How Data Automation is Solving Everyday Problems

Results for the Research Making Decision Using Data. What are the top pains customers are facing around making informed decision? 1. The lack and quality of the source data.rn2. The ability to generate meaningful insights from big data, don’t have the ability to articulate what they need to see to make informed decisions. (For info about big data - go here - https://www.oqlis.com/big-data/) 3. The complexity of setting up analytics tools to gain insights, and the amount of the work or time it is required to skill up business users to self-service. The default is to export data from databases and manipulate using excel.rn4. Asking the right questions about the data and what needs to be delivered, people have not defined what they need to know or what needs to be measured, the data is only part of answering the questions. rn5. Using a baseline to prove improvement for using data as a way to reduce costs / add value.rn6. Access to informationrn7. Getting the right or correct data, to make the right decisions. How the data is interpreted or presented.rn8. Your data is not telling you a story.rn9. Data must be in real time.rn10. Deep diving into numerous reports, customers need a dashboard with a birds eye view to make informed decisionsrn11. Collection of data from multiple sources (data input is not the issue; it is getting the relevant expertise from the relevant departments together that is the issue)rn12. Getting the relevant skills and expertise to formulate what needs to be done next, the manpower requirements and data segregation that take place to make a decision.rn13. Because of a silo approach that is adopted in businesses, the decision process is hampered by lack of visibility and makes decision-making time consumingrn14. The fact that data resides in various systems, customers want to have one place to interrogate data where the UI and UX is consistent (integrated solution). Discrepancy between data sets causes friction rn15. Very difficult to make informed decisions if you have a lack of understanding of your objectives and how to measure these objectives. The customer does not understand what they need to achieve or what they need to do on a daily basis with data. rn16. Discover your data, to find the gems and diamonds of insights. Have the ability to convert in a short time frame and make it easy to people that are not experts. (View the leader among Data Automation Companies here rnhttps://www.oqlis.com/data-automation/) What are the items that frustrate you (or your customers) at the moment that you wish you could solve using data? 1. Not knowing the integrity and quality of data. rn2. No insights when the data transaction have not been received or data source or data stream is not operational (data reliability)rn3. Standardization of analytics in a way that it can be explained, with some flexibility for users to self- service.rn4. Consistency of data presented to customer, in a way that can be understood.rn5. Availability of historic data or data sets, knowing what data and structure should be stored to add value at a later stagern6. Accessibility of data that can be explored in a simple and intuitive way, where a normal business user can find insights without serious data skills. rn7. Sitting with disparate systems or information that is held within certain individuals, and trying to find the information from the stored within various sources rn8. The time it takes to get information or meaningful results and (or) tangible outcomesrn9. The technical team does not store the data in the correct way that can be explored at a later time when require – Disconnect between how data is stored and the interpretation of data when required.rn10. Understanding the area in the business that would be problematic in the future, when the situation arises it is too late. Predictive problem solving. (Predictive cash flow management, predictive sales forecastingrn11. Comprehensively of graphs and the explainability.rn12. Too much human intervention, it is one thing to have data but it is another thing to interpret the data that it supports decision making. In addition, there is not enough time to get meaningful results.rn13. Spending too much time on monotonous tasks, meetings and emails.rn14. Inaccurate and incomplete data, the data does make sense. To know what the condition of the data.rn15. Not fast enough, do not get answers quick enoughrn16. Value of graphs with dashboards for comprehension compared to columellar reportsrn17. Historical data that can predict and extrapolate into the future (You might be interested in Artificial Intelligence https://www.oqlis.com/artificial-intelligence/) So, walk me through what happens when you experience pains and or frustrations using data. 1. Because the data is not easily accessible, or the team that does the analytics is currently busy with more valuable tasks, questions and insights are just never obtainedrn2. So frustrated, lose interest in the potential insights, and not answer the questionrn3. It takes so long to get insights, that by the time the insights are generated the question or answer is no longer relevant.rn4. Need to understand what is going to happen in the future, if this is not known the consequences can be financially crippling.rn5. Waste of time, could be using the time for more strategic items.rn6. It takes too much time to proceed / solve - Saving time on a daily basis.rn7. When decision can’t be made due to data discrepancies, there is a root cause analysis process that needs to be followed which is very time consuming. This is a painful and laborious process that incorporates many parts of the business.rn8. The solution becomes useless / unusable rnWhat do you think is the ideal solution to getting the most out of data decision making process? 1. A platform that is reliable and consistent in what it does for customersrn2. Analytics needs the flexibility to allow business users to do basic analytics without the need for having a PHD to make daily decisionsrn3. Provide useful business drivers as outputs rn4. Normalises the data, investment in a good data design, getting the data into something that is useable.rn5. Interface that provides ease of use to something similar to excel but with the power of managing large data, with some fundamental templates in a standardised way.rn6. Have all your information coming into a centralised repository, making sure it is organised in a certain way, and once all the processes are automated have access to the information using a tool like OQLIS. Making decision or managing by exceptions.rn7. Having access to information at the click of a button, As a director of a company making decision based on red flags and signals on a graph.rn8. A system that stores the data in a manipulated or prepared way so that can be easily explored by customers.rn9. A simple system that has a predefined data and time factors that can present the data in a simple dropdown way that users can explore their data and gain confidence in the validity thereof.rn10. Managing predictive analytics is complicated, so a system that manages the entire process. Managing the models, the algorithms, the models in production and the infrastructure costs as things change. Addressing the infrastructure and time requirements for deployment and integration.rn11. Simplified visualisation that tell a story, that highlights exception/event management to better make decisions. So if we can resolve these pains and frustration for your customers, would you think they would find this beneficial for your business? 1. Customer would be more driven by data driven decisions versus distinctive decisions.rn2. Speed, reliability, consistency rn3. Quicker deployment and scalability can enable faster market penetrationrn4. Lead time to making decisions. rn5. Putting the customer in the lead against competitors.rn6. Less frustrations.rn7. Manage the entire predictive cycle has a financial benefit to customers – “something in hindsight, is going to be something in foresight”rn8. Supply existing customers with predictive insights will have a huge impact on engagement, retention and employee performance.rn9. Have more time to meet business objectives.rn10. Data maturity.rn11. To be ahead of the curve of competitor and to provide customers with effective way to make effective and insightful decisions. Providing a place where data will assist customers a place to tell their story in an effective way.rn12. System that provides a non-technical person with the ability to diagnose a problem and indicates what to do