Communication of Mission, Vision, and Goals: The Key to Successful Change Management in Changing Times
Notice bibliographique
Résumé
The purpose of this study is to present new empirical evidence that communication of an organization’s mission, vision, and goals (MVG) is the strongest single predictor of successful change management during current environments of uncertainty. This study provides evidence from the 2022 to 2023 Canadian national Public Service Employees Survey (PSES) that successful communication of an organization’s mission, vision, and goals is the strongest statistically validated explanatory power of successful change among many commonly recommended change management actions with a direct benefit to addressing psychological safety and readiness for change. This paper applies a quantitative approach and analysis to selected scaled-answer data derived from the overall 2022 to 2023 Public Service Employee Survey of Canada (PSES, N = 189,584 employees within 90 federal government departments and agencies spread across Canada). The Statistical Product and Service Solutions (SPSS) software is used in applying linear regression analysis including confirmation of linearity, independence of errors, tests for collinearity, homoscedasticity, normality of residuals, correlations, and application of control variables. The research model explains that 87.1% of the variance in change management effectiveness is attributed to four factors. The most significant factor is effective communication of mission, vision, and goals ( r = .887, β = .507, p < .001, 53.43% unique contribution); followed by support for high service levels ( r = .834, β = .298, p < .008, 18.50% contribution); work contributes to goals ( r = . 466, β = .254, p < .007, 13.52% unique contribution), and having clear objectives ( r = .785, β = .182, p < .025, 6.86% unique contribution). The evidence also shows that while the strongest ratings of successful change are aligned with the above ratings of communicating a department’s mission, vision, and goals the reverse is true: Departments with below-average ratings for change management also show below-average ratings for communicating its mission, vision, values. The ability of organizations to adapt is critical in a time of rapid external and internal environmental change. This is especially true in national government departments where changing environments can impact such major factors as technology, healthcare, public safety, socio-economic conditions, the natural environment, and international relations. There is robust literature on many recommended processes and competencies linked to change management. However, this research presents new evidence from an analysis of a national government employee survey that the strongest predictive factor on well managed change is the effective communication of a workplace mission, vision, and goals. Inherent within this factor’s benefit is its impact on reducing the constituent parts of fear of change, namely a sense of powerlessness and the unknown. This paper’s findings present many direct social implications. For a start, the Canadian federal government directly touches the daily lives of over 40 million people be it through the provision of health care, employment, economic and immigration policies, public safety, international affairs, taxation, or pension programs. Federal governments are empowered and expected by society to offer safety, security, socio-economic advantages, trusted performance, fairness, and accountability. Similarly, private corporations and organizations are influenced by evolving regulatory and administrative frameworks, including Diversity, Equity, and Inclusion (DEI), Environmental, Social, and Governance (ESG) considerations as well as Corporate Social Responsibility (CSR) pressures. These demands, driven by employees, shareholders, society, and governments, emphasize the growing interconnection of organizational accountability and societal expectations. This paper proves new statistically grounded evidence that for organizational change to succeed, employees must first understand why and how an organization’s mission, vision, and goals play a critical role in change and specifically how the change will improve existing services, how work directly contributes to the goals, and is training commensurate with new needs. A failure to successfully achieve these results shows a concomitant lessening of change management success and may be an explanatory factor in high rates of change management failure as well as the presence of fear of change.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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