Study the article below and on the basis of the requirements for the proposed study, and answer all the questions that follow.

Where can digital transformation take you? Insight from 1 700 leaders

By Linda A. Hill, Ann Le Cam, Sunand Menon, and Emily Tedards

31 January 2022

In mid-2020, we set out to understand the challenges of leading in the digital era. Teaming with the Harvard Business School Global Research Centres and Salesforce's Ignite team, we held 21 roundtable discussions with more than 175 executives from companies around the world, ranging from dominant incumbents to digital-first start-ups. We also surveyed over 1,500 senior executives from more than 90 countries.

Their conviction was resounding: 97 percent of respondents agree or strongly agreed that organisations will not remain competitive unless they radically adapt to the demands of the digital era. All but 3 percent indicated that their organisations were undergoing digital transformation.

How to do this successfully becomes the pressing question?one we will try to answer in this three-part series: first, to describe what it means to be a digitally mature company? second, to outline what it takes to create one? and finally, probing how leaders must change not just their organisations, but also themselves.

Everything is changing and technology is a key driver

When we asked executives to join our roundtable conversations about "digital leadership," they warned us that the term was too narrow: "leadership in the digital age" better describes the strategic questions they face. After all, they're wrestling with three major shifts in the global economy?changes born of technology that technology alone can no longer address:

New customer expectations. Customers want frictionless, end-to-end experiences with companies, said roundtable participants. Digital natives in particular expect customer-company interactions, even in business-to-business industries, to be as fast and intuitive as tapping out a text or playing a video game. Not only must a company offer high-quality products or services, but the way they deliver them to the customer matters much more today than in the past.

Customers demand more value and innovation than ever before, but they're not always willing to pay more for that product or service. In fact, thanks to social media, dissatisfied customers can amplify their opinions about a company's long support wait times or hold organisations accountable for their environmental practices. Moreover, the accelerating pace of technological development and global interconnectivity can erode a company's competitive edge faster than ever.

New employee expectations. Information has become democratized both inside and outside of companies. In the past, CEOs and other senior leaders were seen as the legitimate strategic decision-makers because they had more access to data and could decide if and when to share it. With much more information available to many more people, leaders' legitimacy must come from different sources, or they must share decision-making with employees?or both.

Workers increasingly resist one-way, top-down communication and commands? they expect to be heard and to help develop their organisations' plans and solutions collaboratively. They take the responsibility that comes with "co-creation" seriously, with younger generations of employees ready to be judged on their creativity as much as their expertise.

New societal expectations. Roundtable participants said that Millennials and members of Generation Z seek purpose and fulfilment from their work, and care deeply about their organisations' long-term impact. They demand that leaders serve stakeholders, not just shareholders, and proactively build a more equitable and sustainable world. Customers increasingly want the same and are especially concerned about issues that affect them personally, such as data privacy and security. Social responsibility in the broadest sense, roundtable participants said, has become a competitive "must," essential for attracting talent and building trust with customers.

Six qualities of digitally mature organisations

Rather than waste time resisting, digitally mature organisations embrace and adapt to these key shifts in the business landscape, participants said. Companies able to navigate this unforgiving dynamic tended to have the following characteristics:

1. An intimate and dynamic understanding of the customer

With more and better data available, companies can get to know their customers like never before. Rather than expecting customers to buy whatever a company sells, the most successful companies proactively anticipate and discover customers' problems and desires and innovate accordingly. Because of the transparency afforded by the Internet, where customers can browse reviews and prices with ease, digitally mature companies aim to provide a unique, often more customized, end-toend customer experience.

"Understand your customer" has long been a business mantra, but even roundtable participants from digital-first companies admitted that too often their organisations merely sell the products and services they have rather than develop new offerings based on evolving customer needs and desires. Interestingly, only 55 percent of survey respondents ranked customer focus as one of the most critical characteristics for success in the digital era.

Getting to know the customer has become a dynamic, ongoing process, and is fast becoming table stakes. For example, companies understand they need to get reacquainted with their customers after the COVID-19 pandemic and recalibrate their pain points and desires. One participant remarked, given the unpredictability of the pandemic and the economy, companies should "serve their customers, not sell to them," and build the connections needed to move to the next normal. Global strategies are also becoming more "glocal," with growing pressure to develop products and services for the needs and expectations of specific national markets.

2. Culture that's data-informed, not data-driven

Digitally mature organisations embrace data?lots of it!?and use it to make better, faster decisions. However, data informs, not determines, their decisions. Analytics are important, but judgment and critical thinking ultimately set the roadmap. All employees, not just the data scientists, use data to develop new insights and foresight instead of relying on past experience. Given the speed of change, hindsight might be irrelevant to the task at hand. Digitally mature companies have the right technical expertise (such as experienced data scientists or analysts), tools (dashboards and data visualisation applications), and platforms (computing infrastructure and operating systems) to integrate data across their organisations.

Simply making data available doesn't guarantee that teams will use it. Can employees access data easily? Is it integrated into employees' workflows and processes? Do employees?regardless of seniority, experience, or age?know how to interpret the data? While 61 percent of survey respondents ranked "data-informed decision-making" as one of the most critical success factors in the digital era, judgment?an analog skill?is still required. Digitally mature companies have employees up and down the hierarchy who can look at data critically, knowing that some analyses will be incomplete, imperfect, or even biased.

3. A challenger mind-set and willingness to disrupt

Digitally mature companies encourage employees to challenge the status quo?even if this means fundamentally rethinking the core business. Everyone in the organisation is responsible for listening to signals from customers, suppliers, and other stakeholders outside the company. They're empowered to question all aspects of the business and suggest new ways to create value for customers. People who thrive in these conditions are actively curious about everything happening around them? they're comfortable admitting what they don't know, and are willing to unlearn, relearn, and embrace the latest and best practices.

Curiosity and creativity are vital resources for a digitally mature company. Even with the automation of many functions, participants were adamant that human ingenuity continues to be critical. Leaders of these organisations tend to look for people who apply their creative sparks to the insights they gain from data, artificial intelligence, and feedback from colleagues. Learning and performance are twinned, not split as is often the case at companies that have yet to embrace agile approaches.

When hiring and promoting staff, these organisations look for candidates with a "growth mindset," who can adapt to changing conditions. One participant said their business assesses each employee's "AQ"?adaptability quotient?to gauge their capacity to be agile and grow even under stress.

4. Distributed decision-making and co-creation

Companies have been aspiring to bust silos for well over a decade, but growing demand for end-to-end customer experiences has made cross-functional work imperative. Roundtable participants agreed that digitally mature organisations are highly collaborative.

Leaders of digitally mature organisations see beyond functional silos and organisational levels to bring together individuals with varied skill sets to frame and solve problems.

These leaders view employees more as "collaborators" than "followers," in part because data and technology enable more employees to have input in decisions. For that reason, diversity, equity, and inclusion efforts that bring more perspectives and experiences inside companies have become critical to stimulating new thinking, some participants said.

Executives we talked to say leaders must carefully balance when to "weigh in" and "step back"? their ambition is to empower employees to own and act on their decisions. But these companies are also willing to go outside their organisations, sectors, and regions to harness talent who can deliver differentiated customer experiences.

Of course, the COVID-19 pandemic has forced leaders and organisations to reimagine collaboration, the participants said. We have all grown accustomed to the virtual meeting and collaboration tools that global companies are using to engage people from around the world at different organisational levels, but success requires more than technology:

- Explicit discussions about shared purpose, values, and norms can encourage ownership and collaboration.

- Regular meetings?not just ad hoc troubleshooting?help standardise processes.

- Rituals can forge a sense of community and belonging despite physical distance and cross-cultural differences.

- Orchestrated "social" encounters can foster mutual trust.

However, participants know first-hand the limits of virtual collaboration. When it comes to horizontal collaboration, there appears to be no substitute for face-to-face interaction for building trust and connection, even among digital-first companies and digital natives.

5. Continuous experimentation and learning

In a world where speed matters, digitally mature organisations act even when the appropriate move is ambiguous. They don't wait for perfect information before making decisions? they see their decisions as "working hypotheses" based on the best information available.

We've heard for years about the need for organisations to develop a workforce of calculated risk-takers, able to live by a "fail fast" and "learn fast" approach. Leaders still want this, and to get it they need to create an environment that makes room for uncertainty, experimentation, and well-intentioned failure. They themselves must be willing to have the courage, as one participant put it, to launch new products or programs, experiment with them, refine them, and even drop them.

Digitally mature organisations leverage design thinking, lean start-up, and agile methodologies to power innovation. They conduct rigorous, relevant experiments, and test, learn, and adapt in light of new developments?even dropping oncepromising projects when the data suggest they no longer work. With customer intimacy guiding their operating models and cultures, these experiments put customer needs first. In fact, we heard examples of companies co-creating new products and services with their customers, for instance, in innovation labs designed for that purpose.

6. Ethical decision-making and proactive governance As technological advances give rise to previously unimaginable use cases, digitally mature organisations recognise that they are accountable for the unintended consequences of their actions within and even outside their organisations. Participants acknowledged that ethical dilemmas will arise, but that leaders must go beyond "do no harm" and establish the processes, habits, and talent that serve as the company's compass and guardrails. Millennials and Generation Z in particular want to work at companies that stay true to espoused values.

Leaders of digitally mature organisations align their employees around a shared purpose that puts ethical decision-making on behalf of stakeholders at the centre. These companies earn the right to collect and use employees' and customers' data, for example, by being transparent about their intentions and relevant processes. When they use that data, they actively ensure they are abiding by the expectations they set when they gather it. Organisations want to get to the point where customers want to share their personal information because they trust they will benefit from its use. Building this trust needs to be a multi-pronged effort embraced by all in the company?not just policed by those in compliance roles.

Digital technology: Enabler or disruptor?

Companies around the world are trying to harness the potential of digital technologies and data to ensure their very survival. When we asked leaders what it takes to prepare organisations for this effort, they shifted quickly from talking about digital tools to talent and culture?a surprise to us. Many companies find the journey to digital maturity daunting, with its seemingly endless considerations and constantly shifting landscape. It is new ways of working and new relationships with customers and other stakeholders that separate digitally mature companies from those whose transformations are still underway or have stalled.

Source: https://hbswk.hbs.edu/item/leading-in-the-digital-era-where-can-digital-transformation-take-you

REQUIRED:

An organisational researcher has proposed a qualitative study with the aim of exploring the factors that sets digitally transformed South African companies apart. The researcher has decided to seek the insights of the top management teams of the top 40 JSE-listed companies using an interview guide built around the six qualities of digitally mature organisations suggested by Hill, Cam, Menon, and Tedards (2022) in the article above.

QUESTION 1

Please outline how you would go about conducting the proposed study with reference to the following:

1.1 Formulate a suitable title for the study proposed by the researcher. (3 marks)

1.2 Specify the aim and significance of the researcher's study. (4 marks)

1.3 Formulate THREE (3) research objectives and THREE (3) research questions for the study proposed by the researcher.

(6 marks)

1.4 Specify and briefly discuss an appropriate research design for the researcher's study, and rationalise the choice of this particular design. (4 marks)

1.5 Based on the design you have chosen above, discuss the research methodology you would follow with regard to:

1.5.1 Sampling Methodology:

1.5.1.1 Specify the target population for the study. (2 marks)

1.5.1.2 Propose a method of sampling for the study and discuss why the sampling is fit for the purpose of the study. (3 marks)

1.5.2Method of Data Collection: (4 marks)

What data collection instrument(s) and/or method(s) would you use to collect your data? Provide a rationale for, and justify the appropriateness of, the proposed data collection method(s).

1.5.3 Method of Data Analysis: (4 marks)

Briefly discuss what method(s) of data analysis would be used in your study (Please note: you are required to specify and explain, where necessary, the methods of analysis you would employ for each of your research questions in 1.3).

QUESTION 2 (10 Marks)

Data saturation straddles the methodological boundaries of sampling, data collection and data analysis in qualitative research. According to Morse (2015: 587), data saturation is "the most frequently touted guarantee of qualitative rigour offered by authors".

In light of the above observation, briefly discuss the concept of data saturation and explain how you would ensure that data saturation is achieved in the proposed study.

SECTION B [60 Marks]

Answer ANY THREE (3) questions in this section.

QUESTION 3

Study the information provided below and answer all questions that follow.

As an organisational researcher, you suspect that operations management competence may be a significant predictor of the performance of manufacturing firms. After an extensive review of the extant literature, you have noted that the interplay of operations management competence and organisational performance has received little attention by researchers.

In the field of operations and supply chain management, as in many other professional or research fields, it is still not clear what is the required set of contemporary competencies for a successful professional performance (Bauer, 2018? D'Orazio, Schiraldi & Vincenzi, 2019? Schallock, 2018? Wienbruch, 2018). At a fundamental level, competences are intended as professional human behaviour abstractions and can be described as human qualities which are connected with skills, knowledge, ability, talent, and employee engagement (Abele, 2015? Bedolla, 2017? Miranda, 2017? Gronau, 2017).

In this regard, you are embarking on a study with the aim of empirically examining the impact of operations management competence on the performance of manufacturing firms across the Southern African Development Community (SADC).

You have gathered data from 160 manufacturing firms across SADC. You measured the average OMC (out of 100 points) of the employees in the operations department of each firm. Furthermore, organisational performance was measured using the Balanced scorecard (out of 100 points). Table 3.1, below, is an excerpt of the data collected.

Table 3.1: Excerpt of data collected from 160 manufacturing firms across SADC

\fKolmogorov-Smirnova Shapiro-Wilk Statistic df Sig. Statistic df Sig. Organisational_performance .173 160 000 780 160 000 a. Lilliefors Significance Correction Figure 3.2: Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate 899a .809 807 3.399\fFigure 3.4: Regression Coefficientsa Unstandardized Standardized Coefficients Coefficients Std. Model B Error Beta Sig. 1 (Constant) 12.750 2.130 5.985 000 Operations_management_competence .810 031 .899 25.831 .000Manager Ref# Level of management Level of organisational commitment 0001 Middle 6 0002 Middle '1' 0003 Junior 5 0004 Senior 8 0005 Junior 4 0006 Middle 5 000? Junior 6 0008 Junior 4 0009 Junior 5 0056 Middle 8 Figure 5.1: Case Processing Summary Cases Valid Missing Total Management_level N Percent N Percent N Percent Organisational_commitment_level Junior_manager 30 100.0% 0 0.0% 10 100.0% Middle_manager 20 100.0% 0 0.0% 10 100.0% Top_manager 6 100.0% 0 0.0% 10 100.0%Figure 5.2: Descriptives Organisational_commitment_level 95% Confidence Interval for Mean Std. Std. Lower Upper N Mean Deviation Error Bound Bound Minimum Maximum Junior_manager 30 4.7333 1.04826 . 19138 4.3582 5.1084 Middle_manager 20 6.8500 1.03999 .23255 6.3942 7.3058 CO Top_manager 6 7.8333 75277 .30732 7.2310 8.4356 CO Total 56 5.8214 1.57373 .21030 5.4092 6.2336 CO CoFigure 5.3: ANOVA Organisational_commitment_level Sum of Squares df Mean Square F Sig. Between Groups 80.964 2 40.482 38.834 000 Within Groups 55.250 53 1.042 Total 136.214 55Figure 5.4: Multiple Comparisons Dependent Variable: Organisational_commitment_level Tukey HSD 95% Confidence Interval (1) ( J) Mean Management_level Management_level Difference (I-J) Std. Error Sig. Lower Bound Upper Bound Junior_manager Middle_manager 2.1167* 95685 000 -3.9921 -.2413 Top_manager -3.1000 1.19071 000 -5.4338 -.7662 Middle_manager Junior_manager 2.1167* 95685 000 .2413 3.9921 Top_manager -.9833* 1.52170 026 -3.9658 1.9992 Top_manager Junior_manager 3.1000 1.19071 000 .7662 5.4338 Middle_manager 9833 1.52170 026 -1.9992 3.9658APPENDIX 1: DECISION-MAKING TREE TYPE OF DATA Level of measurement Interval continuous Nominal/Categorical Research question Tests on arrays of frequencies E.g. Crosstabs Relationships Differences Chi-square Regression/Correlation Tests on means 1 mean 2 means More than 2 means u known A known 1 sample 2 samples 1 IV& 1DV More than 1IV, o known unknown repeated independent repeated IDV factorial measures measures measures design 1IV & 1 DV Independent samples Parametric 1-sample 1-sample Related samples 2-sample Repeated One-way Factorial tests z-test t-test -test difference f-test Measures ANOVA ANOVA scores ANOVA Non- Wilcoxon Man-Whitney Friedman Kruskal- parametric U test Wallis tests