Literary technologies for Leadership

This article explains how leaders can use literary technologies, such as summarizing, persuading and storytelling, to lead through writing.

A quick google search on leadership behaviour reveals many products, services and advice tailored to leaders, on how to act and talk in order to inspire and influence. But what can leaders do when their communication is mediated by technology such as Skype, emails or Enterprise Social Networks?

New media technologies allow for modelling, in other words, we can use technology to emulate behaviours we would have in real life. One of them is authoring, described as “the act of generating content and putting it online for a broad audience”. (Richter and Wagner, 2014).  Computer-mediated communication allows leaders to reach more people, thus broadening their influence and turn the traditional one-way communication, in engaging and online conversations. It is also important to note that employees prefer authentic texts authored by their leaders, as opposed to texts that were edited or written by someone else in the name of the leader (Richter and Wagner, 2014).

There are multiple literary techniques that leaders can use to assemble a text. As Jack Hart, former writing coach at the Oregonian says, a fundamental question to ask in the process of writing, is: “Just what sort of narrative are we talking about here, and what tools will I need to build it?” (Hart, 2012). Depending on the purpose of the communication/text, leaders can use different types of literary techniques to ensemble unique and authentic texts, to inform, motivate or engage:

Persuading techniques – can be used for motivating, persuading and motivating people, for example when assembling a text about disclosing a new direction for the company, a major change – when it is important to bring the employees on board with the message:

• Consultancy discourse – employing a future state (desired or feared) to gain/justify/convince that what we do in the present is exactly what we should be doing. Example: “Because of the new economy, every organization risks irrelevance unless it can keep its technology, people and business processes synchronized with a moving target strategy” (Bloomfield & Vurdubakis, 1994).
• Dynamic words will create a sense of urgency, such as rapidly, dynamic, accelerating, explosive, boom, movement, action, progress. 
• Glossy expressions and clichés can be used to put some aspects in the light and other concepts (for which no glossiness will be used) in the shadow. Example: “first-of-its-kind”, “state-of-the-art”, “breakthrough”, “one-of-a-kind”.
• Multiplicity – bringing in multiple views (research, influencers, journals) can convince your reader of the validity of your sayings. “Research shows that a success factor for digital leadership is transparency. We must therefor be transparent in our work”
• Including the reader: “as our level of acquaintance with the reader rises, so our ability to write something highly personalized – and persuasive – increases” (Camp, 2007).
• Being personal – Camp (2007) thinks it is more persuasive to be personal: this can be achieved by using pronouns in the 1^st person (I, my, mine), sharing your emotions, feelings, views, or opinions.

Summarizing techniques – these techniques can be used when assembling short updates about the company, projects, and/or changes within the organization, meeting minutes and other texts where brevity is important.

• Titled paragraphs: giving titles to paragraphs signals the importance of its contents (Bloomfield & Vurdubakis, 1994).
• Bullet points – “important points are often described as bullet points – presumably emphasising the notion of going straight to the heart of the matter” (Bloomfield & Vurdubakis, 1994).
• Re-read and remove words: A sentence should not contain unnecessary words and a paragraph should not contain unnecessary sentences. Interrogate every word in a sentence for its meaning and utility to your reader.
• Replace vague words with powerful, specific words. For example, replace adjectives with numbers: “Our company has a lot of experience in….” with “Our company has 50 years’ experience in…”.
• Combine sentences: Re-read and pay attention to whether some sentences are unnecessary and the information they convey can be incorporated in another sentence.

Storytelling techniques – can be used for engaging, amusing, and/or conveying difficult concepts and ideas – when it is important that employees remember. “Storytelling has such wide application because, at its root, it serves universal human needs. Story makes sense out of a confusing universe by showing us how one action leads to another” (Hart, 2011).

• Storyline: Explosion, Rising Action, Crisis, Resolution, Denouncement (also known as storyline) are the building blocks of any story.
• Metaphors and figures of speech appeal to the reader’s imagination and are an essential part of Storytelling. Examples: “Our company is like an oak tree – No matter the storm, it will keep standing “.
• Anecdotes are short stories that can be used to capture your audience, or to draw a parallel to a more difficult concept.
• Hyperboles are exaggerated claims that can be used to emphasise arguments. Example: “Our CEO read a million papers about innovation and concluded that…”.
• Juxta positioning of time: using past, present and future alternatively – Example: “Our journey started in 2010, today we are challenged by many technologies, and by 2020 we want to be the best in our industry.”

The realm of literary techniques that can be used for leadership communication is vast. They are even more important when it comes to digital communication for leadership. In I4L we are working on methods and tools to apply them in practice.

Bibliography

1. Bloomfield, B., & Vurdubakis, T., (1994). Re-presenting Technology: IT Consultancy Reports as Textual Reality Constructions. Sociology 28(2): 455-477.
2. Camp, Lindsay (2007). Can I Change Your Mind? The Craft and Art of Persuasive Writing. AC Black, London.
3. Hart, Jack. (2012). Storycraft: The Complete Guide to Writing Narrative Nonfiction. University of Chicago Press, Chicago; London.
4. Richter, A., & Wagner, D. (2014). Leadership 2.0: Engaging and Supporting Leaders in the Transition Towards a Networked Organisation. Hawaii International Conference on System Sciences,7.

This article provides examples of senior managers advocating for analytics in their companies.

As Kotter (1996) points out, leadership is a fundamental factor for any change initiative, such as transforming an organization into a data-driven organization. 

The question of how can leaders transform and propel a data-driven culture can be answered in many ways. During my research on this topic, I found several indicative examples in specialized literature.

An example that sparked a lot of attention is Gary Loveman, CEO of Harrah. Gary often asks the questions: “Do we think it is true? Alternatively, do we know?”. (Davenport, 2006). The questions suggest that decisions at Harrah are not taken based on hypotheses or gut feeling, but rather at the interplay between what we think and what we know, based on data.

Ruben Sigala, the Chief Analytics Officer at Caesars, a company operating under Harrah, presents the transformation undertaken by Harrah to becoming a data-driven company in an interview with MIT Sloan Management Review.

Ruben describes Gary, the CEO, as pivotal in transforming Harrah. With a background in economics, Gary has instilled an analytical culture across the enterprise by being consistent about the importance of leveraging analytics. His focus on analytics helped the company successfully identify itself with a data-driven company and transform itself into one. Although the transformational journey was challenging, some of the important elements that led to the success and fame of Harrah and the leadership of Gary, are:

• The centralization of the analytics functions – the centralization of functions was supported by an internal restructuration – from many stand-alone entities to one integrated enterprise;
• During the transformation, transparency and communication about the undergoing changes and the impact it had on the different stakeholders, as well as ensuring that everyone is on board was vital;
• Analytics units have been built for each area, such as revenue management, finance, marketing, labour, as well as an advanced analytics unit;
• New employees have been provided with specialized training, based on the unit they are joining;
• Many employees, although not specialized or working with analytics, have done rotation in analytical functions;
• Before starting new analytics projects, the company does small live experiments on how marketing affects customer behaviour. There are also larger scale experiments internally, focused on improving operations and processes;
• Although not detailed in media and literature, Ruben names partnerships focused on advancing analytical capabilities as a key element of their success;
• Tackling ambiguity in relation to data in an open way – expressing inconclusiveness and constraints of data when there is the case, but making sure to bring the analytics’ perspective on any question they need to answer.

Other examples of CEO’s advocating for analytics found in literature, are Barry Beracha, Patrick Byrne and Jeff Bezos.

CEO Barry Beracha from the Sara Lee Bakery Group had a sign on his table to summarize his organizational philosophy: “In God we trust. All others bring data.” In this way, he would reinforce the message visually to anyone visiting his office. Beracha was known by employees as a “data dog” because he would ask for data to support any hypothesis, exhibiting a behaviour aligned to his philosophy. (Davenport, 2006).

Patrick Byrne, CEO of Overstock.com described his company as being an analytics company (Watson, 2014). Although Overstock.com is an internet retailer company, the CEO attached the image of his company to that of an analytics company, where although they are selling goods, their success and profit comes from the extensive usage of data.   

Jeff Bezos, CEO of Amazon is very well known for saying: “We never throw away data.” (Davenport and Kim, 2013). This shows that Jeff is supporting and encouraging data collection practices. Although data collection might seem like a small activity, its success depends on the appropriate Big Data IT Infrastructure, data cleansing strategies, and collection processes.

McAfee and Brynjolfsson (2012) advise senior managers that wish to lead a Big Data business transformation to start with the following two techniques. The first technique is to make a habit out of asking what does the data say and question the reliability of the data, which will motivate employees to do the same. The second technique is to allow themselves to be overruled by the data, as it can be motivational for employees and for shifting the organizational culture to see that senior management trusts data more than their intuition. 

The questions asked by the CEOs named above and their behaviours might seem small, but their impact extends towards internal processes for collecting and analyzing data, as well as towards an analytical mind-set that is imposed as a way of taking decisions for their company and employees.

In I4L we are researching tools and methods for leaders to instill a data-driven mind-set as well as an understanding of the capabilities that support a data-driven company.

Bibliography

1. Davenport, T. (2006). Competing on analytics. Harvard Business Review
2. Davenport, T., and Kim, J., (2013) Keeping Up with the Quants: Your Guide to Understanding and Using Analytics. Harvard Business School Press, Boston.
3. Kotter, J.P. Leading Change. Harvard Business School Press, 1996.
4. McAfee, A., & Brynjolfsson, E. (2012). Big data – the management revolution. Harvard Business Review, 60-69.
5. Merchand, D. A., & Peppard, J. (2013, January – February). Why IT Fumbles Analytics. Harvard Business Review.
6. Sigala, R. (2013, July 30). A Process of Continuous Innovation: Centralizing Analytics at Caesars [Interview by R. Boucher Ferguson]. MIT Sloan Management Review. Retrieved June 2, 2017, from http://sloanreview.mit.edu/article/a-process-of-continuous-innovation-centralizing-analytics-at-caesars/
7. Watson, H. (2014). Tutorial: Big Data Analytics: Concepts, Technologies, and Applications. Communications of AIS, 34, 1247–1268.