Why do we work? What does work mean to you?

Have you ever wondered why some people get so much satisfaction from their job while others never seem to be very engaged or motivated? Is it something that we have inside of us or are we influenced by external factors? If it’s within us, then how do we tap into this for our own benefit? Is there anything we can do as leaders to support this? If it is externally influenced then how do we as leaders or people managers use this knowledge to improve workplace engagement and the gains that arise from that to our organisations.

Liz Moody has for many years been interested in how to release the potential in people and the organisations they work in. She has variously tried to understand performance, effective team leadership and employee engagement. In looking at many of the ways organisations and managers seek to organise work, she has concluded that perhaps we are looking in the wrong places for answers to the wrong questions.

A book written 50 years ago by Studs Terkel about working people and how they think and feel about work prompted curiosity about how we derive meaning from work. In this briefing we explored where this meaning comes from and why it might be important. Liz also considered what it is that leaders do (and sometimes don’t) that has an impact on how people think and feel about work.

Watch the recording.

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The latest Business Network Breakfast Briefing saw Dr Anna John use examples from all over the world as she explored three approaches to managing political risks to foreign investments. The Lecturer in Strategic Management presented her research and took questions at the Milton Keynes campus on Tuesday 9 April.

Her presentation, ‘Managing non-market risk to foreign investments: do nothing or manage actively?’, explored these different approaches with examples from countries as varied as Mozambique to China, India to Russia – with the UK and its never-ending Brexit another good source – helping to bring the theory alive.

Non-market risk comprises social risks (for example, nationalist movements and environmental protests) and political risks (for example, political regime change and regulatory uncertainty). Arguably, social activity of organisations, groups and individuals is more visible so social risks are relatively easier to predict and manage. Managing political risks is more of a challenge as the lack of information about political actions and intentions of organisations and governments makes it more difficult to make sense of these risks.

I wanted to focus on how, if at all, political risk should be managed relating to foreign direct investments. What is better: to ‘do nothing’ or to manage actively?

Dr Anna John, Lecturer in Strategic Management, OUBS

Two views – traditional, and modern – exist on what companies should do. The traditional view says political risk has negative implications for the performance of foreign direct investments and is largely defined by actions of governments (for example, protectionist policies). It should be avoided, meaning any investments into highly risky areas should be avoided too.

The modern view, which emerged in the early 1990s, suggests that political risk does not always have negative implications for the performance of organisations; instead, it may be a source of opportunities. Organisations can manage political risk and use it to their benefit.

Anna explored these two views in suggesting three approaches to political risk management of foreign direct investments: institutions approach (reactive), resources and capabilities approach (proactive) and resource dependence approach (active).

The institutions approach suggests that organisations passively react to pressures of political and regulatory institutions and ‘do nothing’. They either passively comply with the existing legislation, or avoid investing into a new and unfamiliar area; for instance, some US-listed companies are expected to comply with the Foreign Corrupt Practices Act (1977) and may not invest in some African and Asian countries where corruption is high.

The resources and capabilities approach suggests that organisations can proactively manage political risk and turn it their advantage by using political resources and capabilities. For instance, companies may benefit from prior experience of working in politically risky contexts (political resource) and from the ability to use this experience to make sense of new politically risky contexts (political capability). Some companies from politically risky environments like Russia, China and South Africa invest actively in Africa, Asia and Latin America.

The third resource dependence approach is a midway option with its major assumption that organisations are not autonomous; instead, they are dependent on resources of others. Like the institutions approach, this focuses on the negative implications but, like the resources and capabilities approach, suggests that organisations can manage political risk by managing their resources dependence upon others.

Reducing resource dependence by gaining control over key strategic resources is a possible strategy. For example, some newcomers to the Mozambican oil and gas sector such as Qatar Petroleum gain access to its key onshore and offshore blocks by partnering with more experienced firms with established ties to key government officials to lead the bidding process. This reduces dependence upon the government officials in the petroleum sector of the country.”

Dr Anna John, Lecturer in Strategic Management, OUBS

The effectiveness of these approaches varies from one context to another:

• The institutions approach is more effective in places such as China and Russia where institutions are well defined and homogenous, and where the central authority is rather strong.
• The resources and capabilities approach may be more effective in volatile places such as Venezuela and Ukraine.
• The resource dependence approach may work better in the USA and India, and somewhere like Mozambique, which have divisions due to federal structure and ethnic differences.

These approaches are not mutually exclusive or in conflict with each other; they can complement and be used in combination with each other.

The Breakfast Briefings are a series of face-to-face events, as part of The Open University Business Network. These events aim to foster collaboration and create an opportunity to explore together the latest and best of business thinking. We understand business and want to help your business flourish by sharing our insights into leadership and management at this series of collaborative events. In between briefings, why not join in on LinkedIn.

Big data analytics seems entirely absent in research on Corporate Social Responsibility (CSR) and sustainability. Yet the potential of big data to advance environmental and social concerns is enormous.

Big data analytics is about analysing very large structured datasets (e.g. those drawn from financial records and stock exchanges) and unstructured datasets (e.g. those generated by emails, tweets and GPS signals) that often cannot be analysed using traditional statistical methods. It opens up entirely new possibilities for spotting previously unnoticed patterns and anomalies.

In our research published in the British Journal of Management last year, we found that big data capabilities of managers are linked to higher sustainability of their organization. We surveyed 175 top management representatives (chief executive officers and managing directors) in food import and export firms headquartered in the UK and New Zealand. Our results from structural equation modelling indicated that big data competencies of top managers help towards environmental practices. What we still do not know is what specific technical or relational big data competencies would be best to advance sustainable practices and how.

What is the potential of big data in sustainability?

There is exponential growth of big data volumes driven by technology advances and lower equipment costs. Let us take a few practical examples from the oil and gas sector that I am familiar with. For example, Chevron’s Tengiz oil field in Kazakhstan has about one million sensors. Combined with real-time weather data and other types of data, big data generated by such equipment can be used to provide near-real-time alerts and help prevent accidents. Similarly, big data from safety inspections, location devices and drone photography can be used to develop predictive analytics to improve safety. In the area of transportation, for example, Devon Energy in the United States apply big data analytics to monitor the speed and location of their vehicle fleet and the need to evacuate workers in areas where hydrogen sulphide is located.

Big data has also been used in human development. The UN established Global Pulse, a big data lab in New York with satellite offices in Kampala and Jakarta. For example, in Indonesia, Global Pulse applied mobile phone data to understand food price fluctuations, and in Uganda, population movements. Non-governmental organizations and initiatives – particularly in health services – are also using big data (e.g. Médecins sans Frontières, Global Viral Forecasting Initiative).

Indeed, the donation of data by companies (or ‘data philanthropy’) has become a CSR activity by itself. For example, IBM and other companies regularly host ‘Open Data’ events (‘jams’ and ‘hackathons’) in which governments, NGOs and companies are encouraged to release data that can be used for some social or environmental purposes.

In a few countries, there is also some regulatory pressure for big data adoption. In the United States, the Deepwater Horizon disaster influenced debates about better process indicators for improving health and safety in offshore oil drilling. For example, the U.S. Bureau of Safety and Environmental Enforcement (BSEE) requires offshore oil drillers to monitor critical safety equipment in real time and then archive the related data onshore – which generates huge volumes of data. More indirectly, government mandates for energy efficiency, climate change and other environmental restrictions have spurred some companies to use big data analytics towards environmental improvements.

So why is so little work done to apply big data?

There are open-source applications such as Apache Hadoop and IBM’s BigSheets that have made big data analytics more accessible to individuals and organizations around the world. So why is so little work being done to apply big data analytics for sustainability?

Part of the explanation may be that a lot of good work may remain unnoticed under the radar screen. Despite the attraction of the topic, the academic community and some popular media outlets do not seem to find this of interest, or perhaps the researchers and writers may feel out of their depth in writing about big data.

Another part of the explanation is that companies have largely focused on big data analytics to improve financial performance, for example, by mining customer data to help sell more products, applying big data analytics to effectively manage inventories or – in the example of the oil sector – using data from sensors to facilitate exploration and production operations.

CSR and sustainability seem to have been left behind. When I spoke with a number of CSR advisers in the oil and gas sector recently and tried to get their companies to support my research, I was told things like ‘I couldn’t sell this to my boss’. However, if you really want to tackle sustainability in new ways, you sometimes need to move outside of your comfort zone. This is what I have done.

Prof. J. George Frynas is Professor of Strategic Management at the Open University Business School. This blog is partly based on the article “Essential Micro-Foundations for Contemporary Business Operations: Top Management Tangible Competencies, Relationship-Based Business Networks and Environmental Sustainability”, British Journal of Management, 29(1), 43-62, 2018. Contact George.