Climate Change Strategy Framework

The literature on climate change strategies converges on 4 main strategic intents namely governance, innovation, compensation, and legitimation. The figure below identifies a corporate climate change strategy framework. The different corporate activities are grouped into 4 strategic intent with a focus of interaction / self-containment levels in each of those activities[1].

Governance which is defined as an organization’s ability to deal with risks and opportunities deals with GHG (Green House Gas) management and associated policy development, organization involvement and risk management. All of these corporate activities are mostly internal to the company and if done properly can be effectively used to formulate and strategize the corporate vision around climate change. Innovation is geared towards the improvement of existing products and processes as well as embracing any new technologies that can accelerate and conform to the various standards related to climate change activities and impact reduction. Compensation is the action taken by an organization to reduce its carbon footprint like buying CO2 credits or enhancing carbon sinks. The organization’s own technological assets and competencies remain unaltered. Legitimation encompasses the activities aimed at retaining or gaining legitimacy around the various activities done by the organization.

There are multiple foci of interaction which can mainly be categorized into internal collaboration and external collaboration with actors outside the field of influence of the organization.

Corporate climate change strategy framework

If an organization fine-tunes its various activities taking climate change into consideration and keeping the 4 points listed above as strategic intent; they can very easily influence the strategic objectives and resulting portfolio strategy to comply and offer products that have a minimal carbon footprint. A more mature organization can also take an active role in the compensation and legitimation intent to steer the climate change debate to its advantage.

[1] – Damert, M., & Baumgartner, R. J. (2017). Intra-Sectoral Differences in Climate Change Strategies: Evidence from the Global Automotive Industry. Business Strategy and the Environment, 27(3), 265–281. https://doi.org/10.1002/bse.1968

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Climate Change Strategies

Climate change is for real and multiple scientific evidence that has been provided by scientists and climate change activists to ask for increased action by corporates and individuals alike to actively work towards reversing and/or stopping the phenomena. Corporates especially are increasingly challenged to incorporate visible and meaningful action on climate change in their day to day activities. Investors are also requesting for transparency on corporate greenhouse gases (GHG) emissions and looking forward to strategies to reduce them. This resulted in a shift towards market responses, i.e. proactive managerial and technological measures, such as the establishment of carbon inventories, investments in ‘green’ products and cleaner production processes[1][2].

The automotive industry is particularly targeted since the transport industry accounts for around 30% of global carbon dioxide emissions, out of which 72% comes from road transportation[3]. Cars are major polluter accounting for 60.7% of total CO2 emissions from road transport in Europe[3]. The new CO2 emissions target wants to cut harmful emissions from new automobiles by 30% by 2030, with an intermediate reduction target of 15% by 2025, as compared to 2019 emission levels [4][5]. The below infographic shows the emissions breakdown by transport mode.

Emissions breakdown by transport mode (2016) [3]

The automotive industry is trying to reduce CO2 emissions by introducing electric cars and stopping the production of ICE (Internal Combustion Engines)[6] as a first step. Adopting renewable energy sources is also the first step to develop a means for more sustainable transport. The second and more important step is to go towards autonomous vehicles and inter-vehicular communications using technologies such as 5G, V2X, V2V, etc. to allow for smoother traffic flow as well as avoid accidents, human error and provide for consistent driving behavior to reduce environmental impact. The third step is to reduce the price premium being applied to these new technologies in automobiles and bringing it to the mass-market. The third step is the most critical for automobile manufacturers who need to also maintain profitability as well as introduce and mature newer technologies such as an alternative power train and/or autonomous driving solutions.

New technologies for transmissions, driver assistance systems, alternative construction techniques and materials, new tyre technology and design, new vehicle design to reduce aerodynamic drag and optimal energy management within the vehicle are the key factors that drive the strategies to fight climate change in the automotive industry. PWC lists the following points to be taken into consideration in the strategic objectives & goals aligning with the climate change goals[7].

  1. Continue to improve on existing portfolio and focus on core competencies
  2. Do not ignore any new technology
  3. Develop a portfolio of technologies
  4. Assess technology acquisition strategies
  5. Evolve an effective innovation strategy
  6. Develop innovation networks and collaborative communities
  7. Manage the network risks
  8. Cooperate not only within the automotive sector but also with the fuel industry
  9. Pursue and agree on industry standards for new technologies
  10. Communicate the success and achievements

[1] – Weinhofer, G. and Hoffmann, V.H. (2008). Mitigating climate change – how do corporate strategies differ? Business Strategy and the Environment, 19(2), pp.77–89
[2] – Jeswani, H.K., Wehrmeyer, W. and Mulugetta, Y. (2007). How warm is the corporate response to climate change? Evidence from Pakistan and the UK. Business Strategy and the Environment, 17(1), pp.46–60
[3] – European Parliament, CO2 emissions from cars: facts and figures (infographics) (2019). CO2 emissions from cars: facts and figures (infographics) | News | European Parliament. [online] Europa.eu. Available at: https://www.europarl.europa.eu/news/en/headlines/society/20190313STO31218/co2-emissions-from-cars-facts-and-figures-infographics [Accessed 30 Oct. 2019]
[4] – European Parliament, Reducing car emissions: new CO2 targets for cars explained (2018). Reducing car emissions: new CO2 targets for cars explained | News | European Parliament. [online] Europa.eu. Available at: https://www.europarl.europa.eu/news/en/headlines/society/20180920STO14027/reducing-car-emissions-new-co2-targets-for-cars-explained [Accessed 30 Oct. 2019]
[5] – European Parliament, MEPs approve new CO2 emissions limits for trucks (2019). MEPs approve new CO2 emissions limits for trucks  | News | European Parliament. [online] Europa.eu. Available at: https://www.europarl.europa.eu/news/en/press-room/20190412IPR39009/meps-approve-new-co2-emissions-limits-for-trucks [Accessed 30 Oct. 2019]
[6] – http://www.climateaction.org/news/volvo-to-stop-making-new-diesel-cars
[7] – Pricewaterhouse Coopers (PWC) (2007). The automotive industry and climate change Framework and dynamics of the CO2 (r)evolution. [online] Available at: https://www.pwc.com/th/en/automotive/assets/co2.pdf [Accessed 30 Oct. 2019]

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Viable System Model (VSM)

VSM stands for the Viable System Model and it introduces the concept of a viable organization and its ability to survive in a changing environment. VSM consists of a number of systems that correspond to the needed roles in an organization for it to be viable and self-producing. There are four underlying principles for VSM according to Beer[1]. These four principles and relevant comments on my behalf are presented below.

Principle 1 (P1) – Managerial, operational and environmental varieties, diffusing an institutional system, tend to equate; they should be designed to do so with minimal damage to people and to cost

P1 talks about the states of a system and suggests that any changes to the states/variety in the system need to be done with minimal disturbance to the entire subsystem. We can take a simple example being a light switch that has 2 varieties/states (off and on). In general, a control system must have the same level of variety in order to monitor and govern a system. When it comes to machine learning, especially in unsupervised ML, the system states can sometimes be so varied that the controlling system cannot comprehend as to what goes on inside the system. eg: FAIR[2] turned off their chatbot creation since it invented its own language[3]. In the future, P1 might need to be changed to incorporate self-correcting mechanisms to allow complex systems to survive.

Principle 2 (P2) – The four directional channels carrying information between the management unit, operations, and the environment must each have a higher capacity to transmit a given amount of information relevant to variety selection in a given time than the originating subsystem has to generate in that time.

Of course, P2 deals with capacity and capability management. Again, I foresee that instead of increasing the capacity for the directional channels to receive & transmit information, the local units should be better prepared to take course correctional decisions by itself without generating extra system overhead. In terms of projects, for instance, the monitoring and control mechanism itself should allow only relevant details to be transferred to other concerned organizations. For example, a portfolio manager is not really interested in the velocity of a team involved with the project and such information even if transferred is useless increasing complications to the already strained communications between a project manager and a portfolio manager.

Principle 3 (P3) – Wherever the information on a channel capable of distinguishing a given variety crosses a boundary, it undergoes transduction; the variety of the transducer must be at least equivalent to the variety of the channel.

P3 very much is in agreement with my statements in the previous paragraphs. The information generated goes through transduction and/or transmutation to satisfy the variety of the channel. Again, most of the information needs to be transmogrify with relevance to the channel and not just superficially wrapped.

Principle 4 (P4) – The operations of the first 3 principles must be cyclically maintained through time without hiatus or lags.

Again, from my perspective, if the system itself has been given the autonomy for course corrections, only the relevant information needs to transmogrify resulting in an overload load reduction as well as the extra capacity generation for tasks that involve collaboration and coordination. From a VPP (Viable Project Portfolio) perspective, it really means intervention when required and asked for. Most of the time, the specific point in time reporting aggravates and shows symptoms but not a cure.

What do you guys think? Shouldn’t these 4 principles be updated/adapted to the ideas mentioned in this post?

[1] – Stafford Beer (2008). Diagnosing the system for organizations. St. Gallen Malik Management Zentrum C.
[2] – Facebook’s Artificial Intelligence Research lab
[3] – https://metro.co.uk/2017/07/31/facebook-robot-is-shut-down-after-it-invented-its-own-language-6818204/ , http://themindunleashed.com/2017/08/facebook-artificial-intelligence-shut-down-for-developing-its-own-coded-language.html

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Corporate Governance

(Vasudha Chhotray and Stoker, 2010) define corporate governance as, “Governance is about the rules of collective decision-making in settings where there is a plurality of actors or organizations and where no formal control system can dictate the terms of the relationship between these actors and organizations”[1]. The Australian Stock Exchange[2] publishes a list of principles for corporate governance which can also be applied to 3P (project, program, and portfolio) governance.

  1. Lay solid foundation for management and oversight
  2. Structure the board to add value
  3. Act ethically and responsibly
  4. Safeguard integrity in corporate reporting
  5. Make timely and balanced disclosure
  6. Respect the rights of security holders
  7. Recognize and manage risk
  8. Remunerate fairly and responsibly

These 8 principles published by ASX are extrapolated to be applied to 3P which will drive the processes, procedure and behavior within an organization[3].

  1. Ensure all project roles and their accountabilities are clearly defined
  2. Ensure all key stakeholders have a ‘voice at the table’
  3. Ensure decision making is informed, timely and effective
  4. All governance report should be concise, accurate and easily understood
  5. Act appropriately to ensure the project stays on track
  6. Optimize the outcome for the project
  7. Recognize and manage risk
  8. Encourage and oversee enhanced performance

The transposition of the principles from a 3P perspective is self-explanatory. But again, the implementation of these principles is dependent on the executive leadership and the procedural maturity of the organization. Leadership behavior has a definite impact on corporate culture. 3P governance does have a direct impact on the organization strategy and in turn on the product portfolio. As Cleland right says, “a project’s success or failure is the result of the leadership of the project’s stakeholders”[4].

What is your view?

[1] – Vasudha Chhotray and Stoker, G. (2010). Governance theory and practice : a cross-disciplinary approach. Basingstoke: Palgrave Macmillan.
[2] – https://www.asx.com.au/documents/asx-compliance/cgc-principles-and-recommendations-fourth-edn.pdf
[3] – Knapp, M. (2019). ENTERPRISE PORTFOLIO GOVERNANCE : how organisations optimise value from their project portfolios. S.L.: Springer Verlag, Singapor.
[4] – Cleland, D.I. (1995). Leadership and the project-management body of knowledge. International Journal of Project Management, 13(2), pp.83–88.

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Organization Project Maturity Model (OPMM)

Maturity has various meanings but from an organizational sense, it is the ability of the organization to act on its experience, to learn, change and improve, essentially what is known as the learning organization[1]. Maturity is seen as being the integration of attitude, knowledge, and action across the management of projects, programs and portfolios. A more mature organization does have a higher rate of project success.

“The central hypothesis behind the OPMM is that an organization’s ability to manage projects successfully can be assessed by analyzing key attributes that define how well project management is being carried out”[2]. OPMM is a 4-level model used to communicate maturity. The 4 stages of OPMM are:

  1. Stage 1: ‘ad-hoc’: In this stage, the projects simply happen. They do not have any endorsed business plans or assigned resources with no/incomplete milestones. No tracking of success or failure of the projects is done. These are typically small projects and the outcome depends on the skills of the individuals involved with the project.
  2. Stage 2: ‘aware’: This stage is achieved after an organization learns from the failed projects in stage 1. Formal project management methods are introduced in organizations at this stage. Project management is still not part of the organization culture and is not seen as one of its core competencies.
  3. Stage 3: ‘competent’: The organization at this stage has adopted project management as a core competency. The organization is aware of its capabilities and all projects are initiated only after proper business analysis has been done. The organization is quality conscious. Change and risk are always taken into consideration in such organizations.
  4. Stage 4: ‘best practice’: The organization at this stage is best in class and does project execution by the book. Organizations have well-developed portfolio management practices. Monitoring, measuring and improving processes are a part of the culture.

Nine maturity attributes namely methods, stakeholders, governance, capability, organization, business, support & tools, metrics and resourcing are used by OPMM to describe each stage. In essence, OPMM is a very simple and well-defined model for measuring the project process maturity within an organization and is less complex and straight forward when compared with other maturity models such as OPM3, P3M3 and CMMI.

[1] – Senge, P.M. (2006). The fifth discipline. London: Random House Business.
[2] – Knapp, M. (2019). ENTERPRISE PORTFOLIO GOVERNANCE : how organisations optimise value from their project portfolios. S.L.: Springer Verlag, Singapor. Page 98

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