Don't Make These 3 Technology Mistakes You first must understand which goals you're trying to achieve before you can cash in on big data and AI.
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Interacting with customers is one of my favorite aspects of owning a business. It's exciting for me to engage them in conversations about the future of their own companies. Finding the right mindset and technologies to help others envision what that future might look like is among the most rewarding experiences any businessperson can achieve.
Entrepreneurs tend to also be consultants and trusted advisors. I've found that even in Fortune 500 companies with very large teams and budgets, leaders rely on their business partners' guidance to make smarter decisions. In my line of business, that means using analytics to understand how collecting and evaluating the right data can help transform business insights and processes.
In the larger context, I also guide people to make decisions about rapidly changing technology. Depending on a customer's willingness to adopt new methods, this can be an alternately mind-numbing or head-spinning transition. Even the most astute and progressive business leaders can't keep abreast of every new solution or application. The technology landscape is too vast. At the same time, companies are adapting, too. This makes it difficult to find the perfect alignment between business goals and the best technologies to support them.
I've learned that while advancements in analytics have proven very valuable to businesses, critical decision-making often gets left by the wayside. Companies reaching for new tools or analytics applications often buy into the potential of a buzzword. This leads to implementing technologies for which the business is not yet ready. Sometimes, companies incorporate technologies that proved successful for other enterprises but might not deliver the right outcomes for their particular business or the specific challenge they're trying to address.
Here are three common misconceptions that trip up business leaders.
1. My business needs big data.
I hear this from clients all the time. They call us, wanting to know how they, too, can benefit from big data. The fact is, they don't need big data. ... yet. The real issue is they're not seeing enough return from their existing data.
Businesses looking to address their most critical business issues first should focus on the data in hand. They must extract every insight they can from existing data before they think about collecting more information. Yes, data is created with every click and interaction -- but not all data has business value. Think about which types of data will be most useful. For example, do you seek to increase customer retention, improve customer loyalty or capture more cross-sell and upsell opportunities? Maybe it's all of the above.
Tap into the richness of the data you already have within your organization. You might find you need to augment what you know with data from new data sources. Either way, collect only the data you need.
2. Analytics can replace leadership.
Analytics is a driving force in every business sector. It's also leading to new insights in every area of the business, from logistics and operations to sales and marketing. It's easy to see why. Analytics helps people make better, data-driven decisions.
Businesses shouldn't confuse analytics with a basic business tenet: Leadership means everything. Companies with a solid culture grounded in leadership, vision and strategy use analytics to inform all of areas of the business, but they don't look to analytics to lead the way. Data analytics can help measure, monitor and predict. Integrating analytics with data-driven initiatives in other areas of the business will help you figure out what's working well and what isn't.
Still, the single most critical factor to success is leadership. It provides the foundation on which a data-driven culture is built and the business lens through which data must be viewed.
3. Automation and AI are going to upend my business.
Many people are talking about artificial intelligence's potential to replace human workers or eliminate much of the need for human oversight in different business areas. It's true that certain business aspects can be automated. Processes and tasks that can be automated, should be. These include monotonous or mundane processes as well as those that require computing or organizing large quantities of data.
But much like business leaders can't expect analytics to work miracles on its own, companies shouldn't rely on automation and AI to replace uniquely human qualities. On average, about 90 percent of today's analyses are done by humans, with 10 percent performed by machines. This will change as we build technology to help machines get smarter. In another 10 years, some projections peg machines to run 50 percent of all analyses.
It's important to understand that experiments with AI will take place on the periphery of most businesses, where the cost of a mistake is lower. If your entire model is based on algorithms -- like Netflix -- you might trial AI in more central components of your company. Nevertheless, any business decision that requires judgment, prioritization, reasoning or weighing pros and cons will require human intelligence until machines get much better at running these types of problems.
Each of these typical tech misunderstandings offers a fundamental lesson: Just because a technology exists doesn't mean it's the right solution for your business. You must carefully evaluate your business challenges and goals against the outcomes a technology or application realistically can produce. Learning from mistakes is part of being a leader. So is avoiding the critical mistakes you shouldn't make in the first place.