Thanks to code-free analytics tools, every employee can be empowered to use data optimally to revolutionize work as we know it.

For most businesses, extracting value from data can be daunting. Businesses accumulate vast amounts of information, but that data is not always organized, accessible or even usable. Data can mask a wealth of transformational business insights that are lost due to non-optimal management; companies must find a way to extract these insights and use them to drive forward strategically.

Until recently, deriving value from disparate data has required highly-skilled data scientists or data analytics specialists with professional qualifications. But the right talents are not easy to hire and they sometimes can be disconnected from the burning issues that drive the business.

Mine data earlier, not later

Quality data insight is no longer a luxury. Any business looking to drive transformational change must have teams that understand both the business and what it takes to pull the right predictive and prescriptive insights.

Thanks to the evolution of technology, we are now seeing a wave of smarter, more accessible data systems that can be deployed by any organization without the need for specialist qualifications or code. Also, the learning curve with the latest enterprise tools is much less steep than with previous generations. Capabilities like self-service drag-and-drop simplicity, code-free automation, along with built-in help and extensive community support all make the road much easier to navigate.

The data journey has never been shorter and, as companies strive to become more efficient during these difficult times, there is ample motivation to embrace smart, data-driven decision-making.

Coke is IT

One famous company that understands the importance of streamlining and efficiency more than most is Coca-Cola. Currently, its Freestyle touchscreen soda fountains with 165 different Coca-Cola drink products that can be mixed and dispensed individually with custom flavors are found in a number of overseas eateries.

This service requires the ability to dispatch a large number of ingredients to vendors on short notice, and choosing the right volumes used to be tricky, often leading to waste. Coca-Cola fixed the problem with data analytics. Using telemetry, the machines send data back to the firm about what is selling well, and when. The firm is then able to compare those findings against a host of other variables to create predictive models that anticipate demand to balance inventory.

In the Asia Pacific region, the Salvation Army, one of the world’s largest social welfare organizations with more than 1.6 million members in over 120 countries, automated their data migration in an easy and repeatable way.

With over 200,000 rows of data, they were able to process, prep and move data from disparate systems, blending them together and generating a savings of over 2,000 hours of manual effort.

Thanks to next-generation self-service analytic platforms, the complex but valuable data optimization processes cited above are no longer reserved for the “big boys”.

As essential as CRM

Soon, having one centralized platform for all analytics assets will be as essential to businesses as having a customer relationship management (CRM) database or accounting software.

A good data platform is essential for capitalizing on the data economy because it supports analytics creation and consumption across an entire organization. By democratizing data access and discovery, an organization will be empowering every worker to ask the right, business-relevant questions and obtain swift answers without relying on highly-trained data professionals.

Additionally, shareable analytics platforms will be critical to unifying the data, analytic processes and people within an organization. By making all data work additive, and all relevant insights accessible seamlessly and securely by relevant parts of the organization, businesses will be able fast-track the continual digital transformation journey. 

Too often the value of data is lost due to organizational silos, a clumsy patchwork of tools and a limited number of ‘data owners’ within the business. Today, a common point of entry is crucial so that insight can be converted to action in the shortest possible time.

A new category software called Analytic Process Automation (APA) is swiftly differentiating itself by accelerating the rate at which businesses can make critical, data-driven decisions. These systems automate everyday processes and guide any user through the entire data continuum: from data discovery, to insight, to action.

One day, we may reflect upon intelligent analytics software as an early example of enterprise automation that got it right. We may ask ourselves how we ever lived without systems that so readily opened access to data findings.

Technology excels when it simplifies complexity. It allows business leaders to free-up staff for more cognitive and creative tasks. 

Evolving problem solving

We stand on the precipice of a significant revolution in how businesses use data. To move forward, organizations must push beyond descriptive and prescriptive analytics.

Successful businesses like Amazon and Netflix continue to stand apart from competitors by making accurate predictions not just for the present but about tomorrow, too. Given the complexity of building predictive models with code, most businesses have not yet realized the incredible, accelerative advantages of predictive analytics. An ‘analytic divide’ is emerging where companies with access to analytics and automation skills are leaving those that lack those capabilities behind.

 Analytic Process Automation systems are here to change that. Through these platforms, methods that used to require a high level of skill can now be executed by employees throughout an organization thanks to ‘code-free’ and assisted building blocks that can construct models with transparency and make data science learning and upskilling easier.

Companies do not need to hire specialists for this role. As more businesses embrace prediction, entire industries will reinvent themselves.

Tapping the data goldmine

Sometimes the greatest obstacle is the data itself. In business we are surrounded by data and yet it can often be difficult to understand. In many cases, the most valuable data—data that can drive the best, most precise predictive insights—is buried in PDFs or images, or perhaps even more abstract forms such as in the opinions or emotions of customers. 

Fortunately, the world around us can now almost entirely be understood in terms of quantifiable data. Be it a photograph, a piece of text or even a handwritten note, intelligent software allows us to lift information from its original context, and this capability is now being democratized so that any business can use it to inform fresh perspectives on stubborn problems. 

Again, a user-friendly format is already liberating these capabilities from the grip of data specialists and providing any business the tools it needs to import difficult data.

This level of dexterity is beyond anything we have seen from legacy enterprise systems. It puts the power of discovery and prediction directly into the hands of decision-makers, expediting what has often been a slow, tedious and skills-dependent process. 

Today, there is much speculation about the future of the workplace, and not all of it is optimistic. Yet, this is also a moment to look ahead to data. When coupled with automation and intelligence, we can mine it to drive real, measurable business outcomes while amplifying the thinking of the humans at the helm. If this happens at scale, we could expect a resurgence of smart, responsive organizations equipped to tackle whatever global economic crisis that comes next.

We already know that many businesses are sitting on a goldmine of intel and untapped talent. Next-generation analytics platform will have less to do with what technology and automation will take away, but about what it will give back in spades.