Digital alchemy: turning data into gold
What’s necessary to perform digital alchemy?
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In the rapidly advancing digital era, a common point of discussion for business leaders is the central importance and key value ofdata, yet few have found effective ways of monetizing such data. The truth is that digital natives and start-ups have built their entire business models around data. It is thus necessary for incumbents to address this issue quickly if they are to compete effectively with digital newcomers.
David Johnson is Director of Solutions Consulting EMEA atDomo.
Which data are we talking about?
Different companies must focus on how best they can categorize their data, as no size fits all. Take one telecommunications as an example, they understand the central importance of data in controlling complex network operations. Telemetry systems on the other hand are well advanced in applying preventive maintenance. IT organizations are using data to help monitor service levels and software testing.
Other companies recognize that data can provide vital insights intocustomerbehavior and is essential to drive decisions relating to new products andcustomer experiences. Data is also vital at a functional level, especially in sales,HRand finance. What is most key here is that there is a need to carefully segment each data type and apply appropriate processes and controls to each category, no matter your business function.
Taking an end-to-end view of data
Data follows a well-trodden path from ingestion, throughanalyticsand finally into the hands of the end user. Companies must establish a coherent set of processes and a supporting cloud-based platform to ensure smooth passage from one end to the other. There are various modules involved in this end-to-end process, including connections to a multiplicity of sources, mechanisms to clean up and transform incoming data, and tools to help visualize outputs.
One of the biggest challenges I see along this process is authenticating and standardizing data ingestion, given the multiplicity of online channels and devices that connect organizations to the outside world. There’s also the issue of fragmentation of data within organizations, especially due to the extensive use of spreadsheets as a means of accessing and manipulating data from legacy systems. Until workflows are fully automated, we can expect such practices to continue to undermine end-to-end data management.
Converting data into value
Data has become the life blood of emerging ecosystems in finance, healthcare, government and elsewhere. Our ability to share and exploit common data sources accelerates value creation, and this is happening in real time across numerous industries, for example:
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Democratization of data usage
Even today, many managers and their staff rely heavily on intuition rather than data to make vital decisions. Much of this is supported by localspreadsheetsthat reflect personal ways of operating. This is in sharp contrast to digital natives, who use data to drive all their commercial decisions.
Traditional organizations are embarking on major change programs to promote data-driven decision making. This can be accelerated with the evolution of visual data tools that improve the user interface and encourage staff engagement. Citizen development and the use of low-code and no-code tooling has helped bridge the gap between traditional and modern data-driven methods of management.
Governance is at the heart of effective data management
The big question for many organizations is ‘who owns our data?’. This can range from the COO and CIO to central data science teams and CMOs, however what is most important here is that data is a business asset and needs oversight from a single corporate function.
IT has a vital but non-exclusive part to play here. IT tools such as data platforms can enable businesses to standardize and integrate data sources as well as providing the essential tools for its manipulation and consumption. However, it must be the businesses who have ultimate responsibility for ownership, especially in a data centric world. Again, much can be learned from digital natives who have organized themselves around their data. In the financial sector, regulation and compliance becomes especially relevant in deciding who controls the data. For example, one of Germany’s multinational investment banks has a central team reporting to the COO, who are responsible for compliance. Organizations need to build data governance into their enterprise architectures and assign appropriate functional responsibilities for operational and commercial data.
To conclude, what actions are necessary to perform digital alchemy?
David Johnson is Director for Solutions Consulting EMEA at Domo.
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