As you read this, data volumes across the world are exploding at an unprecedented rate. Facebook Messenger and WhatsApp alone process 60 billion messages a day. Instagram has over 500 million active users per month who share more than 95 million photos and videos every day. And that's just social media. McKinsey predicts that by 2020, as many as 30 billion smart devices will be connected. Can you imagine the amount of data that that will produce?
What's truly exciting is that we now have the technology to dig deep into these massive treasure troves of data, and draw out meaningful connections and insights that will allow us to make better, faster decisions. We're finally beginning to make the shift from collecting data to connecting data. Emerging technologies such as natural language processing, machine learning, and artificial intelligence have catapulted us into a new era of human intelligence supplemented and enhanced by data science.
In this exciting new world, the individuals and organizations who are able to truly harness the power of data - those who can turn it into timely insights to drive performance, decrease risks, and pursue opportunities - those will be the innovators, the survivors, and success stories of tomorrow.
Big data is fundamentally changing the way we do things. Take the automobile industry, for instance. Where traditional car safety features like airbags and seat belts were designed to react to accidents, Tesla is shifting the narrative to how we can avoid accidents by collecting real-time data on driver behavior, and combining it with machine-learning concepts to build smarter, safer vehicles.
In healthcare too, we're not far from a time when big data will provide a way to predict and prevent epidemics, cure diseases, and improve one's quality of life. Imagine if your smartphone could suggest the single dietary change that would most improve your health based on your unique genetic material and medical history? That and more is exactly what healthcare groups like the Pittsburgh Health Data Alliance are working towards by combining and crunching data from electronic medical records, genomic sequencing, insurance documents, and even wearable sensors.
As for education, big data holds enormous potential to create happier, smarter children by personalizing learning and development programs to each child's unique needs. Already institutions like the Grand Rapids Public Schools in Michigan are mining data to successfully quantify and minimize chronic student absenteeism.
Meanwhile, cities have begun using the power of data gathered from road sensors and traffic cameras to control traffic lights and reduce congestion. Police forces are using predictive data analytics to anticipate and prevent crimes, as well as to foil terrorist plots. Agriculturalists are exploring how we can end world hunger by using big data to optimize crop production. And all this is just the tip of the iceberg.
Better Decisions with Better Information
In businesses too, big data and analytics are empowering decision-makers to anticipate the risks and opportunities that lie ahead, instead of reacting to them after they occur. This forward-looking approach is particularly important in today's uncertain world, marked by events such as Brexit, political upheavals, plunging oil prices, and large-scale cyber security attacks. If we, as businesses, are to effectively manage these hurdles, we need true systems of intelligence to support decision-making. As noted management consultant, Geoffrey Moore said, "Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway."
It's time we started pushing ourselves to anticipate the challenges ahead, and develop effective solutions using big data. Take cybersecurity, for instance. Can we develop more predictive approaches to threat identification and monitoring? Many companies are already analyzing previous data breaches or hacks to anticipate where future threats could occur. Some are tracking the online behavior of employees to uncover trends and patterns that could prevent insider threats. In the future, behavior analytics could become so sophisticated that we could make highly accurate predictions about cyber-criminal tendencies in the individual. We're already going beyond machine learning to talk about deep learning where cyber security systems can detect new malware at the point of entry in real time with the same speed and precision that the human eye can identify a water bottle.
What about the supply chain? Can we leverage internally gathered supplier information, supplemented with data from external sources such as Dun & Bradstreet, to automatically cluster suppliers into various groups based on specific parameters? We could then determine the outliers in each group and descend on them with a greater degree of granularity to address the associated risks. Or, we could combine historical data analyses with risk mapping and scenario planning to anticipate where supply chain issues could occur, so that they can then be minimized ahead of time. The possibilities are immense.
In this exciting new world, full of possibility, organizations will be powered by intelligence, data and metrics. In this context, traditional forms of management must also evolve. Looking backwards, we can see that the role of "management" in industrial-age organizations was to maintain formal hierarchies, and to ensure that specific tasks were carried out by workers within well-defined roles. Management was a top-down approach, and all power lied with the managers themselves rather than with the workers. Over time, we moved from factories to office environments, and the role of management continued to evolve.
In modern organizations of the future, the "manager" role will not micro-manage the tasks of their team. Rather, he or she will take on role that resembles that of a coach, facilitator, and mentor. He or she will also help establish what the organization's risk appetite is, and communicate clearly the acceptable level of risk tolerance. He or she will continually create and cultivate the appropriate layer of governance, which includes establishing the organizational code of conduct, setting the tone from the top down and bottom- up, and cultivating values of trust, integrity, reputation, ethics -- the things that you can't touch or feel, but can sense that they exist.
These modern and forward-looking managers will also leverage the vastness of data - relying on analytics and big data metrics at every step of the way. They will draw from real-time, preemptive, predictive, and proactive feedback and insights, and gather intelligence from across the organization and extended enterprise. They will leverage a federated technology system and implement processes that allow their teams to fulfill their tasks, deliver to customer expectations, and meet the promises they have made to the market.
It's important for managers to remember that achieving value from big data isn't just about applying sophisticated algorithms. It's about, first of all, asking the right questions so that you can narrow your data set to provide more accurate insights. It's also about communicating your findings to your team in a simple and clear manner, using examples, story-telling techniques, and visualizations. And finally, effective analytics is about acting on your findings -- making decisions quickly, and implementing effective solutions that drive performance.
Leading Towards the Future
As we enter an age of drones, robots, self-driving cars, and other connected "things," perhaps it's time to question our traditional approaches to both management and business. The world around us is rapidly changing, and if we want to stay ahead, we need to lead by making faster, better decisions based on accurate and timely business intelligence. Leaders today must wake up the possibilities of the future, and to the power of big data. It is here and it is now.
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