Unraveling Complexity in Digital Business Models: A Microscopic Examination

Pretext

One thing should be made clear at the outset.

This is not about the highly celebrated reduction of complexity until there is nothing left afterwards.

The content of this blog is specifically alimented by my current experiences in two project missions in the German-speaking region of Europe. I observe with a certain amount of amazement that quite a few digital business models are not consistently executed in the digital processes, but rather show strikingly frequent breaks and then a certain process module is executed completely analog and then returns to the digital world as a realimentation. In process mining, such event logs are then particularly conspicuous and require a separate investigation and define a red flag.

The backgrounds for this are complex, but always find their origin in an overly complex business model in the analog world, which should then be transferred 1:1 to the digital world.

Breaks in digital business models with escape into the analog world are strikingly frequent.

Attempt of microscopic look into reality

The dark side of innovation may not be immediately reflected in financial performance indicators. So I recommend that you track difficulties your customers and employees face as a leading indicator of financial performance.

To gauge the level of complexity in your business, ask yourself the following first-aid basic questions. "Yes" answers signal brewing problems.

Employees

Do employees have to access several systems or use manual work-arounds to accomplish a task?

Do they have to contact multiple people to get their jobs done?

Do they have trouble identifying the appropriate in-house experts when needed?

Do they frequently have to stop tasks to wait for decisions or seek approval?

Customers

Do customers have to contact multiple people or call centers for each product and service?

Are different log-ins required to access different products and services online?

Do customers have to provide the same data multiple times during interactions or when switching channels?

Is the customer experience inconsistent from one part of the enterprise to another?

Are there breaks in the digital value chain so that a customer or internal employee or supplier suddenly has to go back to the purely analog world to send postal confirmations?

Does your organization justify the sudden flight into the analog world within a digital value creation process with the alleged data security?

Does exactly this event log of the analog world within the digital value creation lead to customer dissatisfaction, process slowdown and data loss?

Identifying indicators of a complex business process is crucial for businesses to streamline their operations and improve efficiency. Here are some additional indicators that suggest a business process may be too complex:

Lengthy and convoluted workflows

If a process requires numerous steps and involves multiple handoffs between different teams or departments, it could be a sign of complexity. Excessive steps can lead to confusion, delays, and potential errors.

Lack of standardization

When there are no clear guidelines or standardarized procedures in place (event logs), employees may have to navigate through different variations of the process, making it more challenging to execute consistently and efficiently.

High levels of manual intervention

Processes that heavily rely on manual tasks, such as data entry, data manipulation, or document handling, can introduce complexity and increase the likelihood of errors. Automation opportunities may exist to simplify and streamline such tasks.

Redundancy and duplication

If multiple steps within a process are redundant or serve the same purpose, it indicates inefficiency and complexity. Identifying and eliminating duplicated efforts can streamline the process and save time.

Excessive decision-making layers

Processes that require multiple levels of approvals or decision-making can create bottlenecks and slow down the overall progress. Simplifying the decision-making hierarchy and empowering employees with clear guidelines can help streamline the process.

Lack of clarity and communication

Complex processes often suffer from poor communication and unclear instructions. Ambiguity leads to confusion, errors, and delays. Clear and concise communication is essential to simplify and streamline processes.

High error rates and rework

If a process consistently results in errors, rework, or customer complaints, it may indicate complexity. Complex processes are more prone to mistakes, and identifying the root causes of errors can help simplify and improve the process.

Inefficient use of technology

If the technology used in a process is outdated, incompatible, or not effectively integrated, it can hinder efficiency and add unnecessary complexity. Assessing and optimizing the use of technology can simplify processes and enhance productivity.

Lack of employee engagement and satisfaction

When employees find it challenging to navigate through complex processes, it can lead to frustration, demotivation, and decreased productivity. Engaging employees in process improvement initiatives can help simplify processes and increase satisfaction.

Slow response to changes or market demands

If a process is inflexible and cannot adapt quickly to changing business needs or market demands, it may indicate complexity. Agile processes that can adjust and scale are more likely to be efficient and effective.

Deep dive digital business

Of course, the specific views on the evaluation of digital business models and the evaluation of complexity should not be missing. There is no definitive answer to this question, as different digital business models may have different levels of complexity depending on various factors, such as the market, the customer, the value proposition, the revenue model, and the technology. However, some possible indicators and characteristics to identify a too complex digital business model we are able to identify based on our experience in the dynamic Brazilian market and the recent experience accumulated in Europe.

The digital business model is not clear or concise enough to be communicated in a simple way. A useful tool for describing and designing digital business models is the Digital Canvas, which is a modified version of the widely used Business Model Canvas. The Digital Canvas consists of nine building blocks that capture the essential elements of a digital business model, such as the digital value proposition, the digital channels, the digital customer segments, the digital revenue streams, the key digital resources, the key digital activities, the key digital partners, the digital cost structure, and the digital risks. If the Digital Canvas is too crowded or vague, it may indicate that the digital business model is too complex or not well-defined. Together with Design Thinking, the Digital Canvas represents the most important entrepreneurial compass, with which scenarios can be created and business models can be tested very quickly as LoFi models with well-founded feedback in the real world. I am surprised to see that these really strong tools are not given the necessary space in many German companies. This means that strategic scenario generation and business model testing are not conclusive right from the start, and tactical planning, i.e., resource allocation (business plan in Excel), is started almost immediately.

Frequently observed, the digital business model does not have a clear competitive advantage or differentiation from other similar or substitute offerings in the market. A digital business model should be able to create and deliver value to customers in a way that is unique, innovative, and hard to imitate. If the digital business model relies on generic or easily replicable features or functions, it may not be able to sustain its profitability or market share in the long run.

Additionally, the digital business model does not have a clear alignment or fit between its components or with its external environment. A digital business model should be coherent and consistent in its logic and execution, meaning that all its elements should support and reinforce each other and match with the customer needs, preferences, and behaviors. If the digital business model has gaps, conflicts, or mismatches between its components or with its external environment, it may face challenges in delivering value to customers or capturing value for itself. What is particularly striking here are the frequent breaks in the digital business models and the partial continuation of processes in the analog world in order to become digital again at a later point in time. Information is almost always lost at these points. This leads remarkably often to problems in the customer relationship and problematic deliveries with regard to delivery time and the delivered products or services. What actually scares me about very many German managers is the explanation: data security.

Of course, the issue of data security is a top priority. Also, some technological backwardness in Germany, such as the communication network based on copper cables, is a limiting factor. On the other hand, regardless of the limiting factor, one should not simply accept this situation in Germany in particular without contradiction. Even when the liberal coalition partner in the current government reduced the federal budget for digitization to 1/100 a few months ago, this did not trigger an outcry in the business community or the public.

The digital business model does not have a clear measurement or evaluation system to track its performance and progress. A digital business model should be able to define and monitor key performance indicators (KPIs) that reflect its strategic objectives and goals. These KPIs should be relevant, specific, measurable, achievable, realistic, and time-bound. If the digital business model does not have a clear measurement or evaluation system, it may not be able to identify its strengths and weaknesses, optimize its operations and processes, or adapt to changing market conditions or customer feedback.

These are some of the possible indicators and characteristics to identify a too complex digital business model. However, they are not exhaustive or definitive, as different digital business models may have different criteria or standards for complexity. Therefore, it is important to always test and validate one’s assumptions and hypotheses about one’s digital business model with real customers and data.

Conclusion

By identifying these indicators of complexity, businesses can proactively assess and optimize their processes, ultimately improving productivity, reducing costs, and enhancing customer satisfaction.

iMB has been active in reorganization, transformation and on-demand management projects in project management for over 18 years.