Transcending the Functions – Why Should the CEO Care for Lifecycles?

Jul 23, 2021
Dr. Thomas Kamps

‍(The original version of this article was published on LinkedIn.)

In John Stark’s fiction Products2019 [1], the plot involves a CEO, Dr. Bender, who takes over a hypothetical mechanical engineering company- type German “Mittelstand” of about 5.000 employees with productions sites in Germany, France, and the USA. He wants to know what happens to the product from beginning to end and hires an English MBA student, Jane, the main protagonist of the story, to find out. Jane conducts more than one hundred interviews in the various plants with different managers in different corporate functions. She uses abstraction techniques to handle the sheer amount of information she gathers, reflecting the complexity of the organization. The picture of the product lifecycle becomes clearer and clearer after she delves deeper and deeper into the organization. Jane identifies processes, activities, quality gates, issues and documentation across sites and functions. As result of her analysis, she detects structural similarities of processes on the top level in different sites but greater variety on the lower level of the processes. A major outcome of her research is that Dr. Bender decides to install a Chief Product Officer (CPO), “[...] with a responsibility for a 5-year vision, strategy and plan for everything concerned with products [...]”, to whom all product managers from the various sites report.

In this hypothetical scenario, the CEO sees the product lifecycle, the core business process, as its essential source of value creation that needs to be maximized. He is trying to make processes more efficient, and to do so, he needs to establish transparency first. This is not a trivial task as there is a major stumbling block. The organization is segmented into different subsidiaries with different products, markets and cultures while being organized by means of a functional corporate structure. It is well known that functional corporate structures naturally lead to a delimitation of the functions. This is not bad in and out of itself. On the contrary, it is even necessary so that vertical, specialist structures can develop. A negative side effect, however, is that it helps create silos in terms of both decision-making and data that are not adequately available to other functions along the value chain. The consequence of the silo structures is that overarching processes become non-transparent and difficult to reconstruct as we can see in this nicely written fiction by John Stark which I would like to recommend reading at this point. This novel is now used as a teaching material by some universities in Canada and the United States (see [1]).

The Product Lifecycle from a Business Development Point of View

If you look at the product lifecycle from a business development/strategic marketing point of view, as Theodore Levitt did in his Harvard Business Report of 1965 “Exploit the Product Lifecycle” [2], it seems obvious how he transforms the product lifecycle into a management approach for competitive power. He says, “Nothing seems to take more time, cost more money, involve more pitfalls, cause more anguish, or break more careers than do sincere and well-conceived new product programs.”. The latter is, of course, what product planning must be concerned with. Therefore, he is convinced that a managed product lifecycle “[...] can be a great help in developing an orderly series of competitive moves, in expanding or stretching out the life of a product, in maintaining a clean product line, and in purposely phasing out dying and costly old products.”. He goes on and states that “[...] it is this idea of planning in advance of the actual launching of a new product to take specific actions later in its lifecycle — actions designed to sustain its growth and profitability — which appears to have great potential as an instrument of long-term product strategy.”.

The Synthesis between John Stark and Theodore Levitt

How do John Stark’s analysis of the product lifecycle and Theodore Levitt’s demand for a front loaded, planned process come together? I think what they share is the notion of the product lifecycle as a holistic, overarching process that, if it is well managed, can lead to significant value generation.  This is why Dr. Bender decides to establish a CPO role as a focal, holistic process owner in the organization. Because only in this way, the efforts spend on the local level can be levered to lead to a new quality of value which is a prerequisite for an increase of business excellence. To make sure that business value increases is the role of the CEO. This is also the reason why such roles as Chief Digital Officer (CDO) or Chief Technology Officer (CTO) and similar roles have emerged in recent years. It is based on the insight of CEOs that the siloed world must be transcended. Such decisions aim at resulting in a balance of horizontal lifecycle vs. vertical functional structure.

Figure: structural (horizontal) organization vs. process (vertical) organization adapted from Andy Helming's presentation in [3], Hochschule München

As functional structures already exist, emphasis must be put on the strengthening of the processes. Here, efficiency is a real challenge because the organizational silos simultaneously produce their very own data silos and consequently, data are not available for the roles down the value chain. This, in turn, coerces requirements on the support by IT technology. Those are, so far, mainly focused on authoring systems for different corporate functions and processes within these functions that need IT support.

Current IT Technology does not Support the Transcending of the Functions

Product Lifecycle Management (PLM) was originally defined to be a holistic approach but has unfortunately been limited to the processing of Product Data Management (PDM) tasks, essentially. IT vendors offer a zoo of tools for each functional activity, but holistic connectivity of the product lifecycle is still widely missing. Experiences with AI also show that these powerful techniques only help solve specifically localized problems. The conclusion is that technologies so far do not support this transcension process. Therefore, they are hindering this inevitable change. The major reason for this shortcoming is not, as some of the large IT vendors may claim, a uniform data landscape delivered by only one vendor, but a missing layer of abstraction in the IT landscape. This layer is one that connects the data of the authoring systems across the entire process. Knowledge Graphs are a native way to do this because mathematical graphs naturally represent structural information. In case of the product lifecycle, graphs may very well represent the journey that a product takes from the beginning to its end. At Conweaver, we see a Knowledge Graph as a representation for the Digital Twin (see This is a technical implementation of what Dr. Bender envisioned in Products2019. If Jane had had such a tool, her research would have been eased dramatically and her work would have found an adequate form of documentation from which up to date swim lane charts could be computed on-demand.

Similar Lifecycle Challenges in the Banking Industries

Besides the product lifecycle, there are also other types of lifecycles and Digital Twins, such as those representing the assets in case of the machinery in production sites, the software, or the data lifecycle for which the CDO is responsible. Lifecycles may vary in complexity depending on the industry. In the discrete manufacturing industries, typically the product lifecycle is complex - that is why PLM was invented here. In the financial industries, the customer lifecycle is complex. Larger financial institutions often maintain quite a few CRM systems which, in their case, might belong to different subsidiaries and countries with different rules and compliance regulations. For them, “know your customer” (kyc) is a challenge because data are disconnected, and this makes tasks such as fraud detection comparatively hard to solve. They have tried to employ AI techniques too, but it showed, as in many other examples in the manufacturing industry, that machine learning algorithms are only as good as their input. You cannot solve the kyc problem without establishing data connectivity across CRM systems. A common improvement, both for the challenges in the manufacturing and the financial world, would be to create synergies by combining structural intelligence in the form of graphs with analytical intelligence in the form of machine learning.


I am convinced that the increasing complexity larger organizations are facing should be encountered with a much stronger focus on increased efficiency of processes, that is, the ratio of resources vs. output needs to be maximized. This can be supported by IT through application of graph and AI techniques as a foundation of corporate digitalization strategies. The latter aim at improving the automation of processes by delivering the information needed to any role down the value chain of organizations. At the same time, they even allow new business models based on a managed data lifecycle. Both are good reasons for the CEO to care.


[1] Stark, John: "Products2019: A project to map and blueprint the flow and management of products across the product lifecycle", ISBN 979-8664168440

[2] Levitt, Theodore: Harvard Business Review, "Exploit the Product Lifecycle", November 1965,

[3] Helming, Andy: Funktionale vs Prozessorientierte Orgnisation,

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