scholarly journals The Four Most Crucial Elements of Conducting Sales Territory Segmentation at Scale

2020 ◽  
pp. 1-4
Author(s):  
Venketesh Iyer
Keyword(s):  
Data Quality ◽  
Customer Experience ◽  
Data Driven ◽  
Data Governance ◽  
Cause Analysis ◽  
Root Cause ◽  
Fundamental Building Block ◽  
Allocation Process ◽  
Governance Models

The most fundamental building block of any organization is Data; data is critical to any organization’s success. Getting data governance and quality right, can significantly improve the quality of sales planning and result in an intelligent data-driven territory allocation process. On the contrary, poor data quality and loose governance models often lead to laborious territory planning cycles, sub-optimal sales rep to account mapping and poor customer experience. Poor data quality could also result in an over- or under-allocation of a sales person’s territory and can result in poor customer experience and even attrition. On the operational side, this could result in poor forecasting, inefficient revenue attribution, tedious reporting exercises (due to lack of data modeling), and a significantly delayed root cause analysis when companies miss financial goals.

scholarly journals Why Do Patients Leave against Medical Advice? Reasons, Consequences, Prevention, and Interventions

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 111
Author(s):  
Asseel Albayati ◽  
Steven Douedi ◽  
Abbas Alshami ◽  
Mohammad A. Hossain ◽  
Shuvendu Sen ◽  
...  
Keyword(s):  
Hospital Admissions ◽  
Medical Advice ◽  
Preventive Strategies ◽  
Against Medical Advice ◽  
Cause Analysis ◽  
Persistent Problem ◽  
Root Cause ◽  
Discharge Against Medical Advice ◽  
Leaving Against Medical Advice

Background: A patient decides to leave the hospital against medical advice. Is this an erratic eccentric behavior of the patient, or a gap in the quality of care provided by the hospital? With a significant and increasing prevalence of up to 1–2% of all hospital admissions, leaving against medical advice affects both the patient and the healthcare provider. We hereby explore this persistent problem in the healthcare system. We searched Medline and PubMed within the last 10 years, using the keywords “discharge against medical advice,” “DAMA,” “leave against medical advice,” and “AMA.” We retrospectively reviewed 49 articles in our project. Ishikawa fishbone root cause analysis (RCA) was employed to explore reasons for leaving against medical advice (AMA). This report presents the results of the RCA and highlights the consequences of discharge against medical advice (DAMA). In addition, the article explores preventive strategies, as well as interventions to ameliorate leaving AMA.

Root-cause analysis of process-data quality problems

2021 ◽  
pp. 1-25
Author(s):  
Robert Andrews ◽  
Fahame Emamjome ◽  
Arthur H.M. ter Hofstede ◽  
Hajo A. Reijers
Keyword(s):  
Data Quality ◽  
Root Cause Analysis ◽  
Process Data ◽  
Cause Analysis ◽  
Root Cause

Datengetriebene Steigerung der Verfügbarkeit/Data-supported root cause analysis to increase the availability of machine tools. Data-driven availability increase

2020 ◽  
Vol 110 (07-08) ◽  
pp. 532-535
Author(s):  
Eckhart Uhlmann ◽  
Roman Dumitrescu ◽  
Julian Polte ◽  
Maurice Meyer ◽  
Deniz Simsek
Keyword(s):  
Data Analysis ◽  
Machine Tools ◽  
Critical Factor ◽  
Root Cause Analysis ◽  
Data Driven ◽  
Manufacturing Companies ◽  
Cause Analysis ◽  
Root Cause ◽  
Comprehensive Data ◽  
Causes Of Failure

Die Zuverlässigkeit von Werkzeugmaschinen ist ein kritischer Faktor für den Erfolg produzierender Unternehmen. Durch die Analyse von Daten in der Produktplanung können Maschinenhersteller Ausfallursachen eliminieren und Maschinen systematisch verbessern. Jedoch stellt eine umfassende Datenanalyse viele Unternehmen vor große Herausforderungen. Die in diesem Beitrag vorgestellte Methodik adressiert diese Problematik und unterstützt Unternehmen bei der zielgerichteten Datenanalyse.   The reliability of machine tools is a critical factor for the success of manufacturing companies. By analyzing data in product planning, machine manufacturers can eliminate causes of failure and systematically improve machines. However, comprehensive data analysis poses great challenges for many companies. The methodology presented in this paper addresses this problem and supports companies in the goal-driven data analysis.

scholarly journals Quality of Open Research Data: Values, Convergences and Governance

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 175 ◽  
Author(s):  
Tibor Koltay
Keyword(s):  
Big Data ◽  
Data Quality ◽  
Academic Research ◽  
Research Data ◽  
Data Governance ◽  
Quality Of Data ◽  
Open Research ◽  
Research Environments

This paper focuses on the characteristics of research data quality, and aims to cover the most important issues related to it, giving particular attention to its attributes and to data governance. The corporate word’s considerable interest in the quality of data is obvious in several thoughts and issues reported in business-related publications, even if there are apparent differences between values and approaches to data in corporate and in academic (research) environments. The paper also takes into consideration that addressing data quality would be unimaginable without considering big data.

scholarly journals SPATIAL DATA QUALITY AND A WORKFLOW TOOL

2015 ◽  
Vol XL-3/W3 ◽  
pp. 55-59 ◽  
Author(s):  
M. Meijer ◽  
L. A. E. Vullings ◽  
J. D. Bulens ◽  
F. I. Rip ◽  
M. Boss ◽  
...  
Keyword(s):  
Data Quality ◽  
Case Studies ◽  
Spatial Data ◽  
Selection Criterion ◽  
Data Driven ◽  
Product Characteristics ◽  
Spatial Data Quality ◽  
Quality Specifications ◽  
Product Specifications

Although by many perceived as important, spatial data quality has hardly ever been taken centre stage unless something went wrong due to bad quality. However, we think this is going to change soon. We are more and more relying on data driven processes and due to the increased availability of data, there is a choice in what data to use. How to make that choice? We think spatial data quality has potential as a selection criterion. <br><br> In this paper we focus on how a workflow tool can help the consumer as well as the producer to get a better understanding about which product characteristics are important. For this purpose, we have developed a framework in which we define different roles (consumer, producer and intermediary) and differentiate between product specifications and quality specifications. A number of requirements is stated that can be translated into quality elements. We used case studies to validate our framework. This framework is designed following the fitness for use principle. Also part of this framework is software that in some cases can help ascertain the quality of datasets.

Strategies to Address Low DPPM Failure Mechanisms on Automotive Grade Wi-Fi Radio Frequency Devices

2015 ◽  
Author(s):  
Kai Wang ◽  
Sadia Lone ◽  
Colin Thomas ◽  
Rhys Weaver
Keyword(s):  
Failure Analysis ◽  
Continuous Improvement ◽  
Failure Mechanisms ◽  
Time Frame ◽  
Cause Analysis ◽  
Automotive Market ◽  
Root Cause ◽  
Rigorous Testing ◽  
Additional Demand

Abstract System suppliers in the automotive market have an expectation that their IC suppliers provide products with low defective parts per million (DPPM) and have methodologies in place to drive towards 0ppm (Zero Parts Per Million). IC suppliers to the automotive market have supply chains and test methodologies in place to achieve such low DPPMs, but the systems suppliers will still require root cause analysis on every failure. The IC supplier is expected to demonstrate a containment, corrective action and continuous improvement in a very tight time frame. This additional demand of automotive customers poses a challenge to the quality of IC devices and the concept of cross departmental failure analysis. In this paper, we look at a complex Wi-Fi design with multiple IEEE specific radios, and how to address the few parts that escape the rigorous testing by IC supplier to improve the quality for the automotive IC.

Automated Bug Hunting With Data-Driven Symbolic Root Cause Analysis

2021 ◽  
Author(s):  
Carter Yagemann ◽  
Simon P. Chung ◽  
Brendan Saltaformaggio ◽  
Wenke Lee
Keyword(s):  
Root Cause Analysis ◽  
Data Driven ◽  
Cause Analysis ◽  
Root Cause

scholarly journals Root-Cause Analysis of Persistently High Maternal Mortality in a Rural District of Indonesia: Role of Clinical Care Quality and Health Services Organizational Factors

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad Afzal Mahmood ◽  
Ismi Mufidah ◽  
Steven Scroggs ◽  
Amna Rehana Siddiqui ◽  
Hafsa Raheel ◽  
...  
Keyword(s):  
Quality Of Care ◽  
Maternal Mortality ◽  
Clinical Care ◽  
Organizational Factors ◽  
Root Cause Analysis ◽  
Care Quality ◽  
Cause Analysis ◽  
Root Cause ◽  
Essential Services

Background. Despite significant reduction in maternal mortality, there are still many regions in the world that suffer from high mortality. District Kutai Kartanegara, Indonesia, is one such region where consistently high maternal mortality was observed despite high rate of delivery by skilled birth attendants. Method. Thirty maternal deaths were reviewed using verbal autopsy interviews, terminal event reporting, medical records’ review, and Death Audit Committee reports, using a comprehensive root-cause analysis framework including Risk Identification, Signal Services, Emergency Obstetrics Care Evaluation, Quality, and 3 Delays. Findings. The root causes were found in poor quality of care, which caused hospital to be unprepared to manage deteriorating patients. In hospital, poor implementation of standard operating procedures was rooted in inadequate skills, lack of forward planning, ineffective communication, and unavailability of essential services. In primary care, root causes included inadequate risk management, referrals to facilities where needed services are not available, and lack of coordination between primary healthcare and hospitals. Conclusion. There is an urgent need for a shift in focus to quality of care through knowledge, skills, and support for consistent application of protocols, making essential services available, effective risk assessment and management, and facilitating timely referrals to facilities that are adequately equipped.

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