Advanced Analytics Implementation To Benefit From Big Data And Optimize Your Business Outcomes

Any type of analytics is about driving change in the company, improving business processes, or addressing specific business problems to find solutions. SAS as a statistical software suite developed by SAS Institute of data management outlines advanced analytics as a set of tools ‘to apply advanced technology to make your company effective, and interact with the problem to gain the best decision’.

Advanced analytics provides the enterprise with deeper and more substantial insight into patterns, trends, or issues hidden inside the data. It supports the business with more understanding of their customers, buyers’ behavior, predicting future outcomes, and KPIs.

Except for business intelligence, advanced analytics can be presented in the form of data mining, predictive, perspective, and big data analytics. Applying all the types of advanced analytics management is able to optimize company operational scope.

If you implement advanced analytics you gain the following benefits:

• optimizing your decisions (increase booking or buying rates by designing demanded offers and hot deals);
• refining your TA segmentation (specify your client profile, and boost finding new business opportunities);
• enhancing predictions (e.g. predict the outcomes of your ad campaign to make it cost-effective).

Either you are willing to implement data mining, machine learning solutions, or predictive analytics on the basis of CRM or ERP systems, it’s better to be aware of the advanced analytics tools, and be ready to apply them for innovation-driven company operations.

Analytics software is getting more and more applicable across most industries. For example, Gary King, the Director of Harvard Institute of Quantitative Science, noted the following in the interview with New York Times: ‘The march of quantification and analyses is made possible by enormous data sources, and it will sweep across academia, business, and government’.

Before applying any of the enumerated below advanced analytical tools, it’s worth either getting consulting service or evaluating on your own your business in accordance with the following milestones (recommended by the Forbes experts). Analyzing the following issues it’s possible to consider whether an enterprise is ready to become a data-driven one or not:

• creating a data-driven culture (motivate your staff to analyze numbers and facts while encountering the problem and looking for a solution);
• establishing KPIs (key performance indicators) for any problem to be solved;
• using self-service analytical tools to enable data accessibility (company policy or special software to let your employees get any answer when they need it immediately);
• analyze data to obtain deeper insights (e.g. learn data describing your customers to learn who’s your TA).

So, if you have ambitious objectives like Netflix had: to change your buyers’ habits, to make them act in a way profitable for you, let’s learn about analytical tools able to assist you and fasten the process of becoming a data-driven company.

Advanced analytical tools vary from company to company providing comprehensive solutions tailored to your business needs. Thus, Experian as a multinational consumer credit reporting company provides you with a number of advanced analytical tools to enhance consumer insights.

According to Experian vision the following analytical tools to enhance the decisions and deliver increased business performance: scoring models (modeling of the areas demanding assessment); custom modeling (in case your need to match client-specific metrics with model prediction); model validation (assess the performance of the current models you use).

As an example of the described and categorized tools ‘Attribute Toolbox’ by Experian can be presented. It’s a software enabling data access to the credit bureaus, supporting customizable options.
SAS supports your business experience with such analytical tools as data mining (software simplifies data preparation, creating better models considering the data gathered, putting the best models into service); statistical analyses, forecasting, text analytics.

Alongside the other market leaders, Innovecs is also an innovative and experienced partner to develop either big data solutions to benefit from data analyses or blockchain solutions to deal with big data amounts smartly and safely. Before continuing to speak about predictive analytics, big data, and blockchain expertise in advanced analytics, we’d like to mention the quote< given by Innovecs CEO, Alex Lutskiy, some years ago:

And now it could be said confidently that Blockchain R&D Center in Kyiv is working and our company is ready to collaborate on developing big data, predictive analytics software based on blockchain technology. You’re invited to learn more while reading further.

Predictive analytics software provides you with the opportunity to generate many high-quality forecasts with no need for human interventions as well as streamline your forecasting process.

Here is what happens when a business owner applies predictive analytical tools:

• personal bias opportunities are reduced (no chance for organizational politics or personal agendas to contaminate the forecast);
• more effective planning for future appeared (advanced analytics softwareenables testing what-if
• scenarios to determine the likely consequences, considering both planned and unplanned events).

It’s important to note that advanced analytics contributes additional value to forecasting, planning, and predicting counted and uncounted (risky) situations, and everything that’s happening while foreseeing is connected with big data amount processing. So, to perform well, it’s worth remembering about blockchain expertise as a helpful technique for advanced analytics arrangement.

In Cisco survey insights the following reasons to invest in advanced analytics are outlined: possibility to improve product (service) quality or performance; improving staff satisfaction and motivation as well as dealing with the retention rates effectively; increasing customer satisfaction; gain new revenue streams from existing products and services; getting more insights into customer behavior; improving profitability and margin.

As we see from enumerated above issues, all of them are practical ones and lead to enhancing the business operational part and boosting the profits. So, what techniques are able to apply advanced analytics in your business.

Here is something like ‘A Game Plan’ for advanced analytics implementations:

• senior-level managers should have a strong commitment to involving all the staff into innovative software utilizing (build centralized analytics company architecture);
• analytical data should be exposed to as many people in the company as possible because it’s not just the deal to collect and analyze, but to transmit it to the decision-makers at the right time;
• it’s critical to optimize investments into analytical tools (it’s worth making the full use of existing business intelligent systems rather than launching modern and new ones).

No matter what challenges enterprises come across, whether they stick to their strategic plan or roadmap is changed, there are many examples of advanced analytics usage and benefiting from predicting the company’s future.

In every industry, there are many companies having success with the use of advanced analytics (predictive analytics) software.

Thus, for example, in Tesla case study ‘1 million vehicle vision’ is presented. There it’s described that Elon Musk’s business achieved the goal of making 1 million electric cars due to applying advanced analytics in the manufacturing operations.

Their whole production process is divided into several key systems: MES (manufacturing execution system, which is a software for controlling all the assembling process); web-enabled QuickBase is used to track ongoing changes and form the analytical reports; they have an in-house app based on LabView for all the employees to know where necessary data is placed.
Company management outlined the following benefits from advanced analytical software application:

• clear production counts;
• quality defect tracking/analysis;
• root cause investigation possible;
• availability of statistical overview and forecasting.

One of the most frequent challenges while using advanced analytical software is visualizing and creating user-friendly platforms to make analyzed data easily accessible and understandable for employees.

Another car manufacturer, American Honda Motor Co., reports using SAS analytical solution to improve warranty claims and forecast demand for spare parts and maintenance services. Kendrick Kau, an assistant of Honda Advanced Analytics group, said that if we looked back ‘we performed only 1% of what we really forecast’.

Due to advanced analytical software, a great decrease in warranty expenses has been performed: suspicious warranty claims were checked and matched with the guidelines automatically to enable distinguishing cases, where a warranty repair is really needed.

99% accurate demand for spare parts and services as well as a great decrease in warranty repair cases, additionally, saved large amounts from the company budget.

Orlando Machado, Global Director of customer advanced analytics in ‘Aviva’ noted that they turned a huge number of data points about their clients into the knowing of company TA microsegments. This knowledge they used to personalize the customer experience, provide clients with helpful deals at the right time, and forecast which type of marketing campaign will work more efficiently.

Aviva reported advanced analytics contributed greatly to their brand strategy development and benefitting from predicting customers’ pains and gains map.

So, you see that machine learning solutions, big data processing tools, AI, blockchain, and other innovative techniques are used in advanced analytics to smooth enterprise operational work scope, and assist in building up cost-effective production, claims processing or marketing campaign arrangements.

Data mining, statistical analytics, blockchain solutions are ready to transform the way your business is run. They enable:

• effective risk management;
• KPI increase due to accurate demand forecasting;
• product innovations;
• driving additional profit streams due to insights generated by the advanced analysis;
• easing supply chain management.

A statement that ‘Advanced Analytics’ seems to be a powerful and necessary tool as well as an investment priority’ is a key takeaway summary. And if you decide on outsourcing advanced analytical software, just drop a line to Innovecs as a robust development partner.