Value Stream Analysis
Value Stream Analysis
Changing markets, technologies, and customer needs increase process complexity. Hence, the transparency about processes and their inherent structures becomes fuzzier. The challenge rising from that is twofold: First, it is difficult to align processes with the activities that factually add to core value creation. Second, it is unclear where in the process the most effective reductions in complexity can be made.
The transparency that enables managers to shape the process landscape and make the company sustainable can be re-established by the value stream analysis. Regaining the transparency then allows uncovering speed bumps and inefficiencies in processes as well as laying the foundation for holistically restructuring the company on a quantitative basis.
In R&D organizations the V-Modell constitutes a suitable framework to map the value streams onto. Depending on the organization at hand, robust value streams are identified or defined. After that, depending on the framework conditions of the project, the value streams are detailed in different levels of granularity. The formulation in the form of work products is particularly suitable as the lowest level of abstraction, as these represent concrete results.
Based on the defined work products, standardized interviews on department level are conducted to quantify the actual effort invested in the creation of the work products.
The results from the interviews are presented in the form of various diagrams in a final dashboard. This dashboard provides the basis for the evaluation of the data and further steps. The anomalies in the data are worked out and analyzed together with experts. Based on the anomalies, fields of action are identified, and possible solutions are described. The evaluation is carried out at different value stream levels and thus allows subsequent optimization at micro and macro level.
The Value Stream Analysis represents the basis for further optimization steps. The starting point for the optimization are anomalies and hypothesis, which were identified within the data results of the interviews. The anomalies usually relate either to very labor-intensive work products or very low estimated work products.
Optimization requires an interdisciplinary team committed to breaking down the identified work products (high or low estimated) and deriving measures to increase efficiency. Value Stream Optimization uses standardized levers to identify practical measures for the respective work products. These measures are being described, evaluated by work-product responsibles and integrated comprehensively in the existing business processes.
The four main building blocks of the Value Stream Optimization are:
- Speeding up time-to-market by eliminating low-impact and time-consuming work products
- Reducing process complexity by eliminating bottle-necks, speed bumps and process-complexity peaks
- Increasing efficiency by optimizing ratio between in-house & external services and establishing new standards in core-value creation
- Improve product quality by re-investing effort in high-value work products
The impact of the value stream optimization is a significant increase of the R&D budget due to implemented efficiency measures.
A reduction of effort-driven costs up to 15 % is being achieved due to focusing on most valuable core results. Redesign of process operations leads to an increased efficiency of workflow up to 10 % due to reduced process complexity. Finally, the transparency throughout business units increases which allows a reduction of roles by 5 % due to amplified use of cross-functional synergies.