!procent!! !!kontort!!!!! !!!!!hele regionen! 338! 293! 86.69%!! !!AF-ROSKILDE! 305! 293! 96.07%!! !!AF-GREVE! 1! 0! 0!! !!AF-KØGE BUGT!!!!!POSTBOKS 150! 32! 0! 0! Per Andersen, Responsor A/S, Denmark 8

9 The results As you see from the program PROC MEANS is being used to sum up the data and a DATA STEP calculates the data. I have chosen PROC TABULATE to present the data with the help of various formats. This method makes it possible to calculate percentages on various levels as well as being 100% in control. I use _TYPE_ = 0 to calculate totals. Other programs have several columns calculating percentages, but it is extremely hard or impossible controlling percentages with a PROC TABULATE statement. Therefore I have chosen this solution. This method is also easy to explain SAS-users at the job centres. Problems Datadisciplin is one of the larger problems in connection with quality. The data are not always registered in the right manner, (the consultants have the opportunity to write text in the system too) and in some instances the consultant does not know the system well enough to live up to the standard of registration. Many consultants work in a specific area (certain groups of people or companies) and therefore have no need to work with all applications available. But when a consultant helps colleagues, due to for example absenteeism, improved registration is necessary. Education is one method for improving the registrational skills. Regularly the consultants must go through the processes and look upon several examples of poor registration. Weekly lists containing these observations will improve the quality. It must be understood by management that a more correct registration is time consuming, but will as well be a good investment in the long run. Conclusion These quality surveys have more than one aim of course. Apart from an improved registration and better service, the goal is also for the employment service to be granted an ISO-9000 Certificate. At present only one of 14 regions has the ISO Certificate. Per Andersen, Responsor A/S, Denmark 9

10 The assistance from Responsor A/S. Responsor has generated most programs concerning datadisciplin and sampling. The definitions are made by the employment service. The SAS-system from SAS Institute Inc. is used. We hold seminars in order to get a more explicit formulation of the programs needed as well as to debate information from the database. This method has shown to be particular valuable, as we, in Responsor, are not familiar with all possibilities and in the database and the SAS-users from the job centres are not all SAS-experts. This combination is for both parties ideal. During seminars we teach the SAS-users special functions from the SAS-system such as procedures, where-clauses, how to use manuals and help-functions. The close contact with the end-user is of the utmost importance in the early stage of programming. This programming takes place as PROTOTYPING, and for this the SAS-system is a splendid tool. Furthermore we hold between two and four SAS-seminars a year with the SAS-users from the job centres. Here we debate various SAS-problems, talk about new programs, exchange SASexperiences, plan workshops and of course socialize. The latter is very important in order for us to get a close contact with the SAS-user. If you are interested in further information, please contact me on the following address: Responsor A/S Att.: Per Andersen Marielundvej 46 B DK Herlev Denmark Telephone Telefax Per Andersen, Responsor A/S, Denmark 10

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