3 Fundamental Ways Machine Learning Will Change Business in 2018 We aren't talking about losing jobs, we're talking about more effective use of human talent.
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As entrepreneurs, it's our job to evolve and adapt to a changing market. Artificial Intelligence (AI) and machine learning initiatives are creating new opportunities for innovators to offload labor-intensive research and analysis to the cloud.
And, to be clear, "the cloud" is just a fancy term for someone else's computer. But, it's exciting to see these networks of computers crunch data and automate the things that used to eat up our time and server space.
In today's market, the cloud represents a $130 billion industry. And it's projected to continue growing as consumers and corporations continue to offload their data storage, analysis and computing to the cloud.
Machine learning is an exciting, proven concept that allows computers to figure things out for themselves. Instead of every action being explicitly coded, the computer applies pre-configured rules and data sets to perform complex calculations. This technology leverages the cloud in order maximize speed and cost-effectiveness.
Machine learning, powered by the cloud, will impact businesses in the following ways:
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1. Data visualization and KPI tracking
When questions are raised -- like what course a company should take when launching a new product or service -- data won't be confined to a database. Instead, machine learning will allow decision-makers to quickly posit questions and get informed answers that are easily digestible.
Visualizing data helps everyone make better decisions. "90 percent of information transmitted to the brain is visual, and visuals are processed 60,000X faster in the brain than text." So, the more we focus on making data analysis accessible to every member of the team, the more reliable organizations will become at hitting KPI's.
Business leaders should focus a portion of their team's energy on getting comfortable with visual data. Give every member of the organization access to the information that they need to self-assess their effectiveness -- even if it isn't fully optimized.
We are already seeing machine learning platforms evolve that automate critical reporting. Sisense Pulse, for example, is a platform that simplifies the process of reviewing business intelligence, automating the creation of visual reports and improving the chances that an organization can successfully track and exceed their key metrics.
Through active monitoring, the platform can immediately notify key personnel when data anomalies occur that either negatively or positively impact key performance metrics. This helps "corporate first responders" jump into action to solve problems before they become red ink, or to double down on initiatives that are yielding fast returns.
The way that these types of platforms communicate is designed to plug-into the existing corporate communication infrastructure. Zapier and Slack can be integrated into Sisense's ecosystem, creating a comprehensive system for collecting, analyzing and communicating critical BI across the entire organization and with external stakeholders.
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2. Better insights into consumer behavior
The cycle of report generation and KPI analysis will continue to become increasingly automated. And, just as the effectiveness of your team will begin to be monitored by computers, so will the analysis of consumer behavior.
Generating actionable business insights with AI is becoming much easier, thanks to cloud-based platforms that can mine existing data to predict future consumer trends. And consumers are happy to fork over personal information in return for a personalized shopping experience that predicts their needs and wants.
This is exciting, because it empowers businesses to provide a more customized experience -- speaking specifically to their future needs. When companies can predict future needs, they can better position themselves to meet them more effectively than the competition.
Leaders should aggressively deploy AI right now. Get comfortable with it, and learn ways to effectively use it for cleaner decision making in the future. Trust me, your competitors already are.
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3. More effective human labor.
The exciting, and somewhat scary byproduct of increased reliance on AI is that we will need less man hours to compile reports and guide decision-making. This might sound like we'll lose jobs and increase unemployment in 2018 due to robots taking human jobs.
This isn't the case. Just as stagecoach manufacturers had to pivot to new industries after the Model T, data-entry personnel will find ways to use their experience to provide value to companies that no longer require as many hours of manual data mining.
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And I would argue that most organizations have already streamlined their human resources department. Every organization's goal is to operate efficiently and profitably. So, we aren't talking about a loss of a huge number of jobs. We're talking about continuing a trend toward tech integration and more effective use of human talent.
There's a reason that union membership is falling. Employees are working within corporations that are reaping the rewards of improved employee engagement. Engagement can only be improved by giving employees access to the critical information they need to understand their impact on the organization.
I'm excited to see where the trend in automated Business Intelligence heads in the coming years. And, it's my hope that making BI more accessible leads to another surge in entrepreneurship -- as employees gain the confidence to strike out on their own and disrupt stagnant industries.