Problems in business are not uncommon. This is usually because as the business grows, it changes, and external factors also change. However, proper definition of problems will mean that they become easier to solve. Augmented analytics has a huge role to play in solving business issues. Mainly because data shows everything and as such, problematic areas are easier to identify, rectify and monitor. According to HISCOX, Forbes, and the Lean Methods Group.
There are 5 main problems nearly all businesses face. They are
- Monitoring Performance
- Information Overload
- Problem Solving and Risk Management.
Here is how augmented analytics can solve these issues
According to a survey conducted by Computer World, IT jobs will have increased by 22% by 2020. However, this will not automatically translate into enterprises’ better understanding of technology. As it is, most companies rely solely on their data scientists and IT department to take care of data and its subsequent governance. However, according to the Gartner Report, the number of citizen data scientists will have surpassed that of expert data scientists by 2020. It, therefore, makes sense for an organization to leverage this and get as many CDS as possible under their roof. CDS numbers have risen because of the way Augmented Analytics handles data. Since augmented analytics uses Natural Language Generation (NLG), the system is able to generate reports and narratives in an easy to understand human language. Natural Language Processing (NLP) is software that produces or interprets human language. The four major types of NLP are NLG, Speech synthesis, Natural Language Understanding, and speech recognition. With these tools, data can be collaborated and shared with those who need it. turning nearly all staff into CDS. As such, there will be quicker and better understanding of data, meaning improved decision making for the company.
Traditionally, day to day business decisions have been based on contingency. That is probability and probability distribution. This means that they go with estimates and predicted numbers. In short, what they would hope to happen. However, there is a better way. With augmented analytics, Artificial Intelligence (AI) and Machine Learning algorithms can work out all possible scenarios and give you the chance to identify the best path for the future. Data Scientists together with machine learning give power to CDS and business users to automatically find, narrate and visualize predictions, expectation and relevant findings. So not only does augmented analytics help removing uncertainty, it mitigates the risk of missing out on an insight with manual exploration.
- Monitoring Performance
In order for a company to know whether it's moving forward, goals must be set and monitored closely. Key Performance Indicators (KPI's) are critical in measuring how effective companies are at achieving their key business goals. So, when a company doesn’t have a way to monitor these things, improving on certain aspects of the business becomes improbable. Augmented analytics changes the game here because it allows for KPIs to be monitored, analyzed, presented and shared. This allows for management to have a clearer picture of performance and also gain insight into the place that needs rectifying.
- Information overload
Information is the lifeline of businesses. Although some companies struggle to find accurate information, its overload is usually a more pressing issue. Information overload means that you are flooded with information which you can’t decipher and as such it becomes useless to you. Augmented Data Discovery and Augmented Analytics go through all data speedily detecting correlations, patterns, and outliers. Then, it only presents the relevant information in a simple way which everyone can understand. This means that only useful information gets to the business users, CDS, and specialist DS.
- Problem-solving and risk management
Wrong decisions can have a cascade of unwanted consequences on a business. So, how can a business know whether it made the right decisions? Machine learning algorithms have something called “gradient descent,” which improves a solution gradually accounting for changing factors in the business. This way, Machine Learning can help in monitoring flowing data and report irregularities or inefficiencies. This also means risk will be better mitigated.
Conclusion: Problems businesses face will always be there regardless of size or success. By identifying the five biggest alleys, you can better brace your business for what’s to come. By embracing technology, we make better business decisions which in turn translate to success and profit.