Company Success in Manufacturing Organizations

A Holistic Systems Approach

Ana M. Ferreras, Lesia L. Crumpton-Young

• Publisher: CRC Press
• Year: 2017
• ISBN:
  9781351644594
• Edition: 1
• Topic: Business
• Subtopic: Management
• Index: Business

In the past, company success was typically measured by financial indicators. Lately though, non-financial measures such as employee morale have become popular. Although there are approaches that look into quantitative and qualitative performance measures affecting company success, none of them characterize it in a holistic way, combining all the critical performance measures. This book presents a multifaceted approach that prepares engineers and future organizational leaders/managers to measure, monitor, and predict company success in a more meaningful way.

chapter one

Company success in the twenty-first century

Manufacturing is nowadays considered the single most important industry (70%) for a country’s economic health (Selko 2012). Company leaders—from the executive team down to the managers and shift supervisors of individual plants—have the power to give their organizations a true competitive advantage. Increasingly, winning companies will seize this opportunity and adapt their core beliefs, starting now (Hammer and Somers 2015).

Data analytics has become a well-known tool recently since more organizations are using it to know where they stand. The Harvard Business Review report published in 2012 titled The Evolution of Decision Making: How Leading Organizations Are Adopting a Data-Driven Culture presents a survey data and analysis of 646 executives, managers, and professionals, along with more than 10 in-depth interviews with individuals whose companies are at the forefront of adopting a data-driven culture. The survey finds that 11% of the responding organizations are in the group that has integrated analytics across the entire organization. While respondents’ companies usually recognize the need to step up decision-making abilities, many do not have all processes in place to meet the challenge. For example, only a quarter of those in the survey have a formal, corporate-wide decision-making process. One-fifth says their decision-making processes are inconsistent or at best have an informal process. Survey respondents noted frustration with their organizations’ current states on decision-making. Many respondents note that in addition to being able to make decisions faster, they are also making better decisions by using the tools in a data-driven culture. “The economy has become so competitive that you have to use analytics to compete,” explains Christopher C. Williams, strategy executive of J. P. Morgan Chase. The companies that have moved to fact-based, evidence-based decision-making—which is honed against managerial instincts—are simply making decisions superior to those of the companies that still make decisions based on “gut feeling.” Superior companies are doing something differently, which is building an ecosystem so executives understand all the linkages, connections, and historical bases for their decisions. These executives are making wiser and more strategic decisions today than ever (Harvard Business Review 2012). Data-driven decision making gives corporate leaders a greater chance to make wiser decisions based on evidence-based and company performance.

1.1What drives success?

PwC Strategy& developed a web-based survey in 2013 where 720 executives selected up to three public companies within their industry and commented on what drives success for those companies as well as their own company. The survey assessed the relationship between companies’ approach to value creation and their performance. The participants also identified the main challenges companies face in strategy development and assessed the role that a strong identity plays in promoting a company’s success. The survey found that there is no dominant strategy or school of strategy. Companies that owe their success to more asset-driven factors (economies of scale, lucrative assets, or diversification) have measurably lower performance. PwC states that what drives success is the importance of a clear identity and the top issues in strategic development. The survey found out that the common issues companies face in developing strategy are: (1) having too many strategic initiatives (29% respondents), and (2) focusing too much on short-term performance improvement and too little on what will create long-term success (27% respondents). Also, decision makers might select and pursue a bad strategy. Overall, only about one out of three respondents (36%) indicated that the top leaders of their companies were effective at both strategy development and execution, although both dimensions strongly correlate with company performance (Kleiner and Kubis 2013; Leinwand and Mainardi 2013).

Success is a complex achievement that cannot be evaluated or measured by looking into a single area or factor. Osborne and Gaebler (1992) stated:

1.If you don’t measure results, you can’t tell success from failure

2.If you can’t see success, you can’t reward it—and if you can’t reward success, you are probably rewarding failure

3.If you can’t recognize failure, you can’t correct it

1.2Manufacturing leaders and their complex decisions

Organizational decisions are made by the highest level of any business where leaders, top managers, and owners are commonly found. Corporate leaders deal with complex problems and decisions that significantly affect the company success. Organizational managers in manufacturing enterprises need more decision-making tools, methods, and techniques to measure company success and predict its future performance.

Organizational decisions continue to become more complex for top managers considering the large amount of poorly quantified qualitative performance measures that affect company success. Organizational decision makers frequently face high-risk decisions, which entail large and complex data as well as external factors that influence organizational success. Many organizational leaders do not measure critical performance measures essential to achieve company success or they fail to use the data collected to make better decisions. Understanding the significance and complexity of organizational performance measures can help to develop more realistic tools, methods, and techniques that combined can to assist organizational decision makers.

Decision makers for manufacturing companies are looking to gain better visibility into key performance indicators, both in the back office and on the manufacturing floor. After all, it is difficult, if not impossible, to improve processes that are not measured. For manufacturing companies, the pressures of the global economy require a constant commitment to establishing competitive advantages.

1.3Decision-making in manufacturing organizations

These types of decisions are the most unstructured, uncertain, and risky, partly because they reach so far into the future that is hard to control them (Harris 1998).

Decisions should be made and evaluated at all the business levels, but unfortunately many organizations experience a large amount of decisions at the operational level, which indicates that not enough organizational thinking and planning has been previously performed (Harris 1998). This creates a reactive organization, responding to external forces around the business and never getting control of the organization. Customer satisfaction, supply change, environmental factors, and economic demands compel organizations to achieve a variety of objectives simultaneously, but often these objectives are in conflict.

Schiemann and Lingle performed in-deep research and studies on what they defined as measurement-managed organizations (Schiemann and Lingle 1999). In one of their studies performed in 1996, they studied 58 measurement-managed organizations versus 64 nonmeasurement-managed organizations and they found that 97% of measurement-managed organizations reported success with major change efforts—versus only 55% of nonmeasurement-managed organizations. In addition, similar differences were reported for being perceived as an industry leader over 3 years (74% vs. 44%) and being reported as financially ranked in the top third of their industry (83% vs. 52%) (Lingle and Schiemann 1996). Baltazar Herrera (2007) stated that today’s organizational performance measures are financial and nonfinancial, qualitative and quantitative, and hard (financial and operating efficiency) and soft (customer satisfaction and employee engagement) (Teague and Eilon 1973).

1.4Toward a holistic characterization of company success

Although company success has been financially characterized before, a reliable organizational performance methodology that provides a systematic measurement approach based on the company success components—profit, productivity, efficiency, quality, employee morale, safety and ergonomics—has never been developed. In addition, a holistic model to evaluate safety and ergonomics, quality, and employee morale has also been developed. Furthermore, a company success index model that encompasses a large amount of quantitative and qualitative performance measures is essential for manufacturing leaders. Considering the inevitable situation of dealing with qualitative data, different approaches are presented in this book to quantify qualitative measures and combine them with quantitative measures.

To achieve such a complex model, it is imperative to identify performance measures for profit, ergonomics, safety, employee morale, quality, efficiency, and productivity that represent company success in the manufacturing sector and develop a holistic index model that encompasses all these areas.

While business leaders frequently set up organizational goals, they do not have a holistic model that assists them in collecting and analyzing key performance measures systematically. Although there are many indices in the market ...

Table of contents

• Cover
• Half Title
• Industrial Innovation Series
• Title Page
• Copyright Page
• Contents
• Preface
• Acknowledgements
• Authors
• Chapter 1: Company success in the twenty-first century
• Chapter 2: Modeling company success : A novel approach
• Chapter 3: Employee morale : The Ferreras model
• Chapter 4: Modeling quality using quantitative and qualitative performance measures
• Chapter 5: A new model to evaluate and predict ergonomics and safety
• Chapter 6: Profit, productivity, and efficiency within company success
• Chapter 7: A company success index model for manufacturing organizations
• Appendix A: Organizational leader questionnaire
• Appendix B: Plant manager questionnaire
• Appendix C: Glossary of terms
• Appendix D: Employee morale survey
• Appendix E: Checklist for a great place to work
• Appendix F: OSHA ergonomic and safety guidelines assessment
• Index