Table of Contents
The Principles of a Fast Execution
The ever increasing speed in the digital era challenges the traditional modus operandi of IT organizations. Digital products and services must be developed in quick and iterative steps to match the speed of industries and ecosystems. This change in how we deliver value points out implications towards organizational structures, how we coordinate work, degrees of freedom, technological structures, such as the right degree of coupling and focused automation, and, last but not least, financial management structures.
In their 2020 article “Disrupting Traditional Approaches to Create a Resilient Innovation Funding Model” the analysts from Gartner focus on the tension between new ways of working and traditional financial management approaches.
How Do We Operate in Times of High Volatility?
Ensure a fully aligned and agreed-upon plan on how to respond to risk events. Increase oversight of strategy execution […]. ¹
A fully-aligned plan and its fast implementation requires a suitable foundation. A holistic perspective on the organization is necessary, and can be achieved by using a holistic management methodology as provided by BeeCore.
In the following text section, we will briefly outline what constitutes a methodology and then move directly to the principles of BeeCore:
The principles of a fast execution.
What Is a Methodology?
[…] a system of principles, practices, and procedures to a specific branch of knowledge.²
Our specific branch of knowledge is Holistic IT Management. In the remainder of this paper, we briefly introduce BeeCore as overall methodology and then describe the principles of a fast execution in detail.
Holistic IT Management Using BeeCore
BeeCore offers a holistic approach to management that enables you to keep an eye on all management-related factors, from cost-driven projects to the exploration of innovative business opportunities.
BeeCore is based on a modular structure. This enables users to extract specific topics from the overall structure, generate added value in a focused manner, and drive a robust and stepped change. BeeCore covers three levels: principles, practices and procedures.
The approach defines principles for a fast execution, practices for effective steering, and procedures for a holistic management. This paper focuses on the principles of a fast execution.
There will always be questions that cannot be answered formally. We all need to make the hopefully right decision on a regular basis. BeeCore describes four principles that provide a common way of thinking and acting to guide decision-making in ambiguously-defined scenarios.
Principle 1 – Clarity on All Levels: Transparency
All decision-relevant data is accessible to everyone, to enable a common view and language.
Principle 2 – Less Is More: Effective Data
Only data relevant to decision-making is stored, to prevent the proliferation of information and to ensure the reliability of the data
Here, less is more. At first, this focus on as little data as possible, as much data as necessary may seem to take a contrary position in times of Big Data. But Big Data is pursuing a fundamentally different goal. In the context of Big Data, we collect and bundle a large amount of data, then use a wide range of analyses to identify the data’s purpose. In our context, we already know the purpose of our data: holistic management. Accordingly, we can select the appropriate data in a focused and careful manner.
The question must therefore be, which data is relevant for decision-making? At what level of abstraction do I need to collect data before I can trigger targeted, effective decisions? Do I need to store data in the management context that provide me with information down to the last detail and down to the last cent? Do I really need 5 or 10 project traffic lights to communicate the project status, or is one traffic light sufficient here, which simply indicates whether there is a need for action or whether the project is proceeding as planned? Less is more.
With too much data, it is possible that you cannot see the forest for the trees, and therefore do not know which route to take through the forest. If you want to take this route together as a group, it is particularly important to implement the first principle, transparency, or each individual will only navigate from tree to tree. If I know the forest, and I know which trees are relevant for navigation, I can make appropriate decisions.
Principle 3 – Reduce the Noise: Data-Driven Decision-Making
Decisions are made on the basis of data to promote good decisions and make them comprehensible.
At this point, we remove the noise. Decisions are often made based on the intuition of the highest-paid person in the room. This is not necessarily a bad thing, because intuition is gained through learning and experience. There is often a reason why these people are highly paid. But especially from a certain company size on, this kind of decision making can also lead to the promotion of local rather than global optima.
A special challenge can arise when there are conflicting decision options. For example, the decision to migrate a system to the cloud could be pending. This migration leads directly to costs, so the contrary opinion is currently to not migrate to save on costs. However, on-premise operation entails a huge amount of operating and maintenance costs. Technological debts can rapidly accumulate if this is not done carefully. In the long run, on- premise operation is not only more expensive, but will also have a negative impact when the time-to-market of a new product or service depends on system maintenance.
The three principles we have established so far provide a basis for well-founded and comprehensible decisions. We can now use this foundation to further accelerate our decision-making by decentralizing the decision-making process.
Principle 4 – Accelerate Decision-Making: Decentralized Decision-Making
Decision-making powers are delegated to those who value them most to promote the speed, quality, and acceptance of decisions
We empower those who know. Decentralization is known to promote growth. Suppose we want to develop an innovative digital product or service. In this scenario, individual teams interface directly with the potential customer or user of this digital service. The teams know best how to proceed in their field. If I take a classic management approach here, for example in the form of long-term, planned work-breakdown structures, I not only run the risk of overburdening the management due to the complexity and frequency of changes, but also do not lead the teams to explore and develop independently.
By decentralizing decision-making to those who work directly at the customer and user interface, I avoid micromanagement, minimize coordination costs, and increase commitment — both of the teams and of our customers and users.
A striking example of this can be found in the article by Langlois³ , who writes about modularity in organizations. He argues plausibly why actions and decision-making powers ought to be in one entity. For example, he mentions the restaurant owner and the management of table salt. The restaurant owner leaves the salt on the tables for free disposal, because the consumers of this resource know best how they want to salt their dish. Furthermore, the costs incurred by coordination and charging would exceed the revenues — something financially questionable and having exceedingly low quality results.
BeeCore Continues: Practices and Procedures for Holistic IT Management
Combined, the four principles shown here enable the swift implementation of comprehensively coordinated plans across several levels. Each principle builds upon the last. Decisions are made transparently and comprehensibly for all. Decisionmaking powers are shifted to ensure that plans can be implemented quickly and reduce time-to-market.
Decentralization is a well-known tool for promoting growth. On the other hand, centralization is known to increase efficiency and move from growth to scaling. However, decentralization and scaling do not have to contradict each other.
¹ Gartner (2019): Winning in the Turns: A CIO Action Guide
² Peffers et al. (2007): A Design Science Research Methodology for Information Systems Research
³ Langlois (2002): Modularity in Technology and Organization