A paradigm shift in how data is acquired, processed and consumed
In this connected world, it is not just people and devices that are connected but also the markets, assets, infrastructure, fleet, products and customers are connected by some means. Every click and tick on the clock is creating digital footprint resulting in a large volume of useful information. However, not all of it is acquired/stored, processed or consumed to its potential.
Several organisations do admit that they generate large volume and variety of data, but don’t know its economic value or been able to consume it effectively. In many cases, they do not even store or track the data due to the perceived cost implications, lack of skills or appropriate infrastructure. Yet there are a few early adopters in sectors such as banking, insurance, retail, telecom, media (e.g. Netflix) and hospitality (Airbnb), who are able to predict their customer behaviour, manage product performance, predict revenue opportunities or loss, reducing cost and manage business risk effectively by leveraging the data they generate/acquire. However several other organizations who have either gone by the best of breed approach or who have invested across different tools, platforms, technologies due to whatever reason, are yet to see success.
Modern Enterprise Data Architecture (Modern EDA) is transforming the way data is treated within an organisation. It provides organisations an ability to acquire, process and consume data of all shapes and sizes in a unified manner, without having to worry about existing investments and future changes. What differentiates Modern EDA from the rest is that it does not even have to be built on a homogeneous platform or single vendor stack. It is fundamentally designed to support hybrid / heterogeneous architecture wherein each layer or component can come from different vendors or technology platforms. Thereby reducing your overall cost of ownership and increased returns on existing investment.
While a few organisations have started their journey towards implementing the Modern EDA to enhance their enterprise intelligence, many of them are still pondering on areas such as:
- Business applications are become more intelligent with embedded analytics functionalities, do they really need Modern EDA?
- What will happen to their existing investments in a fast evolving or dynamic business environment?
- Confusions over what shape and size of data currently exists or will be generated in future
- What are the building blocks of successful Modern EDA?
- Does the implementation of Modern EDA make existing investment / skills redundant?
- What will be the cost of overall ownership and how will they justify additional investment?
Companies that have adopted a structured approach towards implementing Modern EDW have drawn visible business outcomes. Modern EDW is less about technology platforms and more about business value enablement, which then follow through a detailed strategy and architecture including its components, approach and methodology. It addresses aspects such as data requirement (structured and unstructured), target architecture considering their current and future business and product strategy. At the same time, organisations must also look at larger business benefits that can be drawn from the deployment of Modern EDW and not just limit themselves to digital business platforms, Internet of Things (IoT), machine learning, data analytics, big data, robotics, cloud and cognitive etc.
Increasingly, companies across the globe are leveraging cloud based platforms to build Modern EDW, which enables them to move from capex to opex model. This also gives them the flexibility to control the usage without having to worry about technological changes. The illustration here explains the architecture of Modern EDW
An appropriate case study that explains how visible business benefits can be drawn using Modern EDA could be of a major telecom service provider where the company was facing issues related to increased customer complaints, reduced customer satisfaction, poor network performance, increased cost of services and potential risk of losing customers. With the help of Modern EDA the telco was able to acquire a large volume of data from different sources such as social media, customer call logs, products and service usage, device logs, customer complaints, infrastructure logs, maintenance notifications, capex projects, inventory levels and predict potential issues / customer behaviour along with Next Best Outcome (NBO) and Next Best Action (NBA) with increased confidence interval. This enabled the telco to prioritize their enterprise resources and initiatives to deliver a superior experience to their customers and hence increased revenue.
It is imperative that the companies take holistic view for transforming their enterprise data warehouse to modern data architecture by adopting a structured approach which involves following:
- Define business objectives, use cases linked with business outcomes/KPIs to make this initiative a meaningful and relevant exercise for example Revenue Growth, Cost Reduction, Risk Management, Customer Experience and Retention etc.
- Take a stock of functional and technical components currently being used. Also future investment in including investment in digital initiatives
- Conduct maturity assessment of existing information architecture and technical landscape
- Design target architecture aligned with the business objectives / outcomes and have buy in from key stakeholders and users
- Adopt agile methodology – start with having quick wins followed by global rollout / end to end initiatives
- Design an operationalization governance model – consider key aspects such as in-house, on cloud, as a service, managed services etc.
- Evaluate vendors with objectivity and the value add they bring to your organization
- Focus on user adoption and hence consider adequate investments in learning and development
- Treat data as your valuable enterprise asset and hence protect it