• July 18, 2021
  • cplx
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Every business model is supported by its internal capabilities; capabilities that will be the result of the synergy that is achieved between the following pillars: processes, people or collaborators, the technology available, as well as the level of data use.

Where to start? … definitely not technology. Some will say for people, based on experience in transformation initiatives and above all on the well-known statement of Peter Druker: “Culture eats up company strategies like breakfast.” This is a valid approach when it comes to making changes at all levels, especially since in the beginning, there are no dependencies to develop capacities in people. However, when it is required to work on central aspects, it will be necessary for these capabilities to be closely related to the internal and external processes of the company, in addition to the appropriate use of strategic resources, including data.

In this sense, to improve operational efficiency in companies, it is equally relevant to address the development of capacities at the process level and the effective use of data from the beginning … but where do I start in this scenario? … My response as a consultant is: it depends, it depends on the fluidity, agility, flexibility and development maturity of the end-to-end value chain processes; as well as the level of depth and coverage of data that the company produces and needs, but above all, it will depend on the deficit of decision-making that the company has and the use made of the data to enable automated and intelligent processes.

Consequently, it should start where there is the greatest urgency or where the business priorities indicate it, but it is clear that both pillars are highly dependent. Therefore, from my perspective, starting with the processes has a higher priority; This statement coincides with the statement by Thomas Davenport & Jeanne Harris in their book ”Competing on Analytics”: “In times when companies in many industries offer similar products and use comparable technologies, high-performance business processes are among the latest points of differentiation remaining “.

This reflection is due to the fact that more and more, there is less difference in the offer of companies to their customers, in many cases they are commoditized or have become basic products. It is in this context that competitive advantages depend on the efficiency and effectiveness of how operations are executed. But this efficiency and effectiveness will only be achieved with the integration of predictive analytics in the flow of the point-to-point value chain, in addition to the application in decision-making based on data machine learning.

It is in this context where technology becomes a strategic asset for companies, since it is the most effective way available to achieve this synergy between processes and data. Enabling technologies, such as Cloud, Internet of Everything, Artificial Intelligence or Machine Learning specifically.

Specifically, these technology components will allow the following:

  • Cloud providers will make it possible to make services available on demand when required, allowing point-to-point value flows to have no limitations, allowing information to flow through the value chain in a fluid way. This will also be possible with private Cloud services, but this implies that companies ensure the availability of these services.
  • Internet of Everything is a component that is made up of different means of capturing unstructured data, be it smart sensors (Internet of Things), mobile devices, and even social networks. All this information was previously unthinkable to have, now it is a reality; It only remains to find their value, not individually, but by looking for correlation between them and with the structured information that companies already use.
  • Artificial Intelligence has become a strategic tool to achieve differentiation, especially to achieve the automation of processes in an intelligent way. Being Machine Learning, the main enabling technology for online or deferred predictive analytics.

In conclusion, changes must be addressed in an integrated manner, where the processes have a greater impact on the development of the other pillars necessary for the development of internal capacities, such as: people, technology and data.

Luis Mamani, MBA, Systems Engineer, PMP

Senior Consultant | Project, Program and Portfolio Manager | Customer Success

Coursera, Machine Learning Rock Star – the End-to-End Practice by SAS and Eric Siegel
Coursera, DevOps Culture and Mindset by University of California, Davis
Thomas Davenport & Jeanne Harris, Competing on Analytics