Driving innovation by Prioritise time-savings

Summery:

The time savings model for organizstions is a simplified concept that helps us understand how to optimise efficiency. By considering factors like complexity, resource allocation, and the learning curve, our aim is to reduce the time spent on any task. This approach allows us to identify opportunities for improvement and enhance overall productivity and development efficiency.

The establishment of time-savings

We prioritise time savings by avoiding a team-first approach as we scale knowledge work. Socioeconomic Kanban Systems help establish the right structures in business, product, or IT management, facilitating rapid development in innovative cycles. Our approach emphasizes people working for people.

In driving innovation, permeable hierarchies supporting a culture of trust and anticipating dynamics swiftly are crucial. Continuous learning, customer-centricity, and stable systems enhance adaptability. Embrace high-tech solutions and foster interdependent interactions to utilize time effectively. Increased interaction, both internally and externally, is pivotal for driving innovation. Our experience lies in combining economic thinking at all levels, customer-centricity, trust in hierarchies, and Socioeconomic Kanban Systems to enhance certain and stable adaptability.

The concept of time

The clue lies in embracing a novel perspective on time. By reframing our understanding and utilisation of time, we unlock new possibilities for efficiency. The concept of time as a distance metric is rooted in the idea that time can be treated as a measure of separation or interval between events. Using time as a distance metric involves considering the temporal separation between events or points in the Socioeconomic Kanban System. With this concept, we offer a valuable paradigm shift for understanding and quantifying processes, movements, and changes within various Socioeconomic Kanban Systems.

An example of a model for time savings

Let’s break down this equation:

$T s$ represents the total time spent on tasks before any optimization.
$T a$ represents the time spent after optimization, resulting in time savings. The time saved is calculated as the difference between the total time before optimization and the time after optimization, expressed as $Δ T = T s - T a$ .
$E$ is the efficiency factor, which indicates the impact of optimization on time savings.

Now, let’s look at the equation

T a = T s \times (1 - E)

: This equation indicates that the time spent after optimisation (

T a

) is a fraction of the total time spent before optimisation (

T s

). This fraction is determined by the efficiency factor (

E

). In simpler terms, it means that the time saved (

Δ T

) is equal to the total time before optimisation minus the fraction of time not saved due to inefficiencies (

T a

). The efficiency factor (

E

) can be influenced by various factors, such as the introduction of new technologies or improvements in processes. These factors can impact how much time is saved through optimisation.

Our goal is to maximize the effectiveness of flow systems by integrating Socioeconomic Kanban Systems that are both reconfigurable and changeable. We achieve this by scaling knowledge work to enable flexible responses to dynamic changes.