The Trend of Smart Analytics in 2020 - 1/2: The Critical Challenges

The whole point of “smart analytics” is that the technology can do more of the problem-solving work for us — but despite continuous advances, challenges still exist for many businesses. To understand what those are, let’s first look at why businesses are tapping into the power of smart analytics.

Data mining and data analysis have done great things for conversion marketing, the mainstay of any business; companies that leverage big data and analytics are 23 times more likely to acquire customers and 19 more times more likely to see a boost in their finances (McKinsey). Beyond marketing, smart analytics — such as predictive analytics — guide organizations to understand consumer demands and thus craft the right products (for example, the University of Delaware is using smart analytics for asthma healthcare).

And while modern software’s ability to better investigate and understand their markets has clearly had a positive impact, it’s not having the effect it could because of technical and cultural challenges. Here’s where we see smart business analytics missing the mark for many:

Too Many Data Distractions.

Expanded data gathering capabilities means businesses have as much research, information and data sets as they can handle — but that creates more challenges, particularly around cherry-picking and organization. In a sea of data, everyday users are tasked with having to determine which data matters and which is noise — and quick, efficient decision making becomes difficult. Having seen the effects of this first-hand, we built Kubit in a way that guides users in prioritizing the KPIs that matter most, empowering users to customize key measurements specific to their businesses.

Lack of Holistic Problem Solving.

It’s not uncommon to hear a clip from a celebrity interview taken completely out of context. Imagine having to figure out the true meaning of a strong statement without having any idea of what the larger conversation was about! The same goes for data analytics. Most options on the market lack sufficient capabilities around contextual information — or what we call “benchmark analytics” — which can help a company understand data most holistically. Why is that a challenge? A lack of rich contextual data can send analysts on a wild goose chase for days trying to solve a problem — only to find out it was a simple anomaly that unnecessarily cost them time and money. To solve this, Kubit facilitates analysis around imported historical data and prescriptive insights, which also helps the AI in learning for improved analytical capabilities over time.

Cultural and Technical Paradigms.

Smart analytics systems have typically been reserved for those in project management or those with a data science degree. The idea is that mainstream employees may not always understand the process behind querying (or even have access to data within their own organization). But querying is really just asking a question, and everyone knows how to do that. Because of this heavily ingrained mindset, companies are missing out on a potential competitive advantage in bringing together each department’s unique insights and abilities to independently investigate. Kubit believes that companies don’t need to train employees in new skills around data analysis — they just need an easy-to-use, self-service platform that enables them to ask questions (as well as provides teams with intuitive reporting features that will help them show the evidence behind their data-driven decisions). The other cultural challenge is technical:cloud computing has become a highly competitive space, leading many vendors to partners selectively with other vendors. (For example, if I am using software A, I then can’t use software B because they will not talk to each other — even though the combination of the two would serve me the best). Additional fears around system integration issues and data security encourage businesses to keep with an ineffective status quo around data analytics. To address this, Kubit has partnered with Snowflake and Segment to make integrations easier and more open, as well as fully secure.

Stay tuned for our next blog in this series, where we’ll outline what new players are making moves in this space and how it can help your business.

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