The agile perspective: People make it happen

The agile perspective

Even though we talk about Industry 4.0, Work 4.0 and other 4.0s, our economic system is based on the shoulders and brains of giants from the 3.0 age. Frederick Taylor (*1856-1915), who set the foundations of today’s management sciences and business schools, is one of them and probably the one who determined the 3.0 age of mass production and efficient production like no other. He believed that the success of a business enterprise is related to how work is performed. Taylor’s line of argumentation follows a captivating logic: To yield maximum outcome, with as few as possible mistakes, industrial companies need to break down the work necessary to produce the outcome into specific steps or pieces. These pieces need to be standardized in terms of process steps, responsibility areas or coding conventions, and once standardized they need to be performed by the right experts for each step: Designers, accountants, assembly line workers or testing engineers. Recruiting the right people with the right skills or educating existing staff in required (new) skills has always been a key driver for success.

Many business managers and academics believe that this production model and subsequent division of work is still very relevant. Without any doubt, the tayloristic design of work has created an unbelievable boost in productivity. To be frank, there is nothing wrong with this approach as long as you can forecast well, you know your customer needs and those needs remain stable and reliable, your competitors landscape is furthermore very well known and remains the same. That’s important, because change would mean a reshuffling of the production process or acquaintance of different skills.

Case Study X-Games

We try to exemplify this in the below example. Therefore meet Chris who works at X-games and is responsible for the development of a computer game about football. The game is „produced“ (software development) in a tayloristic way by Chris who has set up a clear process chain of activities and hired respective experts for the job. They are organized in specialists teams each with a team leader. There is a planning team, a design team, a development team, a team for testing and there are commercial guys. The business plan is set up based on market research and some other indicators, which the commercial team is translating into target segments and different price points. The design team has developed the game features according to the target segment, in our case single males between 25 and 40 years.

Everything works just fine. The launch of their app went well and it is steadily picking up. More and more customers are joining, lots of feedback is collected about new feature expectations and improvement wishes.

Collaboration – In addition, waste affected the motivation of Chris’ team. Collaboration deteriorated as they found themselves in a downward spiral where silos lacked a sense of ownership and end-to-end responsibility to the game. When the situation got worse, errors were directed “to the other team” and communication drifted towards self-protection instead of output-oriented feedback - and the battle is quickly lost there.

Speed – whereas industrial companies with mass products can benefit from tayloristic operations, the marginal productivity gains are decreasing. Speed seems to be the game-changer in our times, because customer demands vary and adjust quickly, digital technologies allow new business models and competitors and non-competitors disrupt products and markets similarly as it happened in our X-games example. Therefore, labor division is no longer the answer - speed and the referring adaptability to change drive performance in the 21st century.

Which Lessons can we derive from Chris and the X-Games case study?

1. Face reality

We don’t live in the world of “known knowns” anymore. New technologies, new customer needs, new business models and new ways of working increase uncertainty since there are too many variables we cannot control nor forecast anymore. This is why we are steadily moving towards “unknown unknowns” with the need for flexibility which require novel practices and agility (see graphic below).

graphic: complex, complicated, simple, chaotic

2. Go agile

Secondly, acting in divisional silos with highly sophisticated labor division may cause a demise in productivity and thus in business results. So the quest for stability, best practices and clear (hierarchical)  structures may result in the opposite of what Taylor intended: you become slow and unproductive.

The concept of agility can help here.

With Agile we mean the capability of a system to respond quickly and effectively to present challenges and customer needs in order to create more value. Managing the right balance of stability and flexibility is key and requires a holistic change in six dimensions.

The team gets right to work: Changes are assessed by the planning team, then transferred into design - a first new release is reviewed by commercial and handed over to development. The team collects some more features for the next release and hands over to testing. The testing team gets some use cases from the commercial team and starts reviewing thereafter. Some iterations later (the test team use cases from commercial were not in line with development) they launch the new version to their customers.

But it is too late: there is a new competitor on the market and their game skyrocket immediately and kicked X-games app out of the customer ranking. While Chris’ team was overwhelmed with the amount of feedback and change requests they got, the competitor updated the game in a frequency that was so quickly, nobody could explain how they did it. While Chris’ team struggled to align in time with all relevant teams at X-games, the competitor added even more features. In addition, the world football association adjusted some rules such as a new offsite regulation which brought Chris’ project plan totally out of balance: The World Championship was only few weeks away - and guess who had the update ready just hours after the announcement? It wasn’t Chris’ team.

Time passed and after a long overdue fourth release the management team is called in for a meeting to discuss layoffs. Yes, layoffs. What had happened?

Complexity – like in Chris’ case, every new release means a container of new features and functionalities that are added to the original solution. Interfaces and cross-dependencies increase exponentially in the process of adapting these new changes. When silo teams work in a waterfall logic, complexity can be overwhelmingly difficult to handle and the need for multiple fields of expertise that are needed simultaneously can not be fulfilled.

Performance – new interfaces impact performance and furthermore, they impact quality. The increase of complexity makes it difficult to identify root causes for mistakes. Just like in the X-games case, when complexity got out of proportion, it was not easy to find the root cause nor to find a solution for that. Software updates following the container and release logic do have the increasing problem of downtimes after a new release, which is often related to the increase of complexity and impacts negatively on performance.

Waste – large releases require more  testing and re-testing due to the exponential number of new interfaces and dependencies. Bug fixing creates new bugs and error detection becomes complicated. While trying to gain speed at X-games, Chris’ teams were still working in separate competence teams, thus creating redundancies as an outcome. Waste reduces productivity and performance.



3. Stay ahead of the learning-curve

Uncertainty will be an inevitable parameter of the present and dealing with uncertainty will be a key skill of the future – it actually is a key skill today. It is therefore imperative to not be resting on his/her own expertise but to seek input from other specialists and fields which are “further away” from the own discipline. To exchange knowledge and learn from each other will be more important than ever – because complexity will only increase from here. Making sure to organize specific formats (Working Out Loud, Kitchen Talk, Barcamp or F**k up nights) that enable informal sharing can provide additional learning opportunities. Continuous learning and development to stay relevant takes a lot of practice – it requires one to be curious and to remain open and un-biased – but it will be worth it.

4. Re-learn collaboration from scratch

Collaboration in agile structures means working closely together in truly heterogeneous teams. In order to align all involved functions and to adapt quickly to the changing environment/customer/demands/policies, collaboration needs to be re-learned just like a coding language. Solving conflicts in a room full of various expertise and only few hierarchical guidelines,  autonomous decision-making and switching in between different roles and functions depending on the project can be quite challenging at first. A shared growth mindset and an open attitude towards accepting uncertainty and knowing that not all decisions will be perfect will be essential. And – last but not least – feedback will be the currency of success: Feedback from colleagues to better collaborate, feedback from the management to better deliver and most importantly feedback from customers to develop the best possible outcome.

In the end, people make it happen. It is therefore crucial to set the right parameters in order for the team to perform best. This includes organizational, cultural as well as structural aspects and above all a mindset that believes that winning is a team sport.


Let's start here!

What is your opinion on the tayloristic, agile or mixed approach? Comment on LinkedIn and share your experiences.

    Reza Moussavian

    Head of HR Digital & Innovation
    Deutsche Telekom AG


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