Desenvolvimento e aplicação de uma métric=
a de
avaliação da prestação de serviço de um órgão público federal
Development and application of a producti=
vity
evaluation metric for the provision of service of a federal public agency
Antônio Maria de Carv=
alho
Negrão <=
span
style=3D'mso-bookmark:_Hlk60668720'>
https://orcid.org/0009-0007-135=
3-2275
=
Mestre em Gestão e
Estratégia. Universidade Federal do Rio de Janeiro / Programa de
Pós-Graduação em Gestão e Estratégia (UFRRJ/PPGE) – Brasil. negraofilho@gmail.com .
Daniel Ribeiro de
Oliveira
https://orcid.org/0000-0002-878=
7-8320
Doutor
em Economia. Universidade
Federal do Rio de Janeiro / Programa de
Pós-Graduação em Gestão e Estratégia (UFRRJ/PPGE) – Brasil.
Daniel.eco@uol.com.br
Fabrício Molica de
Mendonça
https://orcid.org/0000-0001-890=
9-6843
Doutor
em Engenharia de Produção. Universidade Federal de São João Del Rei (UFDJ=
) –
Brasil. fabriciomolica@ufsj.edu.br
Saulo Barbara de Oliv=
eira
http://orcid.org/0000-0002-9424=
-5425
Doutor
em Engenharia de Produção. Universidade Federal do Rio de Janeiro / Progr=
ama
de Pós-Graduação em Gestão e Estratégia (UFRRJ/PPGE) – Brasil.
saulobarbar@gmail.com
Geferson Michel Santo=
s de
Sales
https://orcid.org/0009-0009-443=
2-0982
Mestre
em Gestão e Estratégia. Universidade Federal do Rio de Janeiro / Programa=
de
Pós-Graduação em Gestão e Estratégia (UFRRJ/PPGE) – Brasil. g efersonpmm@gmail.com
RESUMO
Um dos=
objetivos
estratégicos do Instituto Nacional do Seguro Social (INSS) é atender bem aos
cidadãos e melhorar a sua produtividade, reduzindo a extensa fila de
requerimentos que aguardam análise e conclusão. Para isso, foi proposto o
desenvolvimento e aplicação de uma métrica para mensurar a produtividade e a
eficiência da prestação dos seus serviços e auxiliar no processo de gestão e
tomada de decisões. Trata-se de uma pesquisa qualitativa e quantitativa,
exploratória, descritiva e aplicada, utilizando métodos como observação
participante, revisão bibliográfica e análise documental. A coleta de dados=
foi
realizada ao longo do período de julho de 2022 a junho de 2023. Para aplica=
r a
métrica proposta foram selecionados os seguintes indicadores de desempenho:
Tempo Médio de Concessão (TMC), o Tempo de Espera de Atendimento Agendado
(TMEA), o percentual de processos reabertos (SUPERTEC), e as manifestações
respondidas no prazo legal (Ouvidoria). <=
/span>Ao
longo do período analisado evidenciou-se aumento na pontuação total da
produtividade do INSS tanto em nível nacional, quanto estadual, apresentando
tendências crescentes, demonstrando o esforço no cumprimento de estratégias
destinadas à melhoria no atendimento. As principais vantagens da aplicação =
da
métrica proposta são: possibilitar o monitoramento da fila de requerimentos=
dos
beneficiados da INSS de forma proativa; servir de instrumento gerencial par=
a a
medição, avaliação, análise e comparação do desempenho dos serviços prestad=
os
pelo INSS ao longo do tempo; e dar suporte e sustentabilidade à tomada de
decisão sobre a aplicação de medidas preventivas e corretivas visando a
melhoria do atendimento dos beneficiários da instituição estudada.
Palavras-chave: métrica
de produtividade; medição e avaliação do desempenho; melhoria do atendiment=
o;
serviço público; INSS.
<=
/o:p>
ABSTRACT
One of the strategic objectives of the INSS (the brazilian institute=
of
social security) is to provide excellent service to citizens and enhance
productivity, aiming to alleviate the backlog of processes awaiting analysis
and resolution. The development and implementation of a metric to measure t=
he
productivity and efficiency of service provision were proposed, aiming to
assist in the management and decision-making processes. This is a qualitati=
ve
and quantitative, exploratory, descriptive, and applied research utilizing
methods such as participant observation, literature review, and document
analysis. Data collection was conducted from July 2022 to June 2023. To app=
ly
the proposed metric, the following performance indicators were selected:
Average Concession Time (TMC), Waiting Time for Scheduled Service (TMEA),
Percentage of cases reopened (SUPERTEC), Manifestations answered within the
legal deadline (Ombudsman Response). Over the analyzed period, there was an
increase in the total INSS productivity score at the national and state lev=
els,
showing increasing trends, demonstrating the effort in complying with
strategies aimed at improving service. The main advantages of implementing =
the
proposed metric are: enabling proactive monitoring of the queue of requests
from INSS beneficiaries; serving as a management tool for measuring,
evaluating, analyzing, and comparing the performance of services provided by
the INSS over time; providing support and sustainability for decision-making
regarding the application of preventive and corrective measures aimed at
enhancing the service provided to beneficiaries of the studied institution.=
Keywords: productivity metrics; performance measurement and evaluation; service
improvement; public service; INSS.
Recebido
em 09/10/223. Aprovado em 28/12/20=
23.
Avaliado pelo sistema double blind =
peer
review . Publicado conforme normas da APA.
https://doi.org/10.2227=
9/navus.v13.1800
1 INTRODUÇÃO
A melhoria da
produtividade, isto é, como fazer mais com menos, é um desafio urgente de t=
odos
os governos, e, em um ambiente de restrições fiscais agravadas à medida que=
a
população envelhece, o setor público enfrenta problemas complexos, como a
desigualdade econômica, a necessidade de assistência à saúde, previdenciári=
a,
segurança etc. (Corydon et al .,=
2017).
Desde os tem=
pos dos precursores
da Administração Científica, como Taylor, Ford e Fayol, o aumento da
produtividade continua a ser um dos grandes desafios para as organizações de
todo tipo. Esse aumento pode também ser alcançado por meio da melhoria da
qualidade. Ao elevar a qualidade, é possível atender a demanda em menos tem=
po,
reduzir o retrabalho, o desperdício e o gasto com recursos. Para isso, as
organizações contam com uma série de técnicas, métodos e ferramentas aliada=
s à
melhoria da gestão organizacional, capazes de fazerem a diferença sobre o g=
anho
da produtividade. Ciente disso, o problema então é saber escolher a ferrame=
nta
correta e compatível com o ambiente específico da organização (Moneni; Ni,
2021).
Esse é o cas=
o do
Instituto Nacional do Seguro Social (INSS), que enfrenta o problema da dema=
nda
crescente por atendimento de seus contribuintes, os quais buscam constantem=
ente
seus benefícios e têm pressa em ser atendidos (Banga et al ., 2020).
O INSS é uma
Autarquia Federal vinculada ao Ministério da Previdência, criada em 1990 pe=
la
fusão do Instituto de Administração Financeira da Previdência e Assistência
Social (IAPAS) com o Instituto Nacional de Previdência Social (INPS). Sua
finalidade é reconhecer os direitos dos beneficiários do Regime Geral de
Previdência Social (RGPS), previsto na Constituição Federal, e prover
benefícios previdenciários e assistenciais. O INSS atende ao público em ger=
al e
é responsável pelo reconhecimento inicial dos direitos aos benefícios
previdenciários. Esses benefícios têm o objetivo de garantir o sustento do
trabalhador e de sua família em casos de incapacidade para o trabalho. Além
disso, o INSS oferece os Benefícios de Prestação Continuada (BPC), destinad=
os a
amparar pessoas em situação de vulnerabilidade social, como idosos e pessoas
com deficiência.
Atualmente, =
o INSS
conta com mais de 65 milhões de contribuintes e está presente em 1.874 unid=
ades,
realizando atendimento presencial para cerca de três milhões de pessoas por
mês. Este atendimento é conduzido através das Agências da Previdência Social
(APS), as quais estão distribuídas em 1.346 municípios em todo o país (Mini=
stério
da Previdência Social, 2021).
Diante desse
contingente de usuários (beneficiários e potenciais beneficiários) e diante=
da
crescente demanda anual, o INSS constantemente recebe cobranças da sociedade
para melhorar a qualidade e agilidade no atendimento ao cidadão.
Para
isso, ao longo de sua trajetória, o INSS vem procurando adotar programas e =
desenvolver
serviços para maximizar seus resultados com o uso de ferramentas de apoio a=
os
processos de gestão. Nesse sentido, a partir de 2017 foi implantado o proje=
to
INSS Digital por meio da PORTARIA Nº 91 /PRES/INSS/2017 (Brasil, 2017a), e =
sua
expansão para todas as unidades com a PORTARIA Nº 1.106/PRES/INSS/2017 (Bra=
sil,
2017b). No mesmo ano, também ocorreu a adoção do Teletrabalho para dar cele=
ridade
às atividades realizadas de forma digital, conforme a PORTARIA Nº 2.033
/PRES/INSS/2017 (Brasil, 2017c). Para melhorar o atendimento ao cidadão e d=
ar
maior celeridade na análise e concessão inicial de benefícios e na redução =
de
pagamentos de benefícios com indícios de inconsistência, foi instituído, por
meio da Portaria Interinstitucional Nº 4 SPREV/SGD/INSS/DATAPREV, de 10 de
abril de 2019 (BRASIL, 2019), o Comitê Estratégico e um Grupo de Trabalho
Interinstitucional para implementação da Transformação Digital. Esta mudança
fez com que os serviços do INSS pudessem ser solicitados pelo segurado de f=
orma
online pela Internet e s=
em
sair de sua residência. Essas iniciativas visam alinhar as ações do INSS à
Política de Governança denominada Processo Eletrônico Nacional (PEN) do
Ministério de Planejamento, Desenvolvimento e Gestão (TOTI; ANJO, 2022).
Com a redução do atendimento presencial,
esperava-se uma melhoria na produtividade dos servidores e na redução da fi=
la
de pedidos a serem analisados. Entretanto, isso não ocorreu, e ainda causou=
uma
percepção negativa junto à sociedade, conforme os relatos veiculados na míd=
ia
entre 2018 e 2021. Tal situação desperta interesse em buscar modelos de ges=
tão
que consigam mensurar a produtividade e melhorar a eficiência na prestação =
de
serviços públicos do INSS.
A discussão sobre produtividade e eficiência no
serviço público é uma preocupação do mundo inteiro, o que torna relevante o
desenvolvimento de pesquisa sobre medição, avaliação e melhoria da
produtividade, especialmente no caso do INSS, como observado anteriormente.=
Devido
à natureza intangível dos serviços e à ausência de métricas financeiras nos
serviços públicos, a medição tem se mostrado um desafio para avaliar a
qualidade, a produtividade e a eficiência do serviço público prestado (Hilh=
orst
et al. , 2022; Nguyen; O’Donnell,
2023). Porém, “a produtividade depende cada vez mais da capacidade de aplic=
ar
as informações no cotidiano empresarial, transformando dados e informações =
em
conhecimento” (Melo et al ., 201=
6, p.
15).
Como alertam Corydon et al . (2017, p. 5), “no mundo inteiro os governos precisam
encontrar, urgentemente, uma maneira de entregar melhores resultados e uma
melhor experiência para os cidadãos”. É neste aspecto que “a medição da
produtividade é fundamental. Mas até agora o progresso no setor público é
limitado” (Codrydon et al., p.5). Como resultado, é difícil para os governos
avaliarem o real retorno sobre o gasto público.
Dada a importância de se mensurar produtividade=
e
eficiência em toda organização e da problemática dessa medida para o serviço
público, cabe formalizar a pergunta norteadora desta pesquisa: Como medir a
produtividade no INSS, de forma a aperfeiçoar a prestação de serviços ao
cidadão?
Para responder essa questão, o presente trabalho
teve como objetivo propor uma métrica para mensur=
ar a
produtividade e a eficiência da prestação de serviços do INSS. Isso visa
auxiliar no processo de gestão e na tomada de decisões, com intuito de melh=
orar
o atendimento ao cidadão. Para isto, o seguinte caminho foi percorrido:=
a)
Levantar os indicadores que possibilitassem a análise da produtividade do I=
NSS;
b) Criar uma métrica para mensurar a produtividade e eficiência da prestaçã=
o de
serviços do INSS; c) Aplicar a métrica em uma situação real do INSS de form=
a a
poder avaliar a sua capacidade na prestação de serviço ao longo do tempo,
permitindo comparações.
2 REFERENCIAL T=
EÓRICO
<=
/o:p>
2.1 A
busca pela eficiência de gestão pelo INSS
A estruturação do planejamento no INSS advém da
publicação do Decreto No 3.081/1999 (Brasil, 1999), que descentralizou as
antigas Superintendências em Gerências Executivas (GEX). Porém, esse projeto
incluía apenas as ações de abrangência nacional do Plano Plurianual (PPA).
Contudo, essa descentralização não estava relacionada com estratégias volta=
das
para a visão de futuro da instituição. Em uma nova mudança de estrutura, por
meio do Decreto Nº 4.660/2003 (Brasil, 2003), o INSS criou a Coordenação Ge=
ral
de Controladoria, que entre suas competências tinha a função acompanhar os
resultados obtidos com a aplicação de padrões, sistemas e métodos de avalia=
ção
de produtividade e qualidade, além de recomendar ações de melhorias.
No segundo semestre de 2005, o INSS implementou=
um
Modelo Operacional do Regime Geral de Previdência Social e elaborou o prime=
iro
esboço do seu Mapa Estratégico, alicerçado na metodologia do Balanced
Scorecard (BSC), conforme Resolução Nº 201/INSS/DC, de 14 de julho de 2=
005.
Esse modelo consistiu no Plano Estratégico da Previdência Social para o per=
íodo
de setembro de 2005 a dezembro de 2006, tendo como principais objetivos a
melhoria do atendimento, a redução dos custos operacionais e o combate a
fraudes e pagamentos indevidos (Brasil, 2005).
Nos anos de 2007 e 2008, os desafios do INSS fo=
ram
traduzidos em Planos de Ação compostos por ações integradas, visando a melh=
oria
contínua da gestão e do atendimento. Entretanto, uma deficiência dessa
metodologia consistia na falta de clareza dos processos desenhados para a v=
isão
de futuro, dificultando, assim, o entendimento e a comunicação do Plano par=
a os
níveis de execução (Brasil, 2008). Como “os processos de comunicação contri=
buem
para o desenvolvimento de formas de inter-relação mais participativas e
comprometidas” (MELLO; Nunes, 2020, p.2) foi preciso rever esta situação. <=
o:p>
Na segunda metade de 2008, iniciou-se o trabalh=
o de
elaboração do Planejamento Estratégico da Previdência Social para o período=
de
2009-2015, configurando um marco positivo na história da Previdência Social=
. Diante
da perspectiva de planejamento de longo prazo foram traçadas ações que
permitiam, além de solucionar problemas cotidianos, trilhar o caminho
necessário para a construção do futuro almejado. Este trabalho foi realizad=
o de
modo participativo, integrando ações do MPS, INSS e da Empresa de Tecnologi=
a e
Informações da Previdência Social (Dataprev), conforme Lei N. 11.890 (Brasi=
l,
2008).
O Plano de Ação de 2009 foi o primeiro a ser el=
aborado
após o Planejamento Estratégico da Previdência Social, caracterizando-se co=
mo o
movimento inicial de descentralização do processo de planejamento e
aprimoramento das técnicas de gestão nas unidades descentralizadas do INSS.=
Foi
composto por 35 ações e projetos estruturantes, sendo que 10 dessas ações e=
ram
descentralizadas e acompanhadas pelas Gerências Executivas.
Com
o Plano de Ação/2010 foram inseridas quatro importantes inovações: 1ª)
planejamento participativo; 2ª) contratualização da gestão, 3ª) ciclo de
avaliação de resultados; 4ª) institucionalização do Plano. Nos anos
subsequentes, tais inovações foram definitivamente agregadas às práticas da=
Casa, desenvolvidas com perseverança,
empenho e firmeza, no caminho de conquista da
missão institucional de=
senhada.
O Plano de Ação tem se mostrado um importante instrumento de disseminação de
boas práticas, sendo um eficiente canal de comunicação, já que as críticas =
e as
sugestões apresentadas pelos servidores e gestores são transmitidas e
discutidas com os níveis hierárquicos superiores. A avaliação desse plano, =
que
faz parte do dia a dia do INSS, é realizada trimestralmente por meio de
reuniões conduzidas pelos respectivos gestores.
Em 2016, devido ao Plano Plurianual da União para o período de 2016 a 2019, instituído pela Lei No de 13 de janeiro de 2016
(Brasil, 2016a), e conforme
a transferência e vinculação
do INSS do Ministério do Trabalho e Previdência Social para o Ministério do=
Desenvolvimento Social e Agrário, nos
termos da Medida Provisória No 2016,
convertida na Lei No de 29 de setembro
de 2016 (Brasil, 2016b),=
foi aprovado o Mapa Estratégico para o quadriênio 2016-2019. Esse mapa foi estabelecido p=
ela
Resolução No 2016 (Brasil, 2016c). Ele foi consol=
idado
com base na metodologia do BSC e serve de instrumento de comunicação que proporciona maior alinhamento do Ins=
tituto
com os objetivos institucionais. Nele, constam a missão, a visão de futuro, os direcionadores e os objetivos =
estratégicos,
representados por diagramas de relação entre causa e efeito.=
Em
2017, por meio da Portaria No o
Por
meio do avanço tecnológico e com o objetivo de agilizar e tornar mais econô=
mico
o atendimento prestado, além de otimizar a força de trabalho, o INSS
implementou a Prova de Conceito do Projeto Teletrabalho. Esse projeto permi=
te
que as atividades laborais exercidas pelos servidores da Autarquia possam s=
er
executadas dentro ou fora de suas dependências, em localidade diferente de =
seu
órgão de lotação (alternativa remota), sob a denominação de Teletrabalho, c=
onforme
Portaria No
Em
10 de abril de 2019, por meio da Portaria interinstitucional No
Posteriormente,
com base na Resolução PRES/INSS No
Diante
do exposto, é possível notar que o INSS, ao longo dos anos, tem empregado u=
ma
variedade de planos de ação, privilegiando o uso de indicadores com o objet=
ivo
de buscar a melhoria do atendimento ao público. Embora disponha de uma
ouvidoria que permite aos segurados apresentar reclamações relativas às
prestações de serviços, denúncias ou elogios, conforme disposto no Art 37§3=
º da
Constituição Federal, não se identificou uma métrica para avaliar a qualida=
de
do serviço prestado, associado à produtividade da instituição.
=
2.2 A produtivi=
dade em
serviço público
A
administração pública pode ser conceituada como a função que o Estado exerce
para garantir os interesses da sociedade, tais como educação, cultura,
segurança, saúde, entre outras áreas. É o conjunto de órgãos e de pessoas
jurídicas aos quais a lei imputa o exercício da função administrativa do Es=
tado
(Denhardt, 2012). Considerando os direitos e deveres do poder público, o Es=
tado
deve tomar decisões que incluam a participação dos diversos setores da
sociedade. Assim, suas escolhas poderão atender aos anseios da sociedade,
contemplando o apoio aos cidadão-usuários na implementação dos
programas/projetos e na fiscalização dos serviços públicos (Paludo, 2013).<=
span
style=3D'mso-spacerun:yes'>
Como
a tarefa do setor público é produzir um conjunto selecionado de serviços com
resultados satisfatórios, dentro dos limites das restrições orçamentárias,
destinados a atender a toda população, há pressão para que as organizações
públicas melhorem seu desempenho e demonstrem progresso das entradas
financeiras em saídas de serviço de alta qualidade, utilizando processos
eficientes e eficazes (Silva; Santos; Medeiros, 2018). Nesse sentido, as
medidas de produtividade podem atuar como parte dos sistemas de medição de
desempenho (Nguyen; O’DonnelL. 2023).
A
produtividade, de acordo com a Organização Europeia para Cooperação Econômi=
ca
(OECD), é descrita como fundamental para a competitividade e o crescimento
econômico das instituições, e seu conceito varia de acordo com o ambiente q=
ue
se busca analisar ou conforme a opinião dos pesquisadores (OECD, 2019).
Tradicionalmente, a produtivi=
dade é
definida pela relação entre outputs e inputs . Os outputs
são a quantidade produzida de determinado produto/serviço e os inputs os
recursos usados no processo de criação desse produto/serviço (Rutkauskas; P=
aulavičienė,
2005). Para Jacobs e Chase (2018), a produtividade é uma medida comum que u=
ma
unidade de negócio, indústria ou país utiliza para avaliar como seus recurs=
os
estão sendo empregados na busca pela realização de seus objetivos. Tem o po=
der de
comparação da mesma operação com operações semelhantes dentro de uma indúst=
ria
ou com operações em todo o conjunto de uma indústria. Essa medida pode ser
física, monetária ou expressa por um índice.
Como
a produtividade trata da razão entre o output e o input de um
dado processo, torna-se necessário compreender esses dois termos no context=
o de
serviços. Os inputs variam de acordo com a natureza do negócio e pod=
em
incluir mão de obra física e intelectual, materiais, energia e capital – co=
mo terrenos,
edificações, equipamentos, sistemas de informação e ativos financeiros. Os =
outputs
também variam conforme a natureza do serviço. Em empresas de serviços que
processam as posses de seus clientes, por executarem tarefas rotineiras com=
inputs
e outputs de fácil medição, assemelham-se às indústrias e, por isso,=
a
tarefa da medição da produtividade é considerada simples. Porém, devido a
intangibilidade, torna-se complexo avaliar as diferenças entre resultados
obtidos nos serviços (Lovelock; Wirtz, 2006).
De
qualquer forma, para melhorar a produtividade é preciso antes medi-la
sistematicamente. Um sistema de medição de desempenho é um dos determinantes
que criam o valor de uma empresa (Waśniewsk, 2021). Assim, a avaliação=
do
desempenho de forma mais ampla requer um Sistema de Medição e Avaliação do =
Desempenho
(SAD), de modo a facilitar a tomada de decisão (Chen; Lill; Lucianetti, 202=
3),
e os indicadores são elementos importantes de qualquer SAD. Assim, um conju=
nto
de indicadores-chave de desempenho, ou Key Performace
Indicators (KPIs), são essenciais para medir, acompanhar e avaliar o
desempenho de produto ou serviço ( Mahmood
et al ., 2018). Jääskeläinen,
Tappura e Pirhonen (2022) corroboram essa ideia ao afirmarem que a medição =
de
desempenho é uma ferramenta importante para a gestão no alcance de seus
objetivos.
A
função de um SAD é aumentar o sucesso de um produto, serviço, processo ou
projeto. No caso dos serviços, a medição do desempenho define a avaliação
subjetiva do cliente e sua percepção sobre o de serviço prestado, procurando
estabelecer as bases para a redução da "lacuna" entre o desempenho
real e o esperado. No entanto, apesar dos extensos esforços de medição e
controle, esta lacuna é difícil de fechar, o que acabará influenciando a
satisfação das partes interessadas (Maylor et al ., 2023; Korhonen et
al., 2023).
A
produção e o consumo do serviço são processos simultâneos nos quais os clie=
ntes
participam ativamente. Como os recursos ou insumos usados para produzir
serviços não podem ser completamente padronizados, torna-se difícil relacio=
nar
um determinado número de entradas – seja um volume ou valor – a uma certa
quantidade de saídas e estabelecer uma unidade de serviço (Grönroos; OJASAL=
O,
2004).
Em
virtude da complexidade da prestação de serviços, vários modelos e estudos
sobre a temática foram desenvolvidos, com destaque para os trabalhos de: a)
Armistead e Machin (1998), Ojasalo (1999), Johnston e Jones (2004) que
compreendem a produtividade e a qualidade percebida pelo cliente como fenôm=
enos
inseparáveis, visto que a satisfação do cliente e a otimização da produtivi=
dade
podem ser objetivos incompatíveis quando buscados simultaneamente; b) Marti=
n,
Horne e Chan (2001), que ressaltam o papel do cliente na prestação de servi=
ços;
c) Grönroos e Ojasalo (2004), que destacaram o aprendizado e a capacidade de
prestação do serviço, associada ao papel de cliente no processo de entrega =
do
serviço; d) Sahay (2005), que estendeu o exame tradicional da produtividade=
a
fatores estressantes como a qualidade do serviço; e) Scerri e Agarwal (2018)
que demonstraram que a análise de produtividade em serviços devem abordar a
escolha do cliente e sua capacidade de pagar, o compromisso assumido, a
conclusão da entrega, a determinação da complexidade e os sistemas de gestã=
o de
qualidade.
Grönroos
e Ojasalo (2004) consideram que o conceito de produtividade usado na manufa=
tura
é muito limitado para caracterizar a produtividade em serviços, não sendo e=
ste
um conceito estático, mas sim dinâmico. Nesse sentido, os autores sugerem q=
ue a
produtividade em serviços advém de três fatores: 1) Eficiência interna –
capacidade de conversão de inputs em outputs para o cliente; =
2)
Eficiência externa – propicia o interesse externo na conversão do output=
,
configurando a capacidade de a empresa produzir certo nível de qualidade de
serviço, a partir de certa estrutura de recursos; 3) Eficiência de capacida=
de –
gestão eficiente da capacidade com base na procura.
De
acordo com Faria (2018), muitos aspectos da qualidade do serviço estão
claramente relacionados a elementos intangíveis. Isso fez com que o conceit=
o de
qualidade deixasse de se restringir às especificações técnicas do produto ou
serviço, passando a depender da avaliação do cliente.
No
contexto dos serviços públicos, um dos principais problemas na medição da
produtividade diz respeito aos resultados dos serviços e, especialmente, aos
aspectos intangíveis dos componentes dos produtos. Por essa razão, o termo
"desempenho" parece ser mais frequentemente utilizado por
pesquisadores e profissionais do que o termo "produtividade" (Sil=
va;
Santos; Medeiros, 2018).
Apesar
de uma avaliação abrangente e equilibrada de desempenho ser justificada, is=
so
não diminui a importância da produtividade como uma das metas principais. A
produtividade do serviço público está associada à economia, eficiência,
produtos e insumos, os quais constituem componentes dos modelos de desempen=
ho
do serviço público, abrangendo também alguns aspectos de resultados e eficá=
cia
(Boyne, 2002; Maurel et al ., 2014).
As
perspectivas de desempenho para o serviço público, apresentadas por Boyne
(2002) e Jääskeläinen (2009), envolvem: a) o produtos/serviços em termos de
quantidades e qualidades ofertadas; b) a eficiência mensurada pelos custos =
por
unidade de produto/serviço; c) os resultados do serviço levando em consider=
ação
a eficácia formal e o impacto; d) a capacidade de resposta que pode ser
traduzida na satisfação do pessoal e do cliente; e) os resultados democráti=
cos,
relacionados à probidade e participação.
Um
método que tem sido usado para associar desempenho do serviço à produtivida=
de é
a denominada Matriz de Produtividade (MP). Esse método, que pode ser aplica=
do
em serviços públicos, contém um conjunto de medidas de produtividade direta=
e
indireta, que são utilizadas para compor um único resultado de medição. Por
incluir diferentes fatores que afetam a produtividade acaba se distanciando=
do
exame de produtividade tradicional baseado na relação entre produto e insum=
o (Jääskeläinen,
2009).
De
acordo com Jääskeläinen (2009), nessa Matriz, cada medida tem seu próprio p=
eso
que varia de 0 a 100 e os valores esperados de diferentes medidas são escal=
ados
para produzir uma pontuação de 0 a 10 para cada medida. Então, multiplicando
primeiro a pontuação de cada medida pelos pesos e, em seguida, somando os r=
esultados,
a matriz produz uma pontuação total de 0 a 1000.
<=
/o:p>
3 METODOLOGIA
Quanto à abordagem, a pesquisa
possui características tanto qualitativas como quantitativas (Creswell, 201=
4; Gil,
2022). No aspecto qualitativo, busca compreender a descrição e a análise dos
componentes de um sistema complexo de significados e impactos sociais e
culturais de um fenômeno. No aspecto quantitativo, busca quantificar dados e
utiliza de provas científicas como testes, modelos, graus de significância e
sistematizações para validar o estudo.
Trata-se também de uma pesqui=
sa de
natureza aplicada, decorrente da necessidade de resolver problemas concreto=
s,
tendo a finalidade prática sobre o desenvolvimento da métrica proposta (Ver=
gara,
2013). Quanto ao objetivo, a pesquisa assume características da pesquisa
exploratória e descritiva, ao ilustrar certos fenômenos e conceitos a parti=
r da
descrição de processos e de correlações, identificando os fatores que
determinam ou contribuem para a ocorrência desses fenômenos (Creswell, 2014=
).
Para fundamentar a coleta de =
dados,
foram utilizadas a pesquisa bibliográfica, documental e observação particip=
ante
(Vergara, 2013; Creswell, 2014; Gil, 2022). Tal coleta
foi realizada nas condições naturais em que os fenômenos ocorrem (Gil, 2022=
) e
por meio de: a) pesquisa bibliográfica que consistiu no levantamento, seleç=
ão,
fichamento e arquivamento de informações relacionadas à temática; b) pesqui=
sa
documental, levando em consideração as legislações relacionadas à temática,=
bem
como os dados e indicadores existentes na instituição referentes aos inputs e outputs do serviço prestado pelo INSS; c) pesquisa de campo,
incluindo testes e observação participante para aferir o índice de
produtividade e eficiência criado.
A
Figura 1 mostra o esquema metodológico adotado para a realização da presente
pesquisa, enquanto a Matriz de Produtividade de Jääskeläinen (2009), utiliz=
ada
nesta pesquisa, é apresentada na Tabela 1.
Nessa
tabela a pontuação do indicador específico (pj) equivale ao resultado de po=
ntos
(Rj) que varia de 0 a 10 pontos, sendo 0 (zero) a pontuação mínima e 10 (de=
z) a
pontuação máxima.
Figura 1 – Esquema metodológico
Fonte: Elabora=
ção
própria (2023).
<=
/o:p>
Essa pontuação é atribuída em
função de uma determinada classificação “c’ do indicador “i” na posição “j”
(ci,j), obtida por meio de uma avaliação individual.
Tabela 1 – Mat=
riz de
Produtividade para apuração da pontuação total do conjunto de indicadores de
produtividade de serviços
Fonte: Elaboração própria (2023) com bas=
e em Jääskeläinen
(2009).
Cada
indicador (ci) recebe um peso (ki) específico, variando de 0 a 100, determi=
nado
de acordo com a perspectiva dos avaliadores, que, no caso estudado, está
relacionado ao peso do indicador do ponto de vista da melhoria da
produtividade. Assim, multiplicando-se a pontuação (pi) pelo peso atribuído=
ao
indicador (ci), obtém-se a Pontuação Ponderada (Pi) do indicador (ci)
específico, conforme mostra a fórmula 1.
Pi =3D pi x ki (1)
Em que:
Pi =3D Pontuação ponderada
pi =3D pontuação do indicador
específico (ci)
ki =3D peso atribuído ao indi=
cador
específico (ci).
A
Pontuação Total (PT) da instituição é obtida por meio do somatório das
Pontuações Ponderadas, conforme mostra a fórmula 2.
(2)
Para a montagem da Matriz de =
Produtividade
foram escolhidos quatro indicadores, detalhados no subtópico 4.1. Para
demonstrar o seu funcionamento, a MP foi aplicada no INSS, em nível naciona=
l e
em nível estadual, considerando os dados do estado do Rio de Janeiro, no
período de julho de 2022 a junho de 2023. Isso permitiu fazer comparações do
desempenho de cada nível ao longo do tempo e entre os níveis. Adicionalment=
e,
foi gerado o gráfico de tendência para cada nível, a equação da reta e a an=
álise
da regressão linear.
=
4 RESULTADOS E
DISCUSSÃO
<=
/o:p>
4.1 Montagem da Matriz de Produtivida=
de
para o INSS
A
discussão sobre produtividade e eficiência em serviço é histórica e possui
diversos direcionamentos. Para o serviço público, apesar de haver quantidade
expressiva de pesquisa, há dificuldades em avançar nesse ponto em virtude de
não envolver a métrica financeira, a natureza intangível do serviço e a
avaliação da qualidade do serviço. Por isso, na aplicação do método matrici=
al
devem ser consideradas tanto as necessidades gerenciais quanto a medição da
qualidade do serviço, pois, segundo Hodgkinson (1999), ignorar a qualidade =
na
avaliação dos serviços públicos pode prejudicar a motivação para a melhorar=
ia da
produtividade.
Na
montagem da MP para o INSS levou-se em consideração quatro indicadores: Tem=
po
Médio de Concessão do Benefício (TMC), o Tempo de Espera de Atendimento
Agendado (TMEA), o SUPERTEC (porcentagem de processos reabertos) e a Ouvido=
ria
(percentual de manifestações respondidas no prazo legal). Cada indicador,
dependendo do seu desempenho, recebe um valor correspondente de 0 (zero) a =
10
(dez) pontos.
O
TMC, representado na Figura 2, quantifica o tempo médio decorrido entre a d=
ata
da entrada do requerimento (DER), - que representa o pedido do segurado,
podendo ser feito por telefone, canais remotos de Internet ou aplicativos
próprios - e a data da decisão administrativa dos pedidos referentes a
benefícios sobre aposentadorias, pensões e auxílios. Este indicador pode si=
nalizar
uma demora da análise devido a estoque alto de pedidos, ineficiência nos
processos e outros fatores mais complexos. A escolha da escala desse indica=
dor
(por meio de avaliações individuais, que são realizadas internamente e
registradas nos planos de ações anteriores), considera como excelente um TM=
C de
10 dias, ou seja, até 10 dias, recebe a pontuação máxima de 10 pontos, enqu=
anto
um TMC igual ou maior que 110 dias recebe uma pontuação igual a zero. O peso
desse indicador, do ponto de vista da melhoria da produtividade, é igual a =
45.
Figura 2 – Tempo =
médio
de concessão de benefício
=
Fonte: Elaboração
própria (2023).
O
TMEA, representado pela Figura 3, foi incluído ao modelo porque, apesar do
sucesso da inclusão do Projeto INSS Digital de 2017, ainda existem agendame=
ntos
presenciais nas unidades de atendimento do INSS (APS). Logo, acredita-se que
esse indicador seja imprescindível para a avaliação da performance da
Instituição. A escolha da escala desse indicador (por meio de avaliações
individuais, realizadas internamente e registradas nos planos de ações
anteriores) considera como excelente, recebendo nota igual a 10, um TMEA de=
5
dias, e zero para um TMEA igual ou maior que 55 dias. Em virtude de sua
importância, o peso desse indicador é igual a 25.
Figura 3 – Tempo =
de
espera de atendimento agendado
=
Fonte: Elaboração
própria (2023).
A
Supervisão Técnica ou programa SUPERTEC é outro ponto de qualidade, levanta=
do
junto aos gestores, que foi considerado por representar a porcentagem de processos reabertos . Esse program=
a é
considerado novo e se encontra em período de experiência na Instituição
estudada. Todavia, na escolha da escala desse indicador, por meio da avalia=
ção
individual, não se pode deixar de considerar o nível de excelência em 0% de
processos reabertos após supervisão técnica, obtendo a pontuação máxima de =
10.
Isso se fundamenta na premissa de que não se pode considerar nível de
excelência um percentual de retrabalho, enquanto o resultado zero é atribuí=
do
quando se tem 100% dos processos reabertos. Em termos de importância do pon=
to
de vista da produtividade, esse programa recebeu peso igual a 15.
A
ouvidoria, por fazer parte do objetivo estratégico de desburocratização dos
processos de trabalho, conforme o plano de ação de 2022, deve receber resul=
tado
de avaliação 10 quando a instituição consegue atender de forma tempestiva 1=
00%
das manifestações de Ouvidoria recepcionada pelo INSS. Receberá pontuação z=
ero
quando não se consegue atender nenhuma solicitação no prazo legal. A ouvido=
ria
também recebeu peso igual a 15. Essa Matriz de Produtividade é mostrada na
Tabela 2.
Tabela 2 – Matriz de Produtiv=
idade
adaptada à realidade do INSS para o levantamento da pontuação total da
produtividade
=
Fonte: Elaboração
própria (2023) com base em Jääskeläinen (2009).=
Nessa
matriz constam os quatro indicadores que são analisados em conjunto (TMC, T=
MEA,
SUPERTEC e Ouvidoria); os resultados da medição, que variam de 10 (dez) a 0
(zero); a eficiência de cada indicador, em que o TMC já inicia com eficiênc=
ia
máxima em 10 dias, o TMEA em 5 dias, o SUPERTEC em 0% de retrabalho e a
Ouvidoria em 100% das manifestações respondidas dentro do prazo; os pesos
atribuídos a cada indicador, em virtude de sua importância, do ponto de vis=
ta
da melhoria da produtividade, em que o TMC recebeu peso igual a 45, o TMEA,=
25,
o SUPERTEC e a Ouvidoria receberam pesos iguais a 15.
O
funcionamento dessa matriz pode ser visualizado por meio de um exemplo
ilustrativo, recorrendo-se à simulação, considerando o TMC igual a 80 dias;=
o
TMEA igual a 26 dias; a taxa de processos reabertos para o SUPERTEC igual a
15%; o percentual de respostas dentro do prazo legal das manifestações de 8=
0%.
O resultado está ilustrado na Tabela 3.
Tabela 3 – Resultado da matriz de produt=
ividade
com base em simulação
Resultado
da medição
80
26
15%
80%
8
5
3
3
5
8
8
135
125
120
120
500
=
Fonte: Elaboração
própria com base nos dados da pesquisa (2023).
Analisando
essas informações separadas e no conjunto, pode-se verificar que: a) um TMC=
de
80 dias cumpre os requisitos da pontuação 3, em que, esse valor multiplicado
pelo peso de 45, resulta em uma pontuação ponderada da medida de 135 nesse
indicador individual; b) um TMEA de 26 dias está entre os valores escalares=
de
25 e 30, por isso, cumpre com o requisito 5, que multiplicado pelo peso de =
25,
resulta em uma pontuação ponderada individual de medida de 125 pontos; c) um
SUPERTEC de 15% de retrabalhos (processos reabertos), se encontra entre duas
classificações escalares, 10% e 20%, por isso, atende o requisito de pontua=
ção
igual a 8, que multiplicando pelo peso 15, resulta em uma pontuação pondera=
da
individual de medida de 120 pontos; uma Ouvidoria atendendo 80% das
manifestações dentro do prazo legal, atende o requisito de pontuação igual =
a 8,
que multiplicando pelo peso de 15, resulta em uma pontuação ponderada
individual de medida igual a 120 pontos.
Somando-se
as pontuações ponderadas individuais, obtém-se uma pontuação final igual a =
500.
Esse valor representa a produtividade total da instituição no período
analisado, em que recebe influência de cada um dos indicadores
individualmente. Entretanto, para =
que um
indicador consiga produzir informação para dar suporte à análise e contribu=
ir
no processo de gestão e tomada de decisão, requer que seja analisado ao lon=
go
de um período, de modo a entender a performance
da instituição, como poderá ser observado a seguir.
4.2 Performance
da matriz de produtividade no INSS no período de julho/22 a junho/23
A
Matriz de Produtividade no INSS pode ser usada para analisar a performance do INSS nacional, esta=
dual
e, até mesmo, em postos específicos de atendimento. Neste trabalho buscou-se
apresentar a pontuação obtida no período de julho de 2022 a junho de 2023 n=
os
níveis nacional e estadual. Para analisar a
performance da Matriz de Produtividade em nível estadual, escolheu-se, =
com
base no critério de acessibilidade, o estado do Rio de Janeiro em virtude da
maior proximidade com os autores do trabalho. Isso permite fazer comparação=
do
desempenho de cada nível ao longo do tempo; entre níveis diferentes, em pon=
tos
específicos; e, comparar os níveis ao longo do tempo.
=
4.2.1 Performance
da matriz de produtividade em nível nacional
Para
analisar a performance da
produtividade do INSS, em nível nacional, na aplicação da MP, com base nos
dados do período de julho de 2022 a junho de 2023, foram consideradas as
variações ocorridas em termos de TMC e TMEA. Para todos os meses foram
considerados SUPERTEC igual a 15% e Ouvidoria igual a 80%, visando suprir a
falta de dados históricos desses dois últimos indicadores. Os resultados
obtidos foram agrupados conforme mostra a Tabela 4.
Tabela 4 – Performance da produtividade =
do
INSS nacional de julho/22 a junho/23
SUPERTEC <=
/span>
Média
Desvio padrão
Cv
No
período analisado a pontuação média obtida foi igual a 565,42 com desvio pa=
drão
igual a 75 pontos, provocados por um TMC médio de 82 dias e um TMEA de 22 d=
ias,
com desvios de 18,25 e 2,12, respectivamente. Analisando o comportamento de=
ssa
pontuação mês a mês, observa-se um aumento na pontuação total do INSS em
virtude da tendência da redução nos tempos TMC e TMEA. As menores pontuações
ocorreram nos meses de julho e agosto de 2022 e a maior em abril de 2023, em
que se alcançou 640 pontos do total de 1.000 pontos. Isso reflete o cuidado=
na
gestão voltada para a melhoria da eficiência geral dos serviços prestados. =
Esse
aumento dos pontos ocorreu porque o TMC exerce maior peso, dada sua importâ=
ncia
operacional, visto que o comportamento dos prazos não seguiu a mesma tendên=
cia,
conforme mostra o Gráfico 1.
Nos meses de maio e junho de =
2023
houve aumento no tempo de ambos os indicadores, reduzindo a pontuação final=
.
Gráfico 1 – Comportamento do TCM e TMEA =
ao
logo do período de análise
Fonte: Elaboração própria com base nos dados da
pesquisa (2023).
=
Essa redução pode estar assoc=
iada:
a) à perda de eficiência no atendimento, como no caso do mês de junho em qu=
e o
número médio de dias para atendimento do Benefício Assistencial à Pessoa com
Deficiência passou de 142 dias no mês de abril para 172 dias no mês de junh=
o de
2023; b) ao aumento do número de requisições de um serviço que demanda maior
número de dias para atendimento como no mês de maio em que o número de
requisições do Benefício Assistencial à Pessoa com Deficiência passou de 75=
.386
em abril para 92.529 em maio de 2023; à incidência de serviço que demanda m=
aior
número de dias para atendimento como, por exemplo, c) à perda da eficiência=
e
aumento do número de requisições ao mesmo tempo, como no caso da Aposentado=
ria
por Idade Urbana, que passou de 5.679 requisições e 41 dias médios em abril
para 71.445 requisições e 108 dias médios em maio de 2023.
A
pontuação final alcançada representa a produtividade total da instituição no
período analisado, em que recebe influência de cada um dos indicadores
individualmente, de modo a entender a performance
da instituição. Ao longo do período de julho/22 a junho/23 houve um aumento=
na
pontuação total do INSS em virtude da tendência da redução nos tempos TMC e
TMEA. As reduções no TMC apresentam maior impacto porque são atribuídas a e=
la o
maior peso. As variações nos indicadores podem representar perda ou ganho de
eficiência bem como a concentração em determinados meses de solicitações que
demandam mais ou menos tempo.
=
4.2.2 Performance da matriz de
produtividade em nível estadual
No
período analisado a pontuação média obtida foi igual a 531,25, com desvio
padrão igual a 134 pontos e coeficiente de variação de 0,2527, provocados p=
or
um TMC médio de 85 dias e um TMEA médio de 30 dias, desvios de 32,27 e 7,95=
e
coeficientes de variação de 0,3796 e 0,2623, respectivamente (Tabela 5).
Analisando
o comportamento dessa pontuação mês a mês, no estado do Rio de Janeiro tamb=
ém
apresentou aumento na pontuação total do INSS em virtude da tendência da
redução nos tempos TMC a partir de agosto de 2022, e TMEA a partir de outub=
ro
de 2022. A menor pontuação ocorreu no mês de agosto de 2022 e as maiores em
março e abril de 2023, com 685 do total de 1.000 pontos. <=
/span>
Tabela 5 – A
performance da produtividade do INSS do estado do Rio de Janeiro no período=
de
julho/22 a junho/23
SUPERTEC <=
/span>
Média
Desvio padrão
CV
Fonte: Elaboração própria com base nos dados da
pesquisa (2023).
As equações da reta nacional y =3D
0,4672x-20419 e estadual y =3D 1,1032x -49015 apresentam coeficientes angul=
ares
positivos, confirmando o crescimento da pontuação total ao longo do tempo e=
um comportamento
mais acentuado do Estado. Isso demonstra que alguns estados podem ter
apresentado comportamentos diferentes do analisado e acabaram impactando no
desempenho nacional. Entretanto, não foi possível ter acesso aos dados dos
demais estados para poder identificar o comportamento de cada um, podendo s=
er
considerado como uma limitação do estudo.
Ao analisar a regressão linear, observa-se q=
ue, o
R² nacional foi igual a 0,4615 e o R² estadual foi igual a 0,8101. Isso
significa que enquanto no nacional o modelo linear explica 46,15% da variân=
cia
da variável dependente, no estadual o modelo explica 81,01%.
5 VANTAGENS DA
APLICAÇÃO DA MÉTRICA PROPOSTA
<=
/o:p>
Pelo estudo realizado é possível perceber qu=
e são
várias as vantagens sobre o uso regular na aplicação da métrica desenvolvid=
a na
medição e avaliação do desempenho do atendimento aos beneficiários do INSS.=
De forma mais ampla destacam-se as seguintes
vantagens: gerar conhecimento sobre a dimensão do atendimento no curto, méd=
io e
longo prazo; servir de orientação para desenvolver procedimentos de controle
efetivo sobre as demandas do INSS; exercer de forma contínua o gerenciamento
sobre o monitoramento e melhoria do desempenho institucional em virtude de =
sua
capacidade de analisar a produtividade na prestação de serviço do INSS, ao
longo do tempo; dar suporte e sustentação à tomada de decisão sobre a aplic=
ação
de medidas preventivas e corretivas, visando a melhoria do atendimento dos
beneficiários da instituição estudada.
De forma mais prática e específica, destacam=
-se as
seguintes vantágens: possibilitar o monitoramento da fila de requerimentos =
dos
beneficiados da INSS de forma proativa; servir de instrumento gerencial par=
a a
medição, avaliação, análise e comparação do desempenho dos serviços prestad=
os
pelo INSS tanto em nível nacional quanto em nível estadual e, ainda, fazer a
comparação entre eles, mostrando se o desempenho de um estado está abaixo,
acima ou na média nacional, permitindo a adoção de medidas de controle e ju=
ste.
<=
/o:p>
6 CONCLUSÃO
<=
/o:p>
A pesquisa teve como objetivo propor uma mét=
rica
para mensurar a produtividade e a eficiência da prestação de serviços públi=
cos
do INSS. Isso visou auxiliar no processo de gestão e tomada de decisões,
destinadas a melhorar o atendimento ao cidadão, beneficiários do INSS. Para
isso, foi realizada uma pesquisa com características tanto qualitativas como
quantitativas.
A produtividade é um fator importante em tod=
as as
organizações, entretanto, quando se pretende fazer adaptação a empresas
prestadoras de serviços, principalmente as de serviços públicos, como o INS=
S, essa
avaliação se torna desafiadora. Isso ocorre porque ela precisa ir além da r=
azão
entre input e output , devendo incorporar a intangibilidade dos componentes do
produto e a relevância da qualidade nesses resultados. Por isso, a adoção da
Matriz de Produtividade demostrou ser um método apropriado por avaliar tant=
o a
entrada quanto a qualidade da saída.
A mon=
tagem da
Matriz de Produtividade levou em consideração os indicadores Tempo Médio de
Concessão (TMC), o Tempo de Espera de Atendimento Agendado (TMEA), o SUPERT=
EC
que descreve o percentual de processos reabertos, e a Ouvidoria que present=
a o
percentual de manifestações respondidas no prazo legal.
A
pontuação final alcançada representa a produtividade total da instituição no
período analisado, em que recebe influência de cada um dos indicadores
individualmente, de modo a entender a performance
da instituição. Ao longo do período analisado (de julho/22 a junho/23) houv=
e um
aumento na pontuação total do INSS em virtude da tendência da redução nos
tempos TMC e TMEA. As reduções no TMC apresentam maior impacto porque são
atribuídas a elas o maior peso. As variações nos indicadores podem represen=
tar
perda ou ganho de eficiência, bem como a concentração em determinados meses=
de
solicitações que demandam mais ou menos tempo para serem atendidas.
As
vantagens mais significativas da aplicação do método matricial residem no u=
so
gerencial para monitoramento e melhoria do desempenho institucional. Ele po=
ssui
a capacidade de analisar a produtividade na prestação de serviço do INSS, ao
longo do tempo, tanto em nível nacional quanto em nível estadual e, ainda
comparar o desempenho entre eles. Esse método permite identificar se o
desempenho de um estado está abaixo, acima ou na média nacional, permitindo=
a
adoção de medidas de controle e ajuste. Durante o período analisado, foram
observadas tendências de pontuação crescente em ambos os níveis - nacional e
estadual. Além disso, destaca-se que o desempenho do Estado do Rio de Janei=
ro
superou a média nacional.
Entretanto, não foi possível analisar o dese=
mpenho
de outros estados em relação ao nacional e nem fazer a comparação entre
estados, devido à definição do escopo da presente pesquisa. Também não fez
parte do escopo deste estudo analisar os diferentes tipos de serviços
oferecidos pelo INSS e seus impactos na composição dos indicadores que são
selecionados para obter a pontuação total.
Essas limitações podem servir como sugestões=
de
pesquisas futuras.
<=
/o:p>
REFERÊNCI=
AS
ARMIS=
TEAD,
Colin; MACHIN, Simon. Business process management: implications for
productivity in multi-stage s=
ervice
networks. Inter=
national
Journal of Service Industry Management=
(IJSIM) , v. 9, n. 4, p. 323-336, 1998.<=
/o:p>
BANGA=
, Harish
Kumar et al . Produ=
ctivity
improvement in manufacturing industry by lean tool. Materials Today:
Proceedings , v. 28, Part 3, 2020, p. 1788-1794. Dispo=
nível
em: https://www.sciencedirect.com/science/article/pii/S2214785320337561. Ac=
esso
em: 12/ jul. 2023.
BOYNE, George. Concepts and Indicators of Local
Authority Performance: An Evaluation of the
Statutory Frameworks in England and Wales. Public
Money & Management , Vol. 22, No. 2, p. 17-=
24,
2002.
BR=
ASIL. Decreto Nº 3.081, de 10 de junho de
1999 . Aprova a Estrutura Regimental e o Quadro Demonstrativo dos Cargos em
Comissão e das Funções Gratificadas do Instituto Nacional do Seg=
uro
Social - INSS, e dá outras
providências.
BR=
ASIL. Decreto Nº 4.660, de 2 de abril de =
2003 .
Aprova a Estrutura Regimental e o Quadro
Demonstrativo dos Cargos em Comissão e das Funções Gratificadas do Institut=
o Nacional
do Seguro Social - INSS, e dá outras
providências.
BRASIL.
Resolução Nº 201/INSS/DC, de 14 de=
julho
de 2005 . Aprova o Planejamento <=
/span>Anual Integrado do INSS, do exercício de 2005.
BR=
ASIL. Lei
Nº 11.890, de 24 de dezembro de 2008 . =
Dispõe
sobre a reestruturação da composição remuneratória das carreiras de auditor=
ia
da receita federal do brasil e auditoria fiscal do trabalho, de que trata
a lei n° 10.910, de 15 de julho de 2004 e dá outras providências.
BRASIL.
Lei N º 13.249, de 13 de j=
aneiro
de 2016. Institui o Plano Plurianual da União para o período de 2=
016 a 2019. (Brasil, 2016a).
BR=
ASIL. Lei N º 13.341, de 29 de
setembro de 2016. Altera as Leis n º 10.683, de 28 de maio de 2003, que dispõe sobre a
organização da Presidência da República e dos Ministérios, e 11.890, de 24 de dezembro de 200=
8, e
revoga a Medida Provisória nº 717, de 16 de março de 2016. (Brasi=
l,
2016b).
BRASIL.
Resolução N º 554/PRES/INSS, de =
20 de
outubro de 2016. Aprova o Mapa <=
/span>Estratégico para o
quadriênio 2016 - 2019. (Brasil, 2016c).
BRASIL.
Portaria N º 91 /PRES/INSS, de =
19 de
janeiro de 2017 . Estabelece novo modelo
de Fluxos de Atendimento a partir da impla=
ntação do Projeto INSS Digital. (B=
rasil,
2017a).
BRASIL.
Portaria N º 1.106 /PRES/INSS, =
de 30
de junho de 2017. Dispõe sobre procedimentos para expansão do Projeto INSS Digital – Uma nova forma
de atender. (Brasil, 2017b).
BRASIL.
Portaria N º 2.033 /PRES/INSS, =
de 28
de novembro de 2017 . Institui Prova de
Conceito do Projeto
Teletrabalho. (Brasil, 2017c).
BRASIL.
Portaria interinstitucional N º
4/SPREV/SGD/INSS/DATAPREV, de 10 de =
abril
de 2019. Institui Comitê Estratégico e Grupo de Trabalho Interinstituci=
onal
para implementação da Transformação
Digital no âmbito do INSS.
BRASIL.
Resolução PRES/INSS Nº 14 de 1º de
fevereiro de 2021. Altera a Resolução nº
2/CEGOV/INSS, de 31 de
dezembro de 2019. <=
/o:p>
CHEN,=
Clara
Xiaoling; LILL, Jeremy; LUCIANETTI, Lorenzo. Performance measurement system
diversity and product innovation: Evidence from longitudinal survey data. <=
b>Accounting,
Organizations and Society, 2023, 101480. Disponível em: https://w=
ww.sciencedirect.com/science/article/pii/S036136822300051X .
Acesso em: 31 jul. 2023.
CORYD=
ON, Bjarne et =
al .
Government Productivity: unlocking the $3.5 trillion opportunity. Discussion
paper. McKinsey Center for Government , 2017. Disponível em:
https://www.mckinsey.com/industries/public-sector/our-insights/the-opportun=
ity-in-government-productivity?cid=3Deml-web#/.
Acesso em: 4 ago. 2023 .
CRESW=
ELL,
John. Research Design: Qualitative, Quantitative and Mixed Method Approa=
ches .
4a. ed. Thousand=
Oaks,
CA, 2014.
DENHARDT,
Robert. Teorias da Administração Pública . São Paulo: Cengage Learnin=
g,
2012.
FARIA, J. Apontamentos Gestão Da Qualidade Total . s. n. t.,
2018.
GIL,
Antonio Carlos. Como Elaborar Projeto de Pesquisa . 7ª. Ed. São Paulo:
ATLAS, 2022.
GRÖNROOS, Christian; OJASALO, Katri. Service
Productivity - Towards a Conceptualization of the Transformation of Inputs into Economic Results in Services. =
Journal of Business Research , v. 57,
n. 4, p. 414-423, 2004.
HILHO=
RST, Cokky
et al . Efficiency gains in publ=
ic
service delivery through information technology in municipalities. <=
b>Government Information Quarte=
rly , V. 39, Issue 4, n.101724, 2=
022.
Disponível em: https://www.sciencedirect.com/science/article/pii/S0740624X2=
2000570.
Acesso em: 23 jul. 2023.
HODGK=
INSON,
Ann. Productivity measurement and enterprise bargaining – the local government perspective. International Journal of Public Sector
Management , Vol. 12, No. =
6, p. 470-481, 1999. =
JÄÄSK=
ELÄINEN,
Aki. Identifying a suitable app=
roach for
measuring and managing public s=
ervice
productivity. Electronic Journal of
Knowledge Management . 2009, Vol. 7, N° 4,
pp. 447-458.
JÄÄSK=
ELÄINEN,
Aki; TAPPURA, Sari; PIRHONEN, Julius. The path toward successful safety
performance measurement. Journal of Safety Research , V. 83, 2022, Pa=
ges
181-194, ISSN 0022-4375. Disponível
em: https://www.sciencedirect.com/science/article/pii=
/S0022437522001281 . Acess=
o em:
27 jul. 2023.
JACOB=
S,
Robert; CHASE, Richard. Operations=
and
Supply Chain Management . 15 ed. =
New
York: McGraw-Hill Education, 2018.
JOHNS=
TON,
Robert; JONES, Peter. Service productivity towards understanding the
relationship between operationa=
l and
customer productivity. Internation=
al
Journal of Productivity and P=
erformance
Management , v. 53, n. 3, p. 201-213, 2004. DOI:
https://doi.org/10.1108/17410400410523756.
KORHO=
NEN,
Tuomas et al . How performance
measurement can support achieving success in project-based operations. I=
nternational
Journal of Project Management , V. 41, Issue 1, 102429, 2023. Disponível em: https://www.sciencedirect.com/science/article/pii=
/S0263786322001326 . Acesso em: 25 jul. 2023.
LO=
VELOCK,
Christopher; WIRTZ, Jochen. Market=
ing de
Serviços: pessoas, tecnologia e resultados. São Paulo: Pearson Prentice Hall, 2006.
MAHMO=
OD, Kashif
et al . A Performance Evaluation
Concept for Production Systems in an SME Network. Procedia CIRP , V. 72, 2018, P. 603-608. IS=
SN
2212-8271. Disponível em: https://www.sciencedirect.com/science/article/pii=
/S221282711830341X . Acesso em: 12 jul. 2023.
MARTI=
N,
Claude; HORNE, David; CHAN, Winnie. A perspective on client productivity in=
business-to-business consulting ser=
vices.
Inter=
national
Journal of Service Industry Man=
agement , v. 12, n. 2, p. 137-157, 2001. DOI:=
https://doi.org/ 10.1108/09564230110387515.
MAUREL, Christopher et al.
Characterization and definition of public performance: an application to lo=
cal
government authorities. Gestion et management public , V. 2 N. 3,=
p.
23-44. Disponível em: https://www.cairn.info/revue-gestion-et-management-pu=
blic.htm.
Acesso em: 30 jul. 2023 .
MAYLO=
R,
Harvey et al . Mind the gap: Tow=
ards
performance measurement beyond a plan-execute logic, International Journ=
al
of Project Management , V. 41, Issue 4, 102467, 2023. Disponível em: https://www.sciencedirect.com/science/article/pii=
/S0263786323000315 . Acesso em: 27 jul. 2023.
MELO, P. A. A.; PEREIRA, A. V. S.; OLIVEIRA, A. H. R.;
D’ELIA, B. B. Aprendizagem e desenvolvimento de pessoas . R=
io
de Janeiro: FGV, 2016.
MELLO, Cássia
Juliano; NUNES, Pereira Moema. A Influência das Ferramentas Tecnológicas de
Comunicação nas Relações Pessoais Dentro de um Ambiente Organizacional. =
Revista
NAVUS, Florianópolis , v. 10, p;01-18, jan./dez. 2020. Disponível em:
https://navus.sc.senac.br/index.php/navus/article/view/1270/pdf. Acesso em:=
13
ago. 2023.
MINISTÉRIO DA
PREVIDÊNCIA SOCIAL [2021]. Dados estatí=
sticos
- Previdência Social e INSS, 2021 Acesso em: 12 ago. 2023.
MONEN=
I,
Farhang; NI, Jun. Quality Can Improve as Productivity Increases:
Machining as Proof. Procedia
Manufacturing , v.
53, 2021, p. 299-309. Disponível em:
https://www.sciencedirect.com/science/article/pii/S235197892100038X. Acesso
em: 12 jul. 2023.
NGUYE=
N, Hong
Ngoc; O’DONNELL, Christopher. Estimating the cost effici=
ency
of public service providers in the presence of demand uncertainty. Europ=
ean
Journal of Operational Research , V. 309, Issue 3, p. 1334-1348, 2023.
Disponível em:
https://www.sciencedirect.com/science/article/pii/S0377221723001558. Acesso=
em:
23 jul. 2023.
OECD.=
OECD compendium of productivity=
indicators 2019 . Relatório, 2019.
OJASA=
LO, Katri.
Conceptualizing productivity in se=
rvices .
Helsinki: Swedish School of E=
conomics and Business
Administration, 1999.
PALUDO, Augustinho. Administração pública. 3ª ed. Rio de Janeiro: Elsevier, 2013.
RUTKAUSKAS, <=
/span>Jonas; PAULAVIČIENĖ, Eimené. Conc=
ept of Productivity in Service Sector. The Engineering Economics , V. 43, p. 35-41, 2005. Disponível em:
https://api.semanticscholar.org/CorpusID:167766412. Acesso em: 15 abr. 2022=
.
SAHAY=
, B.
S. Multi-Factor Productivity Measurement Model for Service Organization. International
Journal of Productivity and Performance Measurement , v. 54, n. 1, p. 7-=
22, 2005.
SCERR=
I,
Moira; AGARWAL, Renu. Service Enterprise Productivity in Action: measuring
service productivity. Journal of Service Theory and Practice , V. 28,=
n.
4, 2018, pp. 524-551. DOI: https://doi.org/10.1108/JSTP-06-2=
017-0104 .
SILVA, Laura
Angélica Moreira; SANTOS, Fernando Burgos Pimentel dos; MEDEIROS, Anny Kari=
ne
de. Orçamento Público Municipal da Cultura: Função, Subfunção ou Sem-Função=
? Cadernos
Gestão Pública e Cidadania , v. 23, n. 76, p. 376-396, 2018.
TOTI, Aline
Rodrigues; ANJO, José Edemir da Silva. A Implantação do Sistema Eletrônico =
de
Informações em uma Superintendência Reginal de Ensino de Minas Gerais. R=
evista
NAVUS, Florianópolis , v. 12, p.01-16, jab./dez.2022. Disponível em:
https://navus.sc.senac.br/index.php/navus/article/view/1689/pdf. Acesso em:=
14
ago. 2023.
VERGARA,
Sylvia Constant. Projetos e Relatórios de Pesquisa em Administração .=
14ª.
Ed. São Paulo: Atlas, 2013.
WA=
46;NIEWSKI,
Piotr. Informal performance measurement in small enterprises. Procedia Computer Science , V. 192, Pages 3310-3319, 20=
21.
Disponível em: https://www.sciencedirect.com/science/article/pii=
/S1877050921018433 . Acess=
o em:
25 jul. 2023.
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Content-Location: file:///C:/AC096630/Navus_v13_1800_arquivos/header.htm
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Desenvolvimento e Aplicação de uma Métrica de Avaliação=
da
Prestação de Serviço de um Órgão Federal
Antônio Maria de
Carvalho Negrão; Daniel Ribeiro de Oliveira; Fabrício Molica de Mendonça; S=
aulo
Barbara de Oliveira; Geferson Michel Santos de Sales
IS=
SN
2237-4558 • Navus
• Florianópolis • <=
/span>SC • <=
/span>v.
12 • p. 01- 23 • jan./dez. 2022
21
ISSN 2237-4558
•
Navus •
Florianópolis • SC •
v.9 • n.2
• p. XX-XX • <=
/span>abr./jun.
2019
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