Hidden data tax affecting businesses

In a world of economic uncertainty, geopolitical tensions, ongoing supply chain challenges and heightened customer expectations, organisations are making moving operations to the cloud a strategic priority. In fact, recent data reveals that between 2019 and 2020, 55% of all Australian businesses reported use of paid cloud services, up from 42% in 2017–2018.

Organisations that are moving to the cloud need an agility that enables them to anticipate and address changes in real time, improve organisational productivity and drive operational efficiencies. As more and more businesses become reliant on storing and operating using data from the cloud, we cannot ignore that some organisations have already made significant investments into on-premise solutions and are now choosing to invest further in multi-cloud strategies to kick-start their journey to the cloud so as to minimise any potential data loss or downtime that could erode a competitive advantage.

This competitive advantage gained from moving to the cloud has lent itself to creating a buyer’s market in which businesses can choose to switch cloud providers depending on their business needs. While moving from one provider to another based on specialisation makes sense, it also reveals a key issue which is widely overlooked. An issue that we at SAP refer to it as the ‘data tax’.

Breaking down data tax

Data tax refers to the loss of contextual and relative information around a set of data when migrating from one cloud system to another. This can be explained by drawing a parallel against transferring photos from an old mobile phone to a new one.

When moving files and data from an old device to a new one, the onus to categorise the incoming files and data lies with the new device. This new device may utilise a newer or completely different set of variables to catalogue information. In this case, images being ported over to the new device may appear in different albums, or even as one mass album, regardless of how they were originally stored and categorised. The result could be images which were captured in January appear next to those captured in May because the context of these images failed to transfer.

How does the data tax affect a business?

While the photo analogy demonstrates how frustrating incorrectly catalogued data can be, the issue is significantly compounded when organisations are moving large volumes of business-critical information between cloud services — all of which utilise their own unique blend of variables to categorise data.

One could argue that a company faces no losses at all if its data is available and accessible as they could simply spend some time re-organising this information. And while this may be true in the short term, the mid- to long-term impact of decontextualised data can be summarised across four key aspects:

• Efficiency — Repeated investment into re-contextualising information takes away resources which could otherwise be used to drive growth.
• Decision making — Scrambled and de-contextualised data may obscure or incorrectly represent the current state of the business. Without this information, the organisation risks its ability to react to the needs of its customers swiftly and accurately, which can lead to a loss of competitive advantage.
• Problem solving — Learnings and insights which have been cultivated throughout the operating period of a company have a great amount of contextual information associated with them. This bank of experiential data provides information on solutions to recurring or periodic challenges. The loss of contextual information to this bank of data renders it ineffective, which limits agility in the face of unexpected challenges.
• Redundancy in effort — Before moving to a new cloud provider, an organisation can invest in reorganising its data to align with the cataloguing style of the new solution. However, in the fast-paced world of technology, it is likely that the company will move to a more optimised solution in the future that will require the data to be reorganised yet again.

Mitigating the data tax

While it may be some time before the data tax can be completely eradicated, there are methods through which it can be mitigated.

One way to do so is by selecting a solution which is built to reflect the underlying data across all cloud services and present it as a single source of truth. We refer to this as a ‘business data fabric’. A business data fabric intrinsically provides data federation and virtualisation capabilities, connecting and managing all its data in real time across different systems and applications, while maintaining business semantics.

As an example, the creation of a sales order initiates thousands of fields of data and dozens of tables to be created on the backend. A bill of materials with all the items needed to execute an order is created linking procurement, production, supply chain and finance to name a few — data that is all related to one sales order and all of which have a dynamic relationship with other data fields. Without clearly defined business semantics, when a sales order is created, thousands of data points sit stagnant waiting for manual interpretation — a process that incurs more time and costs.

A unified data fabric integrates data from various data sources and provides a companywide view of business operations to HR operations and customer satisfaction, which can help to uncover any issues within the business as early as possible.

As more and more organisations move their data into and within the cloud, data tax will need to be managed through a holistic cloud strategy.

Image credit: iStock.com/iambuff