modernized data-driven

5 tips to harvest the value of a modernized data-driven Supply Chain 

Alis Hinrichsen
Alis Sindbjerg
Hinrichsen
Thought Leader & Strategic Advisor

Covid-19, labor shortages, and disruptions, in general, have created global Supply Chain nightmares and revealed a need to modernize the Supply Chain with modern technologies and data-driven approaches, especially within the planning area. The utilization of AI and machine learning is helping to modernize the Supply Chain. More can though be done. A recent report is stating that only 8% (1) of the companies are able to mitigate Supply Chain disruptions due to their maturity.
The key question is: How does the leader succeed with technology and a data-driven approach when maturity is low?

Cultural change is critical

Companies and Supply Chains have been working to become more data-driven for many years. Some have done this with mixed results. Everyone understands by now that those that are able to utilize data to make more informed decisions will stand out in the competition compared to those who do not.
The biggest challenge for organizations working on their data-driven approach might not have to do with technology at all. Cultural change is the most critical business imperative. Becoming data-driven is about the ability of people and organizations to adapt to change.
Long-established companies, which have been successful over generations or centuries, are unlikely to change overnight. Becoming data-driven represents a business transformation that is playing out over the course of a generation.

Barriers to becoming data-driven

Achieving data-driven leadership remains an aspiration for most organizations — just 26.5% of organizations report having established a data-driven organization (1). Second, becoming data-driven requires an organizational focus on cultural change. According to the report, 91.9% of executives cite cultural obstacles as the greatest barrier to becoming data-driven.

1. Understand the stakeholders

It is not a technology issue. It is a people challenge. The task of being data-driven keeps getting harder. Today, companies encounter vast new volumes of data, as well as new sources of data. Data cuts across traditional organizational boundaries, often without clear ownership. The fluidity of data compounds the complexity of managing this asset in a way that consistently delivers business value.

2. Adopt a new mental mindset

Becoming a data-driven organization is a journey, which unfolds over time, measured in years, and sometimes decades. Becoming data-driven requires a different mindset. Organizations must be prepared to think differently. There is no shortage of analytic algorithms. These need to be matched by critical thinking, human judgment, as well as creative innovation.


3. Fail fast, learn faster

Leaders must understand that individuals and organizations learn through experience, which often entails trial and error. It has been said that failure is a foundation of innovation. Companies that are prepared for faster iterative learning — fail fast, learn faster — will gain insight and knowledge before their competitors.

4. Focus on the long-term

Data leaders appreciate that the data journey is a transformation effort that unfolds over time. Becoming data-driven is a process. The French writer Voltaire famously said, “Perfect is the enemy of good.” (2) Perfection is rarely achievable. Data-driven companies recognize that success is achieved iteratively. Successful organizations expect to be at this for a while. They focus on the long-term.

As many as 85% of companies want to have a digital Supply Chain in place within five years. But companies’ roadmaps often only have a three-year horizon. And all the disruptions of the past few years have only intensified the short-term focus (3).

5. Decide whether it is optimization or transformation

Many companies confuse digital optimization with digital transformation. As an example of digital optimization, you have retailers which implement technologies where you can shop without physically having to pay at checkout. Instead, smart technology registers what they take off the shelves and the amount is debited automatically. This is not a new business model, so it’s not a digital transformation.

Companies that enable consumers to use an app to order groceries for home delivery have introduced a new value proposition that can help them to attract new customers. This could even be linked to a new revenue model, such as a subscription. This is indeed a new business model, and it also has a major impact on the Supply Chain. The key question here is, what do you want to achieve – digital optimization or digital transformation?

New technologies can help to reduce costs because they allow for example planners to create a schedule faster. They can also be used to improve the quality of decisions or to plan things that were impossible to plan in the past. The key thing to do though is to determine where you currently stand in terms of maturity and which steps you need to take to improve it.

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