Shiny object syndrome: the organizational points to think about when looking at complex data projects

All this week Daniel Henriksen, technology and operations director, programmatic at OmnicomMediaGroup in Asia Pacific, is helping marketers diagnose whether they have shiny object syndrome, when it comes to data and analytics. The four aspects brands need to consider are reality, organization, people and process.

Organization

Many types or organizations exists, and they are becoming increasingly more complex since the digital revolution started somewhere in the mid 1900’s. Physical borders are deteriorating, and despite constant political uncertainties and unstable macroeconomics, the truth is, it’s never been easier to start, run and operate a business selling or distributing goods to consumers around the globe.

This is a beautiful thing, and is also the key driver of current- and future prosperity. However, despite the “simplicity” of creating a business, organizations are becoming much more diverse and complex. The days of packing your lunch, get on a 45min bus ride, getting into the factory at 7am, clocking in to mark attendance, and then clock out after a full day’s labor are coming to an end in a lot of economies. Employees are now working remotely, in different countries, in different time zones, in different teams across multiple projects, from diverse cultural backgrounds with different perspectives on the world. This is the state of many organizations today, especially within media, marketing and tech. Engineers can be in India, business development in New York, finance/HR in London, and HQ might be in Shanghai.

Why is this important to understand? Because it is critical to understand this complexity through change management processes, and as mentioned previously, to be aware of the reality of the organization. Within this area, there are also a few things worth to assess and evaluate before initiating complex data and analytics projects:

Climate & History of Change

Self-reflection is healthy, and using the past to inform the future can be very useful when starting new projects or implementing change in an organization.

Fundamentally changing processes and integrating advanced data and analytics into core business functions will possibly make many who are not Millennials or from Generation Z insecure, as this might be a new and unfamiliar area. We are creatures of habit, and we tend to be very comfortable with status quo. Therefore, assessing whether the organization have gone through extensive change management processes can be very valuable, as this will make it possible to discover the climate for initiating new projects. Was there a lot of resistance with previous change? Has the organization settled since the last extensive change? These are important questions to ask before proceeding.

Design

Workflows, procedures and structures makes up the design of the organization, and the orchestration of these aspects defines the success of the business, and its ability to adjust and adapt to change when developing plans to integrate modern technology or processes.

Organizations can be complex, and many inefficiencies or dysfunctions can exist within all functions. Existing inefficiencies or dysfunctions will obviously make it challenging to implement new change, and it might be more valuable to focus on those existing challenges for the overall health of the organization, rather than chasing “shiny” objects when it comes to technology and integration of data and analytics. If the current organizational design doesn’t support the integration of data and analytics, figure out what might be the main challenge, and prioritize resources towards that specific challenge.

Accountability

As the former US President Harry Truman said, “The Buck Stops Here”. If you look up the phrase on Wikipedia, it will give you the definition that it means making someone responsible for making decisions – and who will ultimately be accountable for the outcome. In any change management process or project, it is crucial that accountability and responsibility is assigned and acknowledged by all key stakeholders involved, making sure that they understand their role in making it a success for the entire organization. Too many projects fail due to lack of assigned accountability, and no one wants to hold the “hot potato” in the event of failure. Leaders can’t be passive, and they need to lead the organization towards success collectively with their respective teams and stakeholders.

Data and analytics projects in all shapes or forms are not a new thing to most organizations, but the advancement of computational power when it comes to integration of artificial intelligence and machine learning can be a new and unexplored area to many. Leaders might be hesitant to take accountability in such projects, as it can be sensitive in terms of the fear of automation eliminating manual processes, and as a result, jobs and need for human labor. The age of data and technology is an exciting time, and data and analytics will empower business to connect with consumers in a much better and efficient way. Therefore, organizations need to identify leaders who will be accountable for taking them through this change, and make everyone understand that it’s an opportunity for them to progress and perform as individuals as well. In case you fear that your current job will be made redundant by data, analytics and automation, Harvard Business Review published an interesting article on what “being smart” will mean in the age of artificial Intelligence.

Daniel Henriksen is technology and operations director, programmatic at OmnicomMediaGroup.

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