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Smarter Analytics: Less Work, Bigger Impact

1–2 minutes

A major issue in analytics is the ongoing feud between customers and analysts. Customers often struggle to define their needs or interpret the results, while analysts may miss key details of the problem or fail to present findings in a clear, accessible way. This back-and-forth can lead to rising costs, mounting frustration, and missed opportunities to gain real value from analytics.

The analytics cycle between the customer who keeps getting results but they don't know what they mean or what to do next and the analyst who keeps providing further results with greater detail and complexity.

Challenge with Analytics

The gap between customers and analysts comes from the distinct roles they play in problem solution. While analysts aim to deliver depth and detail, customers desire clear, actionable results.

Two major issues with analytics. First, they are excessive in that a lot of work gets done and often leads to overwhelming output. What is needed is to only do what is required to get the desired results. Second, they are inconclusive with even large amounts of output being unclear and failing to solve the problem. What is needed is the delivery of output that conclusively solves the problem.

Conventional Analytics Process

The conventional analytics process uses a bottom-up approach, which ensures thorough and objective results. However, this can quickly expand the scope of work and lead to many possible interpretations by the customer. While skilled analysts can narrow the focus, the process remains more of an art than a clearly defined method.

With the conventional analytics process the scope of work can grow very quickly and many possible actions can be taken. In-depth problem analysis is followed by extensive data gathering. Different insights can be obtained from the same data. Insights can be tailored into unique reports for the customer. Reports can result in many actions depending on how they're understood.

The scope of work can quickly grow due to the complexity of each stage in the process. Since actions typically fall outside the analyst’s responsibilities, customer interpretation can risk undermining the entire analysis.

Conventional analytics process involves extensive analysis that may quickly increase the scope and lead to a diverse range of outputs.

Advanata Process

Advanata uses a top-down approach designed to effectively solve most real-world analytics problems. This method replaces the typical one-to-many complexity with a streamlined one-to-one process, offering a clear, objective framework for building practical and effective analytics solutions.

The Advanata process greatly reduces the scope of work with only specific actions are to be taken. Starting from a known action means only a single report is needed. report needs a set amount of insights. Required data is therefore limited and alternatives can also be utilized.

This approach keeps the scope of work controlled and also eliminates the need for extensive upfront problem analysis. It also accounts for the customer’s actions, making the analysis results easy to use and ensuring accurate implementation.

Advanata process starts with the desired action, works backward to manage the scope and guarantees a solution.

Maximizing Results Without the Waste

Clearly defining the roles of customers, analysts, and even machines is essential for effectively solving analytics problems. Advanata’s robust, user-friendly process accelerates result generation, enhances usability, and helps unlock the full value of analytics.

The Advanata process starts with the customer providing problem structure, then the analyst refines problem parameters and finally the machine calculates problem solution.

Tell us in the comments what other issues make analytics harder to use?

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