data driven business transformation Archives

Data-driven business is booming. The dominant, driving force in business has arguably become a driving force in our daily lives for consumers and corporations alike.

We now live in an age in which data is a more valuable resource than oil, and five of the world’s most valuable companies – Alphabet/Google, Amazon, Apple, Facebook and Microsoft – all deal in data.

However, just acknowledging data’s value won’t do. For a business to truly benefit from its information, a change in perspective is also required. With an additional $65 million in net income available to Fortune 1000 companies that make use of just 10 percent more of their data, the stakes are too high to ignore.

Changing Perspective

Traditionally, data management only concerned data professionals. However, mass digital transformation, with data as the foundation, puts this traditional approach at odds with current market needs. Siloing data with data professionals undermines the opportunity to apply data to improve overall business performance.

The precedent is there. Some of the most disruptive businesses of the last decade have doubled down on the data-driven approach, reaping huge rewards for it.

Airbnb, Netflix and Uber have used data to transform everything, including how they make decisions, invent new products or services, and improve processes to add to both their top and bottom lines. And they have shaken their respective markets to their cores.

Even with very different offerings, all three of these businesses identify under the technology banner – that’s telling.

Common Goals

One key reason for the success of data-driven business, is the alignment of common C-suite goals with the outcomes of a data initiative.

Those goals being:

Identifying opportunities and risk
Strengthening marketing and sales
Improving operational and financial performance
Managing risk and compliance
Producing new products and services, or improve existing ones
Monetizing data
Satisfying customers

This list of C-suite goals is, in essence, identical to the business outcomes of a data-driven business strategy.

What Your Data Strategy Needs

In the early stages of data transformation, businesses tend to take an ad-hoc approach to data management. Although that might be viable in the beginning, a holistic data-driven strategy requires more than makeshift efforts, and repurposed Office tools .

Organizations that truly embrace data, becoming fundamentally data-driven businesses, will have to manage data from numerous and disparate sources (variety) in increasingly large quantities (volume) and at demandingly high speeds (velocity).

To manage these three Vs of data effectively, your business needs to take an “any-squared” (Any²) approach. That’s “any data” from “anywhere.”

By leveraging a data management platform with data modeling, enterprise architecture and business process modelling, you can ensure your organization is prepared to undergo a successful digital transformation.

Data modeling identifies what data you have (internal and external), enterprise architecture determines how best to use that data to drive value, and business process modeling provides understanding in how the data should be used to drive business strategy and objectives.

Therefore, the application of the above disciplines and associated tools goes a long way in achieving the common goals of C-suite executives.

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In light of data’s prominence in modern business, organizations need to ensure they have a strong data foundation in place.

The ascent of data’s value has been as steep as it is staggering. In 2016, it was suggested that more data would be created in 2017 than in the previous 5000 years of humanity.

But what’s even more shocking is that the peak still not may not even be in sight.

To put its value into context, the five most valuable businesses in the world all deal in data (Alphabet/Google, Amazon, Apple, Facebook and Microsoft). It’s even overtaken oil as the world’s most valuable resource.

Yet, even with data’s value being as high as it is, there’s still a long way to go. Many businesses are still getting to grips with data storage, management and analysis.

Fortune 1000 companies, for example, could earn another $65 million in net income, with access to just 10 percent more of their data (from Data-Driven Business Transformation 2017).

We’re already witnessing the beginnings of this increased potential across various industries. Data-driven businesses such as Airbnb, Uber and Netflix are all dominating, disrupting and revolutionizing their respective sectors.

Interestingly, although they provide very different services for the consumer, the organizations themselves all identify as data companies. This simple change in perception and outlook stresses the importance of data to their business models. For them, data analysis isn’t just an arm of the business… It’s the core.

The dominating data-driven businesses use data to influence almost everything. How decisions are made, how processes could be improved, and where the business should focus its innovation efforts.

However, simply establishing that your business could (and should) be getting more out of data, doesn’t necessarily mean you’re ready to reap the rewards.

In fact, a pre-emptive dive into a data strategy could in fact, slow your digital transformation efforts down. Hurried software investments in response to disruption can lead to teething problems in your strategy’s adoption, and shelfware, wasting time and money.

Additionally, oversights in the strategy’s implementation will stifle the very potential effectiveness you’re hoping to benefit from.

Therefore, when deciding to bolster your data efforts, a great place to start is to consider the ‘three Vs’.

The three Vs

The three Vs of data are volume, variety and velocity. Volume references the amount of data; variety, its different sources; and velocity, the speed in which it must be processed.

When you’re ready to start focusing on the business outcomes that you hope data will provide, you can also stretch those three Vs, to five. The five Vs include the aforementioned, and also acknowledge veracity (confidence in the data’s accuracy) and value, but for now we’ll stick to three.

As discussed, the total amount of data in the world is staggering. But the total data available to any one business can be huge in its own right (depending on the extent of your data strategy).

Unsurprisingly, vast volumes of data are sourced from a vast amount of potential sources. It takes dedicated tools to be processed. Even then, the sources are often disparate, and very unlikely to offer worthwhile insight in a vacuum.

This is why it’s so important to have an assured data foundation upon which to build a data platform on.

A solid data foundation

The Any² approach is a strategy for housing, sorting and analysing data that aims to be that very foundation on which you build your data strategy.

Shorthand for Any Data, Anywhere, Any²can help clean up the disparate noise, and let businesses drill down on, and effectively analyze the data in order to yield more reliable and informative results.

It’s especially important today, as data sources are becoming increasingly unstructured, and so more difficult to manage.

Big data for example, can consist of click stream data, Internet of Things data, machine data and social media data. The sources need to be rationalized and correlated so they can be analyzed more effectively.

When it comes to actioning an Any²approach, a fluid relationship between the various data initiative involved is essential. Those being, Data Modeling, Enterprise Architecture, Business Process, and Data Governance.

It also requires collaboration, both in between the aforementioned initiatives, and with the wider business to ensure everybody is working towards the same goal.

With a solid data foundation platform in place, your business can really begin to start realizing data’s potential for itself. You also ensure you’re not left behind as new disruptors enter the market, and your competition continues to evolve.

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