Despite the emergence of blockchain, analytics continue to be crucial for many organizations to develop. Given the amount of data that’s being generated, advocates consider it a major oversight not to use the information. Of course, this could always be a double-edged sword.
The recent Facebook and Cambridge Analytica scandal only underscored the power that the applications of analytics and intelligence have to influence people. However, regardless of intention, the potential is there.
For businesses, the ability to make game-changing decisions is core to survival given today’s environment. Successful analytics projects have led to competitive advantages. UPS, for instance, uses big data to optimize its fleets’ routes allowing it to deliver more packages at less cost. Walmart has been able to stay relevant as a brick-and-mortar retailer despite the tremendous growth of e-commerce thanks to its analytics hub. Walmart’s facility churns out timely insights that allow their operations to readily adjust to emerging trends.
Unfortunately for many organizations, tapping into big data is still quite complex. Big data has long been a big players' game and smaller businesses struggle to compete as even larger enterprises find barriers to analytics still exist. Even if cost isn’t an issue for a business, data science expertise might be one. Blockchain, however, is leveling the playing field by making powerful tools that overcome these barriers accessible to everyone. Could this eventually lead to better decision-making for organizations?
Enterprise-Grade Tools and Capabilities
Blockchain is being applied to just about everything these days. It was inevitable for ventures to fuse blockchain and analytics together, which has resulted in various interrelated projects such as data marketplaces, predictive analytics, sentiment analysis, and artificial intelligence (AI) platforms.
Big data projects typically require immense amounts of computing power which becomes a barrier for less-resourced enterprises. Blockchain networks prove useful in this regard as their distributed infrastructure allows them to tap into numerous computers to essentially function as large supercomputers. Anyone can spend Ether tokens and have Ethereum’s virtual machine run computing jobs. Other AI-meets-blockchain projects like DeepBrain Chain and TraneAI also seek to provide readily-available computing power to big data efforts.
Aside from infrastructure, there’s also the expertise required that needs consideration. Analytical projects often need multi-disciplinary expertise in a variety of fields, but now, these new platforms seek to make analytics as user-friendly as possible. Endor, for instance, created by MIT engineers has recently entered the crypto space by offering a blockchain protocol that allows users to simply ask questions and get back predictions. Using the protocol, businesses can get powerful insights through straightforward queries in almost as simple a manner as searching for information on google.
Making Big Data More Accessible
The distributed architecture helps offset the infrastructure costs that are typically needed to sustain such computing resources. But aside from the computing power, these blockchain-based services also provide greater accessibility.
The token economies that govern these various platforms attempt to make them self-sustaining. Peers who contribute computing resources or help out in the maintenance and improvement of these systems are rewarded with crypto tokens for their efforts. These combine to make access considerably cheaper and participation, incentivized. Users can also acquire these utility tokens through initial coin offerings at significant discounts.
Organizations and individuals as well don't need to have massive budgets or hire armies of experts to use these tools or even gain access to the data. There are now blockchain-based marketplaces through which companies and individuals can simply purchase the data or insights they need. Data marketplaces like Datum and Repux seek to make more data usable by enabling users to easily purchase access to repositories and use the information in their own analytic efforts.
Data-Driven Decisions
These platforms essentially provide the requisites for interested parties to embark on their own analytics and intelligence projects lowering significant barriers like cost, expertise, and where to get the raw data from. The big question now is whether smaller companies will eventually take the big step and begin using these tools and services to fuel their own decision-making processes.
Using data in decisions making has two key benefits, namely objectivity and speed. Numbers, unless distorted, never lie and so, insights generated from quantitative information are impartial and unbiased. They aren’t colored or influenced by people’s tastes, dispositions, or emotions. Decision makers can trust that the numbers paint a better picture of reality than their opinion of reality. Numbers can also reveal trends that aren’t obvious just from observation.
Through the use of intelligence tools, analyses could take into account large volumes and wide varieties of data. Insights would be able to be generated in real-time allowing decision-makers to make timely choices and adjustments to strategies. For smaller organization, this combined with their agility could level the playing field when going up against industry giants.
Translating to Action
Still, it is up to organizations whether or not to finally pursue analytics and intelligence efforts. The benefits reaped by those who successfully implemented data projects should encourage ventures to do so. The sophistication of analytics tools and their accessibility thanks to these new blockchain services leave little excuse not to pursue such efforts.
It is crucial is for organizations to adopt a data-driven mindset and encourage smart decision making based on tangible data. Insights, regardless of how rich and timely, aren't worth much if they aren’t readily translated into action. It is also important to focus on solving real business problems and pain points, with analytics, this could become an easier task for many businesses.
Jim Hoffer is founder and managing director at Hoffer Financial Consulting. Follow him on Twitter.