The old adage goes, “What you put into things is what you get out of them.”. It turns out this is not just guidance for personal effort. In fact, it holds true for technology too. More data is being collected and stored than ever before so the quality of that data as the input must be the highest priority, and no business can claim functionality when data is bad.
The bad news is that bad data is a reality. A Harvard Business Review from 2017 found that “on average, 47% of newly-created data records have at least one critical (e.g., work-impacting) error.” But what is the reality of bad data?
In a best-case scenario, bad data out means a redo, which is still not necessarily a quick and easy fix. Opportunities, time, money, resources, and potentially customers are lost when the process must be repeated to correct the mistake. Clarifying bad information that was entered, troubleshooting the problems that result from delivering on the bad data, and responding to dissatisfied clients who did not get the outcome they were looking for is inefficient.
In a worst-case scenario, bad data out could mean an incorrect medical diagnosis, assets titled in the wrong name, money missing from a bank account, and the list goes on. Imagine any undesirable outcome and know that it could result from bad data. In addition to the harm done to the end user, it is hard for any company to come back from a data blunder. A company’s reputation is at risk if they become known for getting it wrong.
Do you recall NASA’s launch of the Mars Climate Orbiter in 1998? It was designed to study the Martian climate and atmosphere. Communication with the spacecraft was lost because the probe went off track and disintegrated in the atmosphere of Mars. The navigation error was due to a measurement mismatch; the software failed to convert data from English units to metric, a mistake in standardization that cost $193 million.
Another example of a bad data input was the design of the Citicorp Center in 1978. An architecture student who was writing her senior thesis on the 59-story Manhattan skyscraper, which was unique because of its raised base and diagonal bracing, uncovered a structural flaw: the potential wind loads for the building were incorrectly computed by the chief architect. Her calculation of the building’s stresses led to a welding repair process that secured the building and saved it from toppling.
We can agree that we need good data. There is no question that it has to be accurate, reliable, relevant, consistent, and complete. Even the most innovative technology will not revolutionize the world if it operates on bad data.
We can ensure the quality of data in a number of ways. It starts with improving data collection. How is it collected? Who is collecting it? What are the sources? The next step is improving data organization. Once you have it, what is the method for storing and managing it? Then, the data needs to be standardized. How can multiple sources be made consistent? What is the standard for “good”? After that, it is about data entry. If it is done by machine, are there broken paths? If it is done by humans, are there bad actors or is attention to detail lacking? Does training need to improve?
According to some projections, 74 zettabytes (that is 74 trillion gigabytes!) of data will be created in 2021! That quantity of data is huge, but the quality of data is hugely important. The good news is that those companies who are able to master good data will have a competitive edge and be poised for success in the future.
In today’s rapidly transforming environment, organizations are pressured to accelerate their investments in the creation and conversion of content, assets, and data to scale services and products across a multitude of digital channels. Despite the move towards digital, many organizations continue to operate using 20th century, analog processes and capabilities. So, while the final asset or experience might be digital, many companies have yet to become truly digitally enabled enterprises. To become a truly digital, companies must embrace three changes. First, companies must actualize digitalization; the adoption and integration of technologies, processes, data and analytics designed for digital work. Second, companies must take advantage of digitization opportunities by converting physical assets into digital assets. Third, companies must normalize around the development of content, assets, data, and information in a digital format.
Digitalization is the adoption and integration of the technologies, processes / workflows, and data / analytics required to optimize value from being digital.
Digitization is the process of converting a physical asset into a digital version so a computer can store, process and transmit its information.
Digital commonly describes content, data, information, or systems that are created, managed, or stored electronically on a computerized database.
Marketing organizations are notably prone to pursuing digital output using 20th century, analog processes. We see marketers face significant operating and performance challenges today due to manual and disconnected ways of working, common of physical world processes. Some examples of this include planning and budgeting across multiple spreadsheets, or intaking content requests via email communications or manually generating data insights across disparate systems. In particular, digital content is an area that creates the major challenge for marketers as the processes used for creation and management are decidedly physical world. As integral as content marketing is to the success of marketing today, many firms have yet to embrace digitalization of the content value chain.
Digitalization of Your Content Value Chain
Marketers tend to believe the development of digital content, by default, means they have a digitally enabled content value chain. Unfortunately, this is often not the case. At the highest level, the digitalization of your content value chain must occur across each of the six value chain stages.
The Content Value Chain
Frequently, the creation, distribution and management processes marketers use for digital content is eerily similar to processes used for physical content. So, while the final content is digitally formatted and stored, the process activities, inputs and outputs are not. Some key characteristics of the physical content processes include:
Content is developed from scratch for one-time use in a dedicated channel, with limited opportunities for customization or localization
Lengthy content development cycle times due to manual review and approval workflows and need for extensive agency involvement
Lack of coordination and clear pipeline visibility between marketers and agencies, resulting in the creation of duplicative content
Push distribution of content to users regardless of content’s relevancy and consumer’s need/ability to utilize which results from analog’s inability to provide timely, contextual data to guide content distribution
Limited accessibility or findability of content as it is stored in unrelated storage systems across different marketing groups and agencies
Physical-world content processes lack the frameworks and capabilities for organizations to automate, scale, measure, and govern required to be competitive in today’s digital marketplace. Marketing organizations that prioritize the digitalization of their content value chain are able to both improve the effectiveness of their digital content, while driving efficiencies in operating cost and time.
For successful digitalization of the content value chain, marketers must:
Leverage new digital asset management technology
Adopting a digital asset management (DAM) system is critical to access, manage, and store digital content. It centralizes and maintains digital assets in their complete and component parts, reducing the need to recreate net new and instances of duplication. A DAM system allows marketers to quickly access, find, and update digital assets by enriching assets with custom metadata and tags. Marketing organizations that prioritize the digitalization of their content value chain integrate the use of their digital asset management (DAM) technology across the organization, allowing for greater time and cost efficiencies through automation and self-service solutions.
Improve existing processes and workflows
Moving existing processes managed across manual documents (e.g. Excel spreadsheets and PowerPoints) into digital workflow management tools enables efficient, streamlined processes and data transparency. A workflow management tool allows for the real-time visibility, orchestration, and automation of the entire content process across the value chain. Automated, digital workflows can achieve cross-functional alignment, faster cycle times and approvals, streamlined tracking, and reduced risk. A workflow management tool can be leveraged to centralize tasks, reviews, and automate alerts to allow for the transparent and seamless communication of content feedback and approval across stakeholder groups.
Effectively leverage digitized data to measure performance
Existing content processes and performance can be enhanced by integrating and leveraging digitized data in reporting tools. The process of digitizing your content assets means that information and data associated with those assets will also be digitally stored. Building a digital foundation for managing digitized data enables the capabilities to automatically capture key information and insights to more effectively distribute and measure digital content. Establishing a solid digital data foundation starts with identifying the right KPIs and consolidating the right data to measure content effectiveness and operational performance. It also requires that data be ported into established reporting mechanisms to allow for marketers to integrate and generate data into comprehensive reports and insights.
Adopt new ways of operating and digital-first mindsets
As marketing organizations start establishing digital processes and capabilities across the content value chain, they must embrace the shift in how work is getting done, how technology is utilized, and how data is captured and reported. Marketing organizations must solidify digital foundational structures, adopt new ways of operating, and instill digital-first cultural mindsets. A digital-first cultural mindset: seeks opportunities for digitization; shifts from prioritizing the creation of net new to, encouraging the coordination, re-creation, transcreation, and repurposing of content; makes full use of power digitalization has brought to content value chain processes. These mind shifts, ultimately, improve utilization and cost value of content across the organization. Without a solid operating framework in place and a shift in mindset and behaviors, organizations will face challenges in full digitalization of content processes.
While taking these four key actions may seem considerable, the benefits realized are more than worth the effort. The chart below illustrates how digitalization across the content value chain can come to life and some of the benefits realized.
Hallmarks of Digitalization
-Centralized, automated calendaring capabilities to improve pipeline visibility and coordinate alignment on priorities
-Integrated operations -Increased flexibility and organizational alignment
-Digital assets with metadata tags which are easily searchable in a centralized repository for reuse -Digitally signed agency agreements ease onboarding and management across the content lifecycle
-Reduction in marketing spend -Increase in content reuse
-Centralized markup and annotation functionality to easily accommodate asset changes and versioning -Online coauthoring capabilities facilitate collaboration -Content translation is automated and localized for various regions -Content creation is automated through the use of templates and modularization
-Increased capacity / throughput -Reduction in errors -Reduction in direct labor costs -Faster response times
-Automated content distribution capabilities to scale campaigns to targeted audiences and testing strategies across multiple channels
-Reduction in waste (unused content)
-Digitized assets are archived and governed in a single, central digital asset repository making archiving, managing and governing assets easy -Automated content categorization to scale content management and recognition
-Centralized cross-channel data is updated real-time to provide accurate and reliable insights on content performance
-Increase effectiveness -Improved data transparency
Getting Started with Content Operations Digitalization
Producing digital assets / content does not mean your organization has fully embraced being digital.
Marketing, organizations need to strategize and plan for a future that adopts digitalization, if they wish to realize the full value of digital content. KPMG’s Marketing Consulting team can help you identify the opportunities for digitization and build the capabilities and technical solutions for true content digitalization. If you are interested in transforming your content operating model, KPMG is interested in partnering with you. Let’s start the conversation.