For real-time processes in customer contact to work properly, the location where data is located is increasingly important become a failure or success factor. Think of the unambiguous customer view, video calls, agent assist/next best action, real-time translation/transcription or other real-time applications. Part 2 in the Ziptone Tech Updates series on data gravity, the phenomenon that data and applications attract each other. 

tech update is a new section on Ziptone about emerging technology relevant to customer engagement. We briefly explain what it is, how it works, why it is relevant, what the pitfalls are and we ask the reader's opinion: Hot or Not?

1. What is it

Data gravity is both a concept and a metaphor. Data gravity refers to the mutual attraction between applications, services and data collections. Datasets attract (new) applications and services and also (new) datasets. Data gravity is a relatively new buzzword. It was introduced in 2010 by a VP of Engineering at the American concern General Electric (which produces aircraft engines, but also medical equipment).

2. How does it work

Companies with large-scale customer contact often have a range of applications in house – both for routing interactions through different channels and for planning and recording them. This leads to a rapidly growing mountain of data. The mountain of data is also growing in other places within organizations – such as operational data, transaction data and IoT/sensor data. Due to increasing digitization, the volume of digital transactions and interactions is growing and mergers and acquisitions are also leading to new data collections.

These datasets are increasingly being stored in the cloud. This makes them increasingly difficult to move. For example, because the dataformats are not always interchangeable between clouds and there are many links with all kinds of applications. But regulations in the field of data security also ensure that data is 'moved' between applications less and less. Nowadays, applications move to the data and not the other way around.

While data collections are growing, the number of possibilities to do something with that data is also steadily increasing. Think of the emergence of analytics software and machine learning applications, which in turn control other applications.

A good example of data gravity is the mountain of data about customer conversations, which can be used with the help of analytics software analysed, which then forms the basis for building and improving chatbot dialogues. The chatbot combines different types of data, but also generates new data itself in the form of customer conversations and data in the form of quality and customer satisfaction scores.

3. Why is it relevant

1. Companies are increasingly understanding that data is an essential part of business operations. Data is increasingly playing a role in marketing and sales and in real-time business. The location of data will increasingly play a determining role. In real-time processes such as video calls, real-time transactions, real-time agent assist or real-time next best action, real-time translation/transcription, real-time analytics or real-time AI applications the location where data is located will become a failure or success factor. With real-time processes, for example, you don't want any delays because data takes too long to reach an application (latency). It is also increasingly important for contact centers that data can be linked in real time with ACD, IVR and CRM data.

2. Data gravity can encourage vendor lock-in because data cannot be easily moved, partly because the process is too expensive or because the data formats form an obstacle to the roll-out of new applications. Because as said: datasets attract new applications. According to Gartner Research two-thirds of companies want one by 2024 multi cloud strategyhave realized to avoid this problem of vendor lock-in resulting from an exclusive choice of AWS, Google Cloud or Microsoft Azure. Experts also indicate that companies would be wise to think about their data architecture in relation to storage and access.

3. The time when applications were installed locally in the server room of your own office – and managed and maintained from there – is over. Almost all software providers are making the move to the public cloud. These cloud applications – small and large – all need access to data. On the one hand, structurally running heavy data analyzes in the cloud can become a costly affair; on the other hand, laws and regulations do not always allow, for example, customer/personal data to be stored in the cloud. The phenomenon of data gravity can therefore influence your options to make both cost-efficient and compliant use of data.

Add it all up and the conclusion for customer contact departments is that once a path to the cloud has been taken, it will be increasingly difficult to change as more applications, data and services end up in that cloud. Organizations considering moving their core systems from the contact center or customer service department (routing platform and CRM solution) to the cloud would therefore be wise to think about their data architecture in advance.

ICT service provider Interxion has developed a Data Gravity Index, a score (gigabytes per second) for the size of data gravity based on variables such as data creation, data aggregation and data traffic. This score differs per region and per sector.

4. Pay attention

Data gravity is in some ways big data 2.0, the hype that you don't hear much about now. Big data was mainly about the need for companies to be able to realize competitive advantage with your data collection (and as part of that to invest in storage and analysis competencies). Tech companies that come up with data gravity emphasize the importance of data platforms where all kinds of data are grouped together and can be easily accessed. This is relevant for customer contact, for example, to be able to quickly and easily arrive at a clear customer picture – made up of different data sets – or to be able to run real-time processes.

5. Data Gravity: Hot or Not?

What do you think of data gravity? Leave your comments in the comments (at the very bottom). 

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