Digital Transformation: Value-Driven, Process-Led, and Data-Based

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Author(s)

Managing Director | Co-CEO, BPM-D
Dr. Kirchmer is an experienced practitioner and thought leader in the field of Business Process Management (BPM) and Digital Transformation. He co-founded BPM-D, a consulting company focusing on operational excellence, customer experience and process innovation by leveraging the discipline of BPM. Before he was Managing Director and Global Lead of BPM at Accenture, and CEO of the Americas and Japan of IDS Scheer, known for its ARIS Software. Dr. Kirchmer has led numerous transformation and process improvement initiatives in various industries at clients around the world. He has published 11 books and over 150 articles. At the University of Pennsylvania and at Widener University he has served as affiliated faculty for over 15 years. He received a research and teaching fellowship from the Japan Society for the Promotion of Science. E-Mail: mathias.kirchmer@bpm-d.com

What makes a digital transformation successful?

Most organizations have started, or have at least planned, their digital transformation journey [0] [1]. These organizations expect to increase their performance drastically by leveraging digital technologies. However, many of those businesses struggle to meet the high expectations through their digitalization initiatives, and don’t deliver the expected value.

A successful digital transformation is value-driven, process-led, and data-based. It targets business value and works towards a well-defined business case. This value of the transformation is delivered through new or enhanced business processes [2]. Digitalization only delivers its business benefits if you improve what you do or if it helps to do something new that provides additional value – without creating issues in other areas. Hence, processes guide the transformation initiatives towards value-realization. A process delivers, by definition, a result of value – which needs to be moved to the next level. To optimize the time-to-value, fast and well-informed decisions are required. This is achieved through a data-based approach, delivering the required information about current and future process performance at pace in the required quality.

Businesses often focus on getting the technologies to work: They are proud of a successful “Proof of Concept” (POC) – even if it delivers minimal to no value. Many companies don’t master their processes sufficiently enough to realize the full potential of digital technologies [3]. They tend to automate and improve single functions, but miss their transformation goals and don’t deliver sufficiently on the business case.

The right approach to digital transformation targets value systematically, uses the discipline of process management as a value-switch, and leverages process-related data effectively. The transformation approach is digitalized itself, leveraging appropriate process management tools, such as process modelling, simulation, and process mining as accelerators.

Digital Transformation targets value – and doesn’t boil the ocean

Companies only compete through 15-20% of their processes [4]. Those processes are their high impact processes and the other 80%+ are commodity processes that are necessary, however, their performance can be at an industry average. This is a different situation for high impact processes. For those processes, more elaborate optimization and innovation approaches are justified and often required. Related projects have a higher priority. High impact processes that have a lower maturity level, compared to other organizations, are the best improvement targets. Digitalization initiatives that move those processes to the next performance level deliver the most value for an organization [5]. Therefore, it is essential to identify the high impact/low maturity processes and prioritize transformation initiatives in those areas.

High impact processes can be identified systematically through an assessment of the impact of each process on the business strategy, represented through appropriate value-drivers. The maturity of these high impact processes can be pragmatically determined through appropriate stakeholder surveys. Results can be summarized in a process impact assessment matrix that creates the foundation to target best value during a digital transformation. It helps to focus on what matters most and avoids boiling the ocean. The digital transformation becomes more manageable while delivering the most relevant outcomes. Prioritization and project portfolio management tools support this exercise [6]. Figure 1 shows an example for such an assessment matrix.

Figure 1: Process Impact Assessment Matrix – Example

The end-to-end process context guides the transformation towards its goals

Once the processes, or sub-processes, to be improved are identified, an analysis for those processes is required. This detects improvement opportunities related to the defined value drivers and serves as input for the identification of the required digital technologies, the definition of the future digital process and the development of the detailed business case. The as-is process descriptions also support people change management. To accelerate this analysis, process modelling and mining tools have become an increasingly important accelerator [6][7]. They simplify rapid remote discovery sessions, the collaboration around those processes and the systematic collection of quantitative performance information.

To avoid fixing one issue while creating new ones in other sub-processes, an integrated end-to-end process view is required. The positioning of processes in the context of the overall operating model helps to identify other process areas and the touch points to those. It enables the identification of the overall benefits at the end of the business process. The operating model of the company helps to work in an end-to-end context while keeping the scope manageable. An example for such an operating model is shown in figure 2.

The to-be design of the processes in scope reflects the capabilities of digital technologies as well as their alignment with people involved in the process. It describes how the identified improvement opportunities can be met, leveraging the right digital technologies the appropriate way. It allows the finalization of the business case.

Technology-based process reference models reflecting the business impact of digital technologies can be used as a starting point and powerful accelerator [8]. Since many of the digital technologies, like automation platforms, can be used flexibly, it is important to make their business impact transparent. This also simplifies an enterprise-wide rollout of transformed process. The content of process reference models for digital transformation is illustrated in figure 3. The reference to the end-to-end process and the links to other subprocesses is maintained through the operating model context. The use of a process repository tool accelerates the collaborative development and roll out of to-be processes as well as the rapid development and application of the reference models.

The to-be process models are the basis for the technology implementation as well as people change management [8] [11]. They guide detailed selection and configuration of the digital tools. The same models help people understand how to work in the new business environment. In many cases the roles of people have to be entirely redefined, for example to handle exceptions and have robots deal with routine standard cases.

Figure 2: Operating Model – Example of a global Technology Company

 

Figure 3: Content of Process Reference Models for Digital Transformation

Fast well-informed decisions are key – during the transformation and beyond

The development and realization of a realistic business case requires quantitative information about the as-is and to-be processes, such as cost, time and scalability information or improved customer feedback ratings. Appropriate process management tools help deliver this information at pace to enable fast, well-informed decisions and the definition of resulting actions. A process modelling and repository tool allows simulations of the different processes. Information, such as cost and time attributes or probabilities, can be efficiently obtained during the interviews and working sessions. For automated processes, this information can be obtained through process mining. At an insurance company, for example, we could show that a to-be process for underwriting reduces over 80% of administrative work, almost half of the process cost and increases scalability by a factor 9.

A digital transformation journey never ends. To sustain transformation results and keep the related business processes on track, a process governance approach is required. This defines how the performance of a process, and the success of a digital transformation is measured and managed after improvement projects have concluded [4][7]: It ensures the value-realization. Process-owners, for example, have to initiate new transformation initiatives or corrective actions when appropriate. Process stewards provide the arms and legs for the owners to enable the execution of activities. Process sponsors and governance bodies set the direction and resolve conflicts, e.g., with functional leads of the organization or between business and IT team members.

The work of process owners and the entire governance organization is supported through the process models representing the to-be design as well as process intelligence tools, especially process mining. The to-be models provide the top-down guidance. Process mining delivers the necessary conformance and performance information bottom-up. Hence, the process owners know if the actual processes follow the design and reach the performance goals. The governance of digital processes can be supported effectively through mining approaches since those processes have a high degree of automation, delivering the required system lock data. Process governance goes through a digital transformation itself [9]. Figure 4 shows a simple digital tool architecture to enable fast well-informed decisions to support the rapid realization of the targeted value.

Figure 4: Simple digital tool architecture to enable fast well-informed decisions 

Business process management is established as the overarching management discipline [10][11] for the transformation and the following process governance. Thus BPM-Discipline becomes the value-switch for the digital transformation journey; value-driven, process-led, and data-based.

References

[0] Scheer, A.-W.: Unternehmung 4.0 – Vom disruptiven Geschaeftsmodell zur Automatisierung der Geschaeftsprozesse. Saarbruecken 2018.

[1] Kirchmer, M., Franz, P., Lotterer, A., Antonucci, Y., Laengle, S.: The Value-Switch for Digitalisation Initiatives: Business Process Management. BPM-D Whitepaper, Philadelphia – London, 2016.

[2] Kirchmer, M.: Value-driven Digital Transformation: Performance through Process. In: IM+io, Best & Next Practices aus Digitalisierung | Management | Wissenschaft, Heft 2, Juni 2019.

[3] Cantara, M:. Start up your Business Process Competency Center. In: Documentation of The Gartner Business Process Management Summit, National Harbor, 2015.

[4] Franz, P., Kirchmer, M.: Value-Driven Business Process Management: The Value-Switch for Lasting Competitive Advantage. 1st ed., McGraw-Hill, New York 2012.

[5] Kirchmer M., Franz, P.: Targeting Value in a Digital World. BPM-D Publications, Philadelphia, London, 2014.

[6] Kirchmer, M., Franz, P., Gusain, R.: From Strategy to Process Improvement Portfolios and Value Realization:
A Digital Approach to the Discipline of Business Process Management
. In: Proceedings of the Eighth International Symposium on Business Modelling and Software Design, Vienna, 02-04 July 2018.

[7] Kirchmer, M.: High Performance through Business Process Management –Strategy Execution in a Digital World. Springer, 3rd edition, New York, Berlin, e.a. 2017.

[8] Kirchmer, M., Franz, P.: Process Reference Models: Accelerator for Digital Transformation. In: Shishkov B. (eds) Business Modeling and Software Design. BMSD 2020. Lecture Notes in Business Information Processing, vol 391 (ISBN: 978-3-030-52305-3). Springer, Cham.

[9] Kirchmer, M.: Digital Transformation of Business Process Governance. In: Shishkov B. (eds) Business Modeling and Software Design. BMSD 2021. Lecture Notes in Business Information Processing, vol 422 (ISBN: 978-3-030-79975-5). Springer, Cham.

[10] Kirchmer, M., Franz, P.: The Process of Process Management – Strategy Execution in a Digital World. BPM-D Publications, Philadelphia, London, July 2015.

[11] Antonucci, Y., Fortune, A., Kirchmer, M.: An examination of associations between business process management capabilities and the benefits of digitalization: all capabilities are not equal. In: Business Process Management Journal, Vol. ahead-of-print No. ahead-of-print, https://doi.org/10.1108/BPMJ-02-2020-0079, 2020.

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