Enabling the smart & digital enterprise

In the digital era, data is everything, let's look at the data journey and how to make your data work smarter for your business.

I recently gave a presentation at the Gartner Expo in Barcelona, about a subject that is right at the front of my mind just now. The digital era, data and making sense of it. Where do we go from here?

Data now dominates both our work and personal lives. We are now subjected to as much information in any given day as our 15th century ancestors were exposed to in their entire lifetimes, and according to the Economist, by 2025 we will output 62Gb of data per person per day – compared to 500Mb in 2012. Consider just a couple of the numbers and it becomes clear just how much data is the dominant force in our world today: every day, social media gains 840 new users each minute while there are 3,607,080 Google searches conducted every minute.

In effect, we humans have become data-generating machines ourselves. Almost everything we now do creates and leaves a trail of digital breadcrumbs behind us. As such, to process and manage all this data, our world is developing a kind of ‘nervous system’ in which every human being acts as a sensor.

Opportunity, risk and threat

It has been suggested that data is like the new oil, in that it is such an enabler of scalability, new interaction and business models and numerous other new business activities. But while all this data presents enterprises with great opportunities to develop commercial offerings, it also carries with it a degree of risk.

I feel that data has become effectively like a new human sense. It is like vision, audio or our sense of balance – and like our senses and our central nervous system, it is subject to numerous events along its journey as we seek to turn it into actionable commercial information.

Actionable and Business outcomes are the desired end goal of the data, but they are also the stage of the data’s journey where it is most visible, meaning it is at its most vulnerable too: the data can deliver a meaningful outcome but it also possesses the power to disrupt or render any outcome to be less consequential.

Challenges around data exploitation

According to Gartner, there are four main challenges that enterprise executives face regarding data. First, how to turn that data into real value. Second, how to pull together the necessary skills and capabilities. Third, what are the risk and governance issues around issues like security, privacy and data quality? And fourth, how do they best integrate old and new technology and multiple data sources?

It is my view that these challenges are best addressed and overcome via a six step process. In 2000, around 65 percent of the world’s data was still analog. By 2015, the amount of analog data had dropped to less than 1 percent. Everything else was digital, illustrating that we are in the truly digital era now. And how we avoid potential problems in business requires a thorough, end-to-end approach in how we collect, transport, store, secure, analyze and collaborate around data.

Collecting Data is the beginning of the journey. A good example of a company that is inundated with data is Walmart, which gathers up more than 2.5 Petabytes of data from customer transactions every hour! That’s the equivalent of around 20 million filing cabinets’ worth of printed text. This is the first step along the journey.

Orange Business Services has recently announced its first "Smart Resort" in Montgenèvre, in the Alps – the concept brought to life by the ability to capture and analyze population flow statistics throughout the year or around a particular event. This process, which collects and uses anonymized data from Orange’s public mobile network, helps in decision making when important choices must be made to improve tourist services in the valley.

Connect & Transport Data is the second stage. To fully exploit data and maximize it, we have to be able to carry it securely with hi-Quality wherever it is needed – and that means coverage, everywhere. Today companies outsource all kinds of business services, including manufacturing components in various territories, and alongside that they also have multiple data centers that are home to vital research & development (R&D) applications. These R&D apps are typically time-sensitive and companies need connectivity that can connect the knowledge workers at their R&D centers to remote production sites reliably and rapidly.

Store and compute data

As data grows, how we store and manage it increases in importance too. This is step three. Thanks to cloud advances, there are now more ways to do it that address enterprise needs. If a company has data privacy or regulatory concerns, storing data in a private cloud makes sense. To keep on top of costs, enterprises can opt to perform data analytics and visualization in a public cloud, securing the traffic in transit.

It has been forecast that by 2020, one-third of all data will be stored, or will have passed through the cloud, and we will have created 35 zettabytes of data. How and where (center or at the edge) we store that data will impact how successfully we are able to leverage it.

Secure and protect data

Step four on the journey is security. Some facts: cybersecurity experts generally agree that damages incurred from cybercrime will cost the world $6 trillion annually by 2021, up from $3 trillion one year ago. This huge shift represents the greatest transfer of economic wealth in history, and carries additional threats along with it. The potential for being a victim of cybercrime can make companies baulk at innovation and investment. Cybercrime is also set to overtake the worldwide narcotics trade, as it will become more profitable than the global trade of all major illegal drugs combined.

Enterprises are set to respond to this ever-growing threat, with cybersecurity spending to exceed $1 trillion from 2017 to 2021.

Analyze data

Data analytics are already delivering big value to companies via new Business insights and helping create new revenue streams and new business opportunities, but as step five, it is worth recognizing that analysis will only grow in importance on the data journey.

Enterprises will continue to embrace the benefits that deep learning brings to helping them understand big data in new markets. And companies like us will continue investing to develop these valuable capabilities. Check out the recent news about our acquisition of Business & Decision to accelerate Orange Business Services’ growth in Data

Collaborate & Decide using Data - Completing the journey

The last stage of the data journey is providing stakeholders with analyzed data that they can put to use by collaborating around it. Employees, customers, partners and suppliers can all be part of this equation and work together to “let the data speak”.

Orange is working with a number of smart city projects, e.g. in the Middle East to help them make the most of their data. In smart cities, data is everywhere and everything. It is in electricity, gas and water, in traffic management and road safety, in hospitals and schools. All this data is intended to enhance citizens’ lives – and once it has been gathered, stored and analyzed, it can then be collaborated over by all the relevant parties to achieve this.

Remember the human touch

Collaboration over data is where we humanize the endpoint of the journey.

At the Gartner Expo I heard one CIO comment that “Data enables us to evolve from a knowing culture to a learning culture, from a culture that largely depends on heuristics in decision making to a culture that is much more objective and data driven and embraces the power of data and technology.” The Sloan School of Business reports that companies engaged in data-driven decision-making see a 6 percent increase in productivity of the company over companies that do not.

A further human touch within the data journey, and one that references the Gartner point about skills and capabilities, is that the way we address “talent” has also evolved. Today more CIOs are seeking prospective employees who are skilled in multiple areas, not just in a single solution. The handing over of routine tasks to bots will continue, but this does not replace humans, it actually frees them up to perform more complex, greater value tasks.

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If you would like to talk further about the data journey and explore ways of creating a holistic end-to-end strategy to manage it, please drop me a line.