Empowering human resource functions with data-driven decision-making in start-ups: a narrative inquiry approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Deepkumar Varma ◽  
Pankaj Dutta
Keyword(s):  
Decision Making ◽  
Narrative Inquiry ◽  
Technology Implementation ◽  
Data Driven ◽  
Structured Interviews ◽  
New Paradigm ◽  
Data Driven Decision Making ◽  
Content Type ◽  
Start Up ◽  
Start Ups

Purpose Across industries, firms want to adopt data-driven decision-making (DDDM) in various organizational functions. Although DDDM is not a new paradigm, little is known about how to effectively implement DDDM and which problem areas to focus on in these functions. This study aims to enable start-ups to use DDDM in human resources (HR) by studying five HR domains using a narrative inquiry technique and aims to guide managers and HR practitioners in start-ups to enable data-driven decisions in HR. Design/methodology/approach This study adopts the narrative inquiry technique by conducting semi-structured interviews with HR practitioners and senior members handling HR functions in start-ups. Interview memos are thematically analyzed to identify repeated ideas, concepts or elements that become apparent. Findings The study findings indicate that start-ups need to have canned operational reports with right attributes in each of these HR domains, which members should use when performing HR tasks. Few metrics, like cost-to-hire in recruitment, distinctly surfaced relatively higher in importance that each start-up, should compute and use in decision-making. Practical implications Managers, HR practitioners and information technology implementation teams will be able to consume the findings to effectively design or evaluate HR processes or systems that empower decision-making in a start-up. Originality/value Start-ups have a fast-paced culture where creativity, relationships and nimbleness are valued. Prevalent decision models of larger organizations are not suitable in start-ups’ environments. This study, being cognizant of these nuances, takes a fresh approach to guide start-ups adopt DDDM in HR and identify key problem areas where decision-making should be enabled through data.

Think human, act digital: activating data-driven orientation in innovative start-ups

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anna Visvizi ◽  
Orlando Troisi ◽  
Mara Grimaldi ◽  
Francesca Loia
Keyword(s):  
Innovation Management ◽  
Strategic Orientation ◽  
Constructivist Grounded Theory ◽  
Data Driven ◽  
Structured Interviews ◽  
Content Type ◽  
Proactive Management ◽  
Start Up ◽  
Innovation Patterns ◽  
Start Ups

PurposeThe study queries the drivers of innovation management in contemporary data-driven organizations/companies. It is argued that data-driven organizations that integrate a strategic orientation grounded in data, human abilities and proactive management are more effective in triggering innovation.Design/methodology/approachResearch reported in this paper employs constructivist grounded theory, Gioia methodology, and the abductive approach. The data collected through semi-structured interviews administered to 20 Italian start-up founders are then examined.FindingsThe paper identifies the key enablers of innovation development in data-driven companies and reveals that data-driven companies may generate different innovation patterns depending on the kind of capabilities activated.Originality/valueThe study provides evidence of how the combination of data-driven culture, skills' enhancement and the promotion of human resources may boost the emergence of innovation.

scholarly journals Data competence maturity: developing data-driven decision making

2018 ◽  
Vol 11 (2) ◽  
pp. 139-158 ◽  
Author(s):  
Thomas G. Cech ◽  
Trent J. Spaulding ◽  
Joseph A. Cazier
Keyword(s):  
Decision Making ◽  
Secondary Education ◽  
Data Science ◽  
Data Driven ◽  
Decision Making Process ◽  
Maturity Model ◽  
Data Driven Decision Making ◽  
Content Type ◽  
Development Data ◽  
Education Performance

Purpose The purpose of this paper is to lay out the data competence maturity model (DCMM) and discuss how the application of the model can serve as a foundation for a measured and deliberate use of data in secondary education. Design/methodology/approach Although the model is new, its implications, and its application are derived from key findings and best practices from the software development, data analytics and secondary education performance literature. These principles can guide educators to better manage student and operational outcomes. This work builds and applies the DCMM model to secondary education. Findings The conceptual model reveals significant opportunities to improve data-driven decision making in schools and local education agencies (LEAs). Moving past the first and second stages of the data competency maturity model should allow educators to better incorporate data into the regular decision-making process. Practical implications Moving up the DCMM to better integrate data into their decision-making process has the potential to produce profound improvements for schools and LEAs. Data science is about making better decisions. Understanding the path laid out in the DCMM to helping an organization move to a more mature data-driven decision-making process will help improve both student and operational outcomes. Originality/value This paper brings a new concept, the DCMM, to the educational literature and discusses how these principles can be applied to improve decision making by integrating them into their decision-making process and trying to help the organization mature within this framework.

Exploring the role of business relationships in start-ups’ life cycles

IMP Journal ◽  
2018 ◽  
Vol 12 (3) ◽  
pp. 519-543
Author(s):  
Chiara Cantù ◽  
Sepe Giorgia ◽  
Alessandra Tzannis
Keyword(s):  
Life Cycle ◽  
Secondary Data ◽  
Life Cycles ◽  
Business Relationships ◽  
Structured Interviews ◽  
Content Type ◽  
Strategic Resources ◽  
Start Up ◽  
Start Ups

Purpose Differently from previous works that focused on the entrepreneur and on his ability to manage social relationships, the purpose of this paper is to investigate the role of business relationships in the different stages of the life cycle of a start-up. Design/methodology/approach Since the paper aims to explore startups’ evolutionary phenomenon, it adopts a qualitative abductive methodology, presenting an in-depth study of two innovative Italian start-ups. The research is based on two steps. In the first one, the authors collected secondary data from start-ups’ reports and documents, financial indicators (when available) and processed them to understand their background. In the second one, the authors conducted ten semi-structured interviews, including face-to-face interviews, phone interviews and video conferences. Findings The paper presents a relationship-based life cycle model composed of four different stages, depending on the number and role of relationships developed. Indeed, since the beginning, start-ups adopt a relational approach and their evolution involves the shift from the focus on the entrepreneur to the centrality of a network approach based on interconnected relationships. The entering into a new stage of life cycle depends on relationships, mainly based on connected actors and resources shared and combined. Even if a key role is assumed by technology, the main resource is identified in the knowledge concerning the customer/user’s needs that require marketing competencies, human resources, relational capabilities. Thus, the shift from one stage to the next in the start-up’s life cycle is possible thanks to a parallel shift from a focus on the activities to a focus on those strategic and heterogeneous actors that ensure activities. Originality/value In a traditional perspective, the start-up’s life cycle depends on activities, financial resources and revenues, as stated by previous life cycle models. In a different perspective, as depicted in our analysis, the evolution of a start-up depends on the portfolio of their business relationships. The role of business relationships is hence to facilitate the interconnections within specialized key actors, which allow start-ups to access strategic resources. These resources are essential in order to develop the activities that characterize the specific stage of the life cycle.

Enterprise survival in the high-tech community: persuasion and power in board decisions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ronit Yitshaki ◽  
Eli Gimmon ◽  
Susanna Khavul
Keyword(s):  
High Tech ◽  
Structured Interviews ◽  
Board Size ◽  
Term Survival ◽  
Long Term Survival ◽  
Content Type ◽  
Board Processes ◽  
Start Up ◽  
Start Ups

Purpose This study aims to examine the extent to which board size, the use of power by venture capital investors and entrepreneurs’ interpersonal tactics such as persuasion to sway board decisions, influence the long-term survival of start-ups. Design/methodology/approach This study used a mixed-methods approach. The quantitative part is based on data collected from 179 chief executive officers (CEOs) of high-tech start-ups community financed by venture capitalists (VCs) in Israel of which 59 did not survive. To achieve a better understanding of these findings, semi-structured interviews with 12 entrepreneurs were conducted. Findings Smaller boards were positively associated with venture survival. The use of power by VC investors positively influenced start-up survival. CEO persuasion had a negative effect on venture survival; however, its interaction with board size suggests that it had a lesser effect on very small boards. Practical implications Although investors’ control over decision-making contributes to long-term survival, entrepreneurs should be aware of the possible detrimental effects of exercising a high level of persuasion in board processes. The findings also suggest that a small board size is preferable for start-up survival. Originality/value Exploring the effect of board processes on venture survival is considered complex. A unique sample of high-technology start-ups consisting of both surviving and failed start-ups was analyzed to explore the effects of persuasion and power in board processes.

scholarly journals Data-driven decision-making in creating class rosters

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rebecca Wolf ◽  
Joseph M. Reilly ◽  
Steven M. Ross
Keyword(s):  
Decision Making ◽  
Student Learning ◽  
Low Income ◽  
School Leaders ◽  
Data Driven ◽  
Data Driven Decision Making ◽  
Content Type ◽  
Use Of Data ◽  
Using Data ◽  
Rich Data

PurposeThis article informs school leaders and staffs about existing research findings on the use of data-driven decision-making in creating class rosters. Given that teachers are the most important school-based educational resource, decisions regarding the assignment of students to particular classes and teachers are highly impactful for student learning. Classroom compositions of peers can also influence student learning.Design/methodology/approachA literature review was conducted on the use of data-driven decision-making in the rostering process. The review addressed the merits of using various quantitative metrics in the rostering process.FindingsFindings revealed that, despite often being purposeful about rostering, school leaders and staffs have generally not engaged in data-driven decision-making in creating class rosters. Using data-driven rostering may have benefits, such as limiting the questionable practice of assigning the least effective teachers in the school to the youngest or lowest performing students. School leaders and staffs may also work to minimize negative peer effects due to concentrating low-achieving, low-income, or disruptive students in any one class. Any data-driven system used in rostering, however, would need to be adequately complex to account for multiple influences on student learning. Based on the research reviewed, quantitative data alone may not be sufficient for effective rostering decisions.Practical implicationsGiven the rich data available to school leaders and staffs, data-driven decision-making could inform rostering and contribute to more efficacious and equitable classroom assignments.Originality/valueThis article is the first to summarize relevant research across multiple bodies of literature on the opportunities for and challenges of using data-driven decision-making in creating class rosters.

The role of start-up incubators in cooperation networks from the perspective of resource dependence and interlocking directorates

2019 ◽  
Vol 57 (10) ◽  
pp. 2816-2836 ◽  
Author(s):  
Anderson Galvão ◽  
Carla Marques ◽  
Mário Franco ◽  
Carla Mascarenhas
Keyword(s):  
Resource Dependence ◽  
Transaction Cost Economics ◽  
Resource Dependence Theory ◽  
Structured Interviews ◽  
Interlocking Directorates ◽  
Content Type ◽  
Scarce Resources ◽  
Start Up ◽  
Dependence Theory ◽  
Start Ups

Purpose Based on resource dependence theory and the concept of interlocking directorates, the purpose of this paper is to understand the importance of networks for start-ups and the role incubators play in these companies’ networking processes. Design/methodology/approach The research was conducted through semi-structured interviews with the entrepreneurs responsible for three start-ups and the heads of their incubators. The interview data were subjected to content analysis using NVivo software. Findings The results indicate that start-ups often resort to networks to overcome their weak reputations and scarce resources. Incubators play a quite important role in this process since they promote events that encourage the creation of partnerships and networks either between start-ups within the same incubator or with external institutions. In addition, the results reveal that most cooperation networks are informal and that they fulfil needs that start-ups are not yet able to meet themselves, for example, when they compete for public tenders. Practical implications The present study explored this topic from two perspectives (i.e. start-ups and incubators). This approach facilitated the identification of the main features upon which start-ups depend, the entities to which these companies turn for help, the kind of communication in which they usually engage, the primary advantages of establishing cooperation networks and the main types of support given by incubators. Originality/value Most studies of cooperation networks are based on transaction cost economics, a resource-based perspective and/or institutional theory. In contrast, this study innovated by applying resource dependence theory and the concept of interlocking directorates, which provided an alternative explanation regarding cooperation networks’ importance to start-ups and incubators’ roles in these companies’ networking processes.

Entrepreneurial cognition and premature scaling of startups: a qualitative analysis of determinants of start-up failures

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
George C. Joseph ◽  
Nimitha Aboobaker ◽  
Zakkariya K.A.
Keyword(s):  
Decision Making ◽  
Cognitive Biases ◽  
Early Stage ◽  
Self Regulation ◽  
Behavioral Patterns ◽  
Content Type ◽  
Attitude Theory ◽  
Start Up ◽  
Entrepreneurial Cognition ◽  
Start Ups

Purpose This study aims to explore the behavioral patterns of entrepreneurs, their cognitive styles and personality characteristics that can lead to a self-destructive chain of events during the transition from a fledgling business to one capable of long-term, profitable growth. This study adopts the self-regulation attitude theory to uncover the reasons for premature start-up scaling, which will help founders to study on their cognitive biases, emotions and behaviors and make efforts to do what does not come naturally to them. Design/methodology/approach The respondents for this qualitative study were selected from a group of entrepreneurs with extensive experience with technology start-ups that have either failed or succeeded during their development stages. In-depth semi-structured interviews were conducted with eight participants, who were selected through snowball sampling, on the theme of understanding “How do premature scaling mistakes happen?”. Thematic analysis was used to unearth common themes. Findings The results of this study identified the following themes, “comparison,” “emotional over-reaction,” “impatience,” “mistaken customer priorities,” “overestimation” and “overconfidence,” which eventually leads to premature scaling. The underlying decision-making heuristics of entrepreneurs can be identified as engulfed in different cognitive biases and emotions resulting in negative behavioral patterns, as in the case of premature scaling. Of the six themes, “comparison,” “mistaken customer priorities,” “overestimation” and “overconfidence relates to cognitive bias” and “emotional over-reaction” and “impatience” relate to emotional factors. Research limitations/implications The study was made possible with the support of the voluntary participants chosen by purposive and snowballing data sampling. The interviewee and interviewer biases could have also crept in as part of this qualitative approach. The study pertains only to start-ups in the information technology sector and further studies need to be done to generalize the results across industries as well. Practical implications This early-stage underestimation of unexpected obstacles in the entrepreneurship journey necessitates a focus on the entrepreneur too, as much as the concept. In these hectic and fast-paced circumstances, aspiring entrepreneurs must be taught how to deal objectively with themselves and others, as well as think strategically. Leaders who scale do so because they take purposeful measures to overcome their weaknesses through self-discipline, soliciting advice from others and using their right to change their attitude and points of view. Originality/value The study frames the new approach into the entrepreneurial literature, linking it to self-regulation attitude theory and adds to the nascent literature on neuroentrepreneurship which discuss entrepreneurial cognition, decision-making, and entrepreneurial behavior. This study attempted to explore the reasons behind the premature scaling of startups on an individual level. This study is pioneering in exploring the cognitive factors underlying an entrepreneur’s decision that results in premature scaling. This study provides insights for academicians, entrepreneurs and policymakers and helps understand the cognitive journey that leads to premature scaling.

scholarly journals Angel investors’ predictive and control funding criteria

2018 ◽  
Vol 20 (1) ◽  
pp. 34-56 ◽  
Author(s):  
James M. Crick ◽  
Dave Crick
Keyword(s):  
Decision Making ◽  
Business Model ◽  
Business Models ◽  
Management Teams ◽  
Specific Reference ◽  
Structured Interviews ◽  
Content Type ◽  
And Control ◽  
Start Ups ◽  
Angel Investors

PurposeThis study aims to investigate the question involving what factors affect angel investors’ decision-making in funding new start-ups with specific reference to their evolving business models. Without funding and access to networks and experience, certain entrepreneurs will not get their business model through the start-up phase.Design/methodology/approachData arise from 20 semi-structured interviews with angel investors in New Zealand plus supplementary interviews with business incubator managers and textual data.FindingsThe findings suggest a degree of causation-based decision-making, in that certain linear thinking was evident. The implication is that, without the ability of the entrepreneurs to convince the investors about key criteria in their decision-making, investment is unlikely. Nevertheless, a degree of effectuation-based decision-making was also evident, the implication being investors having to balance risk/reward decisions in the context of their own perceptions of affordable losses against an evolving business model. However, angel investors may take on co-investment, including from overseas, that takes decision-making away from management teams.Originality/valueThe study draws attention to the need to consider entrepreneurial ecosystems in angel investor’s decision-making and especially those with a small domestic market that may require management teams to look for scalability internationally. Furthermore, an effectuation lens contributes to knowledge in respect of predictive and control criteria, in particular, assessing risks and rewards against affordable losses involving an evolving business model.

The business of the library is service

2017 ◽  
Vol 118 (7/8) ◽  
pp. 447-450
Author(s):  
Bruce E. Massis
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Design Methodology ◽  
Business Practice ◽  
Data Driven ◽  
Business Practices ◽  
Data Driven Decision Making ◽  
Content Type

Purpose The purpose of this paper is to suggest that today’s libraries function using business practices in its management of the library to ensure that its service-based mission is respected. Design/methodology/approach Literature review and commentary on this topic that has been addressed by professionals, researchers and practitioners. Findings Libraries have learned from business the importance of using not only the business practice of using a vigorous level of data-driven decision-making, but data-driven reporting as well to a public that expects a higher level of scrutiny, clarity and precision. Paired with evidence from those who have benefitted from the library’s programs and services most visibly, this combination of data and human-driven anecdotes can serve as the optimum marriage of business and service-based confirmation of library success. Originality/value The value in exploring this topic is to make the distinction between libraries whose supporters expect it to be formally managed like a business as opposed to those who suggest that business practices be used in library operations to ensure its mission as a service-based entity is maintained.

Data-driven decision-making in the library

2016 ◽  
Vol 117 (1/2) ◽  
pp. 131-134 ◽  
Author(s):  
Bruce Massis
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Data Driven ◽  
Data Driven Decision Making ◽  
Content Type ◽  
Aggregated Data ◽  
Strategic Direction ◽  
Reporting Decisions ◽  
Using Data ◽  
Support Decision Making

Purpose – The purpose of this paper is to describe the current environment for libraries to consider the value of using data to support decision-making. Design/methodology/approach – This paper contains literature review and commentary on this topic that has been addressed by professionals, researchers and practitioners. Findings – In developing a library’s strategic direction, it is essential that evidentiary data be referenced to supplement the organization’s rationale for decision-making. There is an expectation by stakeholders that libraries are able to generate reports and decisions based on aggregated data for in-demand reporting. Therefore, capturing, analyzing and reporting decisions based on data are indispensable in today’s libraries. Originality/value – The value in addressing this topic is to examine the option by libraries to use data to support data-driven decision-making.

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