Manual content is dead: long live centralised asset and work management!

Author: Inge Scheibel

Inge Scheibel und Armin Noack bei Ihrem Bartalk

It goes without saying that companies invest in collecting and analysing data – but manual work still reigns supreme when it comes to creating content. This contradiction comes at the cost of contacts, interaction and customer loyalty. As a result, standardising processes relating to planning, creation, delivery and efficiency measurement is the logical next step.

Data is the new oil, or so it goes. However, the gold rush is somewhat premature. Companies make investments in the expectation that they’ll be able to speak to customers on a personal level – but these investments need the right data so they can appeal to customers with exactly the right content. The scope offered by the granular approach needs to grow in step with the scope for providing content to underpin this granularity. To this end, companies have to set out new processes and identify whether they are investing in technologies that support the processes at hand. The first step in this endeavour could be a centralised digital asset management system (DAM) or a work management system.

What are the key problems?

Generally speaking, the various content-related processes are still not seen as forming a logical whole. Instead, the planning, creation and delivery of content pillars, and the measurement of their success, are handled in isolation, as they usually fall under separate departments’ remits. However, this process should be viewed holistically as a content supply chain.

Which processes play a crucial role?

When thinking about content optimisation, it is worth looking at the following processes within these pillars in more detail:


Content is usually planned manually in Excel spreadsheets or, in the best-case scenario, in Jira. This is even the case in environments handling large volumes of content. Companies with content creation as part of their business model, in particular, should have a think about automation and ways to manage their workflows.


Current discussions about ChatGPT and AI, along with new product launches, show that people no longer need to be involved in every single activity – but that doesn’t mean that collaboration with creatives is a thing of the past. Instead, companies that create large quantities of content, or want to do so in the future, should consider automating processes that are repetitive, such as steps within a set framework. Nowadays, machines can complete these kinds of tasks much more quickly than people can. For one-to-one communication scenarios, we also need other mechanisms that will adapt content under certain circumstances, e.g. showing the products that were last bought/searches that were last undertaken in an image. It is no longer possible for this to be accomplished manually.


This is the field in which automation is to be found most frequently. Companies that need to regularly share large quantities of content with partners or customers, for instance, can enhance their efficiency in this respect.

Success measurement

Do you know how long it took for your last campaign to be created and how efficient this process was? Do you know how much value the content added? Or what pieces of content had a particularly sizeable impact on conversions? Generally, the answer is “No”. And yet this information would be truly invaluable. It is absolutely possible to obtain this data – and, ultimately, it can even help enrich existing customer data by, say, categorising the content. A certain amount of planning is required in this regard, though.

How can you proceed step by step?

The best way to start is by taking stock of your own content supply chain. What does it look like, which stakeholders are involved, what challenges are there?

Which of the four content pillars has the largest financial impact? The focus can differ depending on the business model at hand: it could relate to boosting content velocity, making cost savings, or something else. This helps with creating an initial roadmap. To begin with, you should focus on a couple of points as it is not possible to overcome every challenge at the same time. Then, the analysis should be taken to a deeper level for the areas with the biggest pain points. This also entails the processes in these fields being documented. In the next step, you need to define what the ideal processes would look like. Finally, it is important to clarify whether these processes can be implemented with the capabilities available or whether your IT landscape needs to be expanded. Only once this has been achieved can a detailed roadmap be drawn up to serve as a foundation for the roll-out.

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