7 Ways To Make Big Data Work For Your Business

Data is the lifeblood of the 4th industrial revolution. 90% of the worlds data was created within the past two years and this is only going to increase exponentially. With so much data at your fingertips, it’s easy to become overwhelmed and stand by the wayside while the rest of the world and especially your competitors dig in.

The ways to successfully actualizing benefits are diverse and times painful, but there is no way around it. Emerging technologies will continue to crop up and the internet-of-things phenomenon is changing how we solve IT and business problems by the day. Resisting it will most definitely mean lethargic growth, low profit margins, weak innovation capabilities and quite possibility disappearance from the market altogether.

Analyzing Your In-House Data

At the centre of this tide of change is data. Businesses are sitting on a data goldmine and the key to getting your skin in the game is to start with the data on hand. And start small. Most enterprises already have a wealth of unleveraged data .The majority of this is legacy data. Analyzing and enriching this data will help your business identify trends and act swiftly to meet unseen demands. Ignoring trends identified or failing to act could be fatal for your business. Too much will be lost by sitting on the fence.

Act Swiftly On Data Analytics Outcomes

Once consumer trends are identified, you will need to act swiftly. In the old days, it was good enough to take a look at data from the previous month or even quarter to fashion a model of what your customer’s preferences or tendencies are. But having the ability to do this in real time, not hours or days after a customer’s last interaction gives you unprecedented influence on their behaviour.

Buzzfeed, The Huffington Post and Vox are shining examples of profitable businesses that are able to capitalize on the struggles of The New York Times, by its own account, to achieve success digitally. An internal leaked report , in March 2014, stated,”…the newsroom needs to become a more nimble, digitally focused newsroom that can thrive in a landscape of constant change.”

Anticipate Future Needs

Changes driven by data are constant. Being actively involved in your own data analytics outcomes will give you forecasts into future customer needs. Ancillary players that have not invested in their own data mining and analytics only need to come up with offerings that are cheaper and at times better than your own, even if you are the current market leader. By anticipating these needs, you have the chance to develop these offerings before your competitors.

In 2010, GE said it wanted to create a solar power business that would rival its $6 billion wind energy business. Despite data indicating that the cost of photovoltaic cells were decreasing as their power increased, GE did not make the required investment. A start-up SolarCity swooped in and developed a business model that took advantage of the sudden boom in solar panels .In the spring of 2014, GE CEO Jeffrey Immelt acknowledged that GE had missed an opportunity stating “My God, I wish I had thought of that,”

Strengthen Your Data Workforce

As with any emerging technology, the recipe for success involves a mix of technical knowledge, business acumen and delivery skills. With every business role being affected, and the right skills in short supply employees will need to be re-skilled. Line managers will be critical in steering the new workforce through this tremendous change while going through the changes themselves.

According to Gartner, through 2020, a lack of data science specialists will inhibit 75% of organizations from achieve their full potential in navigating the big data, IoT and AI landscape.

Innovate via Ecosystems

With systems in place to harness opportunities from in-house data, your company will have a base with which to effectively collaborate with other business, start-ups and third parties. By opening your enterprise up to collaboration, you will get access to a host of opportunities with companies that can complement your services and design innovative applications utilizing outcomes from your data analytics.

As is often the case with automotive companies, Renault teamed up with Paris Incubateurs to expand cooperation between itself and automotive technology startups working on technologies for R-Link and Renaults connected vehicles.

Ensure Data Security

The exploitation of big data by any business can create outsized returns and deliver phenomenal,

relevant, and often free experiences for its customers. At the same time surveys consistently indicate that consumers have concerns about their privacy, and with the amount of data collected about them, these concerns are justified. The risks are two pronged; corporations crossing the bounds of privacy and the threat of cybercriminals raiding these databases. It is essential to understand the  social contract you are entering with your customers, treat this data with respect and be transparent at all times

Target was involved in a serious financial and security breach  between Nov 27 -Dec 2013 when as many as 40 million credit and debit card accounts were impacted. The breach was carried out by hacking into the retailer’s payment system. Things quickly escalated with the retailer closing all 133 of its stores in  Canada and laying off thousands of workers.

Hold On To Your Own Data

In a data driven economy, your data becomes a commodity in itself, with immense value. If you decide to engage with a data company, you need to ensure your data is not held hostage or have your access to it undermined. Converting your data to their own file formats, throttling the amount of bandwidth customers are allowed and miscellaneous fees embedded in fine print are just some of the ways your data can be held above your head , forcing you to fork up a heft ransom to regain access to it.

The Perils of AI Fuelled Warfare

Significant advances in artificial intelligence over the past decade have changed our way of life, and the impacts of AI are only expected to accelerate.

At the same time, the idea of military applications of AI and the attribute of autonomy has created considerable controversy. There are strong concerns about these technologies, that they could lead to the catastrophic consequences.

What are the actual risks of weaponizing this technology and their effects on international security and stability?

Current applications involve examples in which machines perform specific, pre-programmed tasks for specific purposes. But the possibility of things going horribly left is glaring, multifaceted and all encompassing.

The attached infographic highlights some of the perils of AI fuelled warfare.

The Military Potential of AI and The Future of Warfare

“Artificial intelligence is the future, not only for Russia, but for all humankind. It comes with colossal opportunities, but also threats that are difficult to predict. Whoever becomes the leader in this sphere will become the ruler of the world,”.These were the words of Russian President Vladimir Putin addressing an audience of over a million students and teachers from 16,000 schools in an open lesson on September 1,2017 the start of the school year in Russia. The president concluded that speech by stating  he would not like to see anyone “monopolize” the field.

Like so many technologies, AI is loaded with latent military potential. The United States and China are currently in a race to command the AI heights for both peacetime and wartime uses, driven in part by the rapid absorption of nascent AI-based technologies into diverse sectors often with transformative effects. In June 2018, the U.S. Department of Defense (DoD). The DOD set up its Joint Artificial Intelligence Center, following the establishment of the White House’s Select Committee on AI in May 2018 and the release of the White House Executive Order on Maintaining American Leadership in Artificial Intelligence on February 11, 2019. DOD spending on AI has also increased and AI-supported data analytics are already in use throughout the defense and intelligence communities for military applications like logistics, planning, analysis, and transportation. China’s president is less outspoken on this matter, but has committed China to become the dominant AI power by 2030.

What are we to make of all this? Are the expectations of revolutionary AI realistic? Will the consequences prove positive, negative, or perhaps both for international security and stability?

Michael Horowitz of the University of Pennsylvania compares AI to the internal combustion engine or electricity—an enabling technology with myriad applications. He divides its military applications into three sorts-a)the automation of machines to act without human supervision, b)the capability to process and interpret large volumes of data and c)aiding or handing over the command to conduct and control war.

Starting with automation, AI is required to program skills into a machine like perception, navigation and and higher-order skills, like co-ordination with other machines. In February 2019 , the Defence Advanced Research Projects Agency (darpa), the Pentagon’s blue-sky-thinking branch, conducted their latest test of a six-strong drone swarm capable of collaborating even when cut off from human contact. The drones analyzed two city blocks to find, surround, and secure a mock city building. The US Army has also begun to test the use of drones for infantry units. It recently issued FLIR drones — tiny, palm-sized devices — which can be used to fly ahead of soldiers and send back video and other data.

In an age of unprecedented data abundance, the role for AI in military pursuits is to beam back raw data that might be turned into useful intelligence for warfare. Object identification is a natural starting point for AI and requires sifting through a staggering amount of images and information collected from satellites and drones to find things of military importance, such as missiles, troops, and other relevant intelligence information.

Then comes processing the data collected by drones. Algorithms consistently surpass human performance in image classification and object segmentation,which involves picking out multiple objects from single images, crucial in isolating targets during conflict. AI-empowered systems that makes it possible to locate, track, and target a variety of enemy weapons systems raises the possibility of striking strategic assets, such as aircraft carriers, mobile missiles, or nuclear weapons.

The availability of enormous amounts of data is well suited for another purpose; cyber attacks. On the offence, AI could locate and target particular individual accounts for collection, disruption, or disinformation. On the defense, it could detect and deter such intrusions for sensitive information.

China’s applications of AI for societal surveillance is no secret and there is no reason why this couldn’t be applied and expanded on in times of war. Similarly Russian influence operations have demonstrated just how vulnerable social media platforms are to manipulate as evidence in the 2016 US elections.

In summary, AI has great potential application in the military domain, at both the operational and strategic levels of war, but things could just as easily go very wrong. Machines automated to perform tasks need to be programmed with human values like fairness to be effective. A gun toting robot designed to perform in a specific controlled environment might not perform in the unfamiliarity of an actual battlefield. Distorted data could lead AI systems to take unintended actions, sparking catastrophic reactions, including escalation and retaliation.

The Economic Viability of Plant Factories.

One of the most frequently encountered criticisms of plant factories with artificial lightning is that it is a much more costly endeavor than regular land farming; that along with the unwillingness of the general public to get behind a system that utilizes waste water to produce our food. However, a deeper look into the actual costs of running a unit settles the fact that compared to the conventional method, there is not much difference between the two in terms of cost.

In the case of open land farming initial set up costs include the cost of the land area itself in addition to field preparation and facilities for irrigation, drainage, tilling, planting,harvesting and eventual transporting. These costs are recovered with the production output generated from the land usually over a time period of a few decades.

With PFALs (Plant Factories using Artificial Lighting), the production capacity is 100 times that of open land farming and 10 times that of a greenhouse facility fitted with an evironment control system. So in essence, there is no real difference between the costs of all three systems. The output is high quality plant produce without the use of pesticides and with high resource use efficiency.

It should be noted that in reality current PFALs operate at 60-70% capacity, albeit at a loss but this is attributed to design and construction flaws and lack of production management experience among factory managers and overall business operations.

With regards to future cost reductions it is expected that that costs of PFALs will be cut in half in the near future. In Japan, several facilities have reduced their operation costs and these are expected to continue reducing steadily.

Reference: Kozai T. Niu G, Takagaki M (eds) (2015) [Plant Factory; an indoor vertical farming system for efficient quality food production. Academic, 405 pages]

From Vertical Farms to Plant Factories

Not entirely a new concept, the use of vertical square footage is gaining new momentum.

Vertical Farming vs. Land farming

Owning and buying land to cultivate is expensive and comes with a host of problems to contend with before the crop can get going. Processing the land, tilling, preparing the soil is extremely labor intensive and even then more problems persist. The planted seeds are at the mercy of uncontrolled elements, disease and pests.

In comparison, indoor modular structures where trays are stacked on top of each other makes use of precious vertical square footage and they are compact and can be scaled up. With vertical farms, carefully controlled climatic conditions with hydroponic systems that supply the crop all the nutrients it needs significantly near guarantees a good yield. Moreover the crops are free of chemicals from pesticides and can be consumed immediately without having to transport them to far away locations, thereby reducing emissions from the transport system.

Intelligent Growth Solutions(IGS) a vertical farming company based at Invergowrie,near Dundee, in Scotland, has nine meter-high towers in their demonstration unit that occupies barely 40 square meters. The stacked trays provide 350 square metres of growing area, bathed in LED lights from 1,000 light emitting diodes (leds) strung out above each tray. The demonstration unit is air locked to keep bugs out and temperature, humidity and ventilation are controlled remotely via an app.

Vertical Farming vs. Greenhouse farming

The only significant drawback to vertical farming is high running costs. A greenhouse gets its light and much of its heat, free, courtesy of the sun. The high cost of the electricity required to run the large number of LEDs means that for the moment only high-value, perishable produce only, such as salad leaves and herbs are grown. One way of saving electricity is to only produce the colors that are required by the plants instead of the full spectrum of white light.

The Way Forward

Vertical farming is definitely the future of agriculture. Its advantages outweigh its drawbacks but the few drawbacks that exist are pressing. It may not feed the world but for now it is the best way forward in harnessing local energy to produce our food and produce consistent good yields.