There are a number of limiting factors that impact upon an organisations ability to ‘be a fast fish’
We have grouped these limiting factors into two categories:
- Market Challenges that affect ‘all’ organisations, and
- Internal Challenges that ‘may’ affect your organisation
This section focuses upon the three external challenges as shown below.
1.8.1 Customer-Centricity
In 1970, Milton Friedman published an essay in the New York Times where he argued that “a company has no social responsibility to the public or society; its only responsibility is to its shareholders.“
This essay had a snowball effect upon organisations who shifted their focus from Customers, towards the desires of shareholders i.e. to make a profit.
This is one example of ‘old world’ thinking, that Klaus Schwab was referring to earlier.
However, like everything, it was not universally adopted.
For example, in 1974, Peter Drucker famously wrote about being customer-centric in his book, simply titled ‘Management’.
Whilst some management guru’s maintained that the Customer was king, it wasn’t until the 21st century that this became the norm.
How to Manage the Challenge of being Customer-Centric?
In 2009, Simon Sinek started a movement to refocus organisation strategy upon the Customer with his famous Ted talk, Start with Why.
Whilst Simon was not introducing anything new into the world, he is credited with making the purpose of customer-centricity easy to understand with his Golden Circle concept.
In practice however, the Golden Circle is missing an inner circle, Who? (i.e. who is the Customer?). Without knowing Who, it is difficult to understand Why.
- Who – is the Customer?
- Segment if required
- Why – does the Customer need us?
- What are the Goals that the Customer expects us to achieve?
- How – will we achieve the Customer’s Goal?
- What value streams (aka processes) do we need, and how (activities, procedures) will we do it?
- What – is the final Product/Service that we will offer?
- Frame your solution with a unique selling proposition
1.8.2 VUCA
In decades past, transformative planning would have followed a traditional programme, or project lifecycle.
First, a desirable Vision or Goal would be established.
Second, an articulation of what the future will look like in a Target State design that might include Services, supporting Processes, Organisation models, Technology and Information flows (SPOTI).
Third, a reflection upon the Current State (SPOTI).
Fourth, a Gap Analysis between the Target and Current State.
Fifth, a Roadmap of Milestones to chop up the gap.
Sixth, a series of Projects (or workstreams) to fill the gaps between the Milestones.
This approach is still used today, when the Visible Planning Horizon is far into the future. For example, when building a bridge, a shopping mall, a cruise ship etc
In some (or maybe most) industries today the Visible Planning Horizon is much shorter. Sometimes as short as one year, or even measured in months.
This is due to a VUCA environment.
In this context, we are not able to perform traditional planning. Simply because we are not able to see far enough into the future, to design a Target State within a suitable degree of confidence.
Agile Planning enables us to still maintain some control through the use of a Vision, and a review of the Current State. However, instead of planning a nice linear series of projects, we must experiment by delivering value to the Customer quicky, and learning quickly whether we are on the right track.
Sometimes our experiments pay-off and take us closer to the Vision, and sometimes they fail.
These failures are normal, and since we are aiming to deliver value quickly (from days to a month), the amount of money we stand to lose it limited to the resource costs for this timeframe.
I.e. we may need to throw one months worth of work away, but what we have learned will help be more successful in future experiments.
How to Manage the Challenges of VUCA?
1.8.3 New Technology
IoT
IoT is an acronym for the Internet of Things. This refers to the trend for ‘all’ devices to be smart and network connected. This technology poses significant infrastructure and security challenges as the more devices we add to the network, the more we have to troubleshoot, and the lack of standardisation can result in devices being hacked, or remotely controlled.
Biometric Security
Biometric Security is the ability to identify, track and grant, or deny access based upon your biometric data. For example, your facial features, posture, tone of voice as well as fingerprint can all be used to validate:
- who you are
- where you are, and
- what you can and cannot do.
This technology poses challenges for the protection of your civil rights, and the potential for a new era of fraud.
Big Data / Data Science / Data Analytics
Big Data, sometimes referred to as Data Science and/or Data Analytics is the latest evolution of the challenges involved in managing and using data.
With IoT and Biometric Security generating an exponential increase in data, the effort to manage and use it all, is also increasing exponentially.
AI / Machine Learning
AI/Machine Learning, like Big Data/Data Science is a technology that has been evolving for decades. Whilst true Artificial Intelligence does not exist, Machine Learning is evolving rapidly as a way to simplify operations, automate customer interactions and discover new insights from all the data modern companies are collecting.
The challenge here is one of mathematics (for the ML algorithms), as well as the issue of garbage data in, garbage data out.
Blockchain
Blockchain Technologies, with are essentially distributed databases, include the famous examples such as the cryptocurrency Bitcoin, and the smart contracts platform Ethereum.
This technology includes challenges such as, data sovereignty, governance risk and compliance, as well as (so far) unproven use cases.
Digital Twins
Finally Digital Twins are an exciting example of new technology that you may currently wear on your wrist.
Within industrial environments the digital recreation of physical objects using sensors can enable engineers to run tests and simulations to determine the optimal performance and maintenance schedules.
For smart watches, we’re seeing the first wave of human-focused digital twins, that enables us to track our biometric data digitally. In the future we may have the technology to digitally re-create our entire body to also identify ways to achieve optimal performance and longevity.
Challenges with technology include the sensors being small enough to be inobtrusive, the reliability of sensor information, and how to manage and use the generated data.
How to Manage the Challenges with New Technologies?
As these technologies are either very new to the world, or evolving at such a rapid pace that there is always a ‘new version’, it is very difficult to obtain proven solutions.
Therefore the risk of using new technologies is much higher, than using older (and more proven) technologies.
To determine what/if any new technologies your organisation should utilise, start with your Customer (whether internal, or external).
Agree upon your Vision and Goal, then think about how you will achieve this through your Value Streams.
Once you understand how your Product, or Service must operate the reflection upon which technologies are a best-fit should be more apparent. And, you may even realise that new technologies are not required after all.
However, if they are you must remember that you are going to be a pioneer. No one is an expert in new technologies, therefore you must experiment towards success.
This means adopting a culture of failing fast, and failing forward (learning), faster than your competition.