Reporting, some folks refer to it as a necessary evil, and others call it a fundamental tool for business. No matter what your thoughts are on the matter, if you are reading this, it is because your reporting efforts are taking too much time, costing too much money, or are getting too complex. Hence, you have decided to look into efficient alternatives to make your organization’s reporting efforts easier. You may not know where to start or what to do, but you are not alone.
Part of my responsibilities in my current role is to help surpass current operational efficiency while contributing to the organization’s overall commitment to our customer needs and goals. Our reporting mission is not to provide a one-size-fits-all type of report but one that is carefully customized to each of our clients. This means that I am responsible for designing, developing, and testing our report automation efforts for every account that we manage.
Since I have already started with this project, I decided to share a some of my experiences in the hopes that they either guide you or help you save time. The main thing you must know is that you do not need a massive budget to make reporting automation work. You can make your automated reports as elaborate or as simple as you wish, and your outcome can be a very cool dashboard or a very insightful Excel file. Therefore, because the possibilities are endless, I decided to make these tips as general as possible while sometimes leveraging two of my daily go-to data sources to illustrate some of my points. Without further ado, these are the three key things you should consider:
- What are you trying to accomplish?
The design of your automated report is going to be directly proportional to the desired goal you wish to accomplish. There are several approaches to pull data, analyze it, and present it. Thus, an automated report whose goal is to minimize reporting turnaround times could look and interact substantially differently than one that aims to maximize accuracy or that will interact as a dashboard-like output. Therefore, in order to build the solution that fit your needs, you and your team need to ask: “What are we trying to accomplish? How are we measuring success?”
The most common answers to this question fall within the following verticals:
- Turnaround Efficiency
- Accuracy
- Compliance & Monitoring of KPIs
- Data Integration
Moreover, the more granular these answers are, the more effortless it will be to develop an efficient solution. It is important to understand that apart from the goal, a clear understanding of all team members and stakeholders of how the final output should look, feel, display, etc. will also be of tremendous value in the development stage.
- Have you considered how business requirements may impact your report in the future?
Business is ever changing and, consequently, reporting is as well. When making the design, potential short-term and long-term changes must be considered and consulting with someone who has prior experience with the particular stakeholder or industry may be very helpful to get a sense of how regularly and what type of changes are usually experienced. For instance, in the PPC space, stakeholders often shift their strategies, which entails launching, pausing, and replacing campaigns, ad groups, copy, and search terms – this can happen at any given point, and thus, reports need to be modified to display the active data. Proactively understanding changing business environments and integrating these into the foundational design of an automated report provide you with the flexibility and dynamism to adapt to unforeseen changes.
There is always going to be an unavoidable instance when new development efforts will have to take place to cater to the evolving needs in question. In prior opportunities, even with the most thorough design and use-case scenario preparation, I have witnessed how new business needs and business questions mean almost an entirely new deployment of the reporting infrastructure. Therefore, I always recommend thoroughly documenting the design process, specifically, any unique features or needs that have to be implemented, so that when a request for a major redesign comes in, you and your team will be able to leverage what you or someone else has done in the past. This can contribute to significant time savings and a much more tailored solution.
Keep in mind that with the documentation process, you should be able to respond to these questions for any step of your report:
- Are all steps documented in full detail? If we were to revisit this design in six months, would we be able to remember where we left off?
- Is there any particular step that is particular to this report? If so, have we documented how we overcame this challenge?
- Is there another alternative to get the same result? If there is, have we tested it to determine which one may be better?
- What tests can we carry out to ensure the design works?
- After the data analysis, are there any gaps or questions left unanswered? (If your answer is yes, you should revisit the drawing board and do the necessary to close the gaps.)
- Could you explain your design with a story? (This will help you see if your data relationship makes sense.)
- Have you looked into the quality, structure, complexities, and limitations of your data source(s)?
According to Google Trends, over the past five years, the number of searches for “Data Quality”, “Big Data”, and “Data Cleansing” have increased by 50% year over year (YoY). We all have heard about the power and uses that data can have in the workplace, social media, sports, human behavior analysis, etc. Most of us have seen some type of dashboard and even heard of visualization tools such as Tableau or Google Data Studio. However, not everyone knows the work that it takes to gather the data to use these tools properly.
One of the reasons for this is that every company has its own strategy and design for their OLAP cubes, databases, overall data sources, etc. Another reason is that none of the processes that happen behind the scenes are as engaging as a dashboard. Nevertheless, if you are looking to eventually have or maximize the power of these tools, you must not ignore your data sources.
To illustrate my point, let’s talk about two data sources that our reports tend to leverage: Google Analytics and Google AdWords. While in essence, these two are complimentary platforms and were built by the same company, they do not operate equally in a number of different scenarios, and each presents its own unique challenges. Thus, if you were asked to build an automated report that used both of these sources to show a client how his or her PPC and SEO efforts were performing, how would you be able to seamlessly integrate both of them for your stakeholder?
You have to create or leverage a data relationship. There are several ways to make this work, but I recommend using the following questions as a general guideline to help you determine your next steps:
- Are the data sources inclusive? If so, how are they linked together?
- What metrics are you trying to report on? Is there a possibility that both sources contain the same metric with similar or different results? If they are different, which one will you choose?
- Are there any primary/unique ids that you could leverage to get more granular attribution? (I highly discourage anyone from using alphabetic fields as IDs to create data relationships.)
- Are there any fields that only one of the sources has that could impact the quality or accuracy of your results?
- How will you test the accuracy of the information? (This is particularly important since tools, like Google Adwords, change throughout the day and can generally present results that differ by up to 5%, depending on when you pull the data.)
- Is there any manual entry involved with the process? What steps can you take to minimize human error?
Once you are able to determine the answers to these questions, you will be able to design an action plan that minimizes the vulnerabilities of each source. Finally, in some instances, you will find no relationships in the data, and you must find a way to create one. For instance, if you added to your report additional information from an organic rankings tool and/or social media performance, there will most likely not be a link between these sources and Google Adwords or Analytics. If you find yourself in this situation, you will then have to build a layer where you integrate these sources as you see fit, keeping in mind that, although there is no nexus amongst themselves, they all still are results that pertain to the same client or stakeholder.
I hope that you are able to leverage this information into your reporting automation efforts. From personal experience, being prepared to address these questions before diving into a report automation project will help you maximize the efforts invested, create a better final product, and facilitate management discussions so that you can move seamlessly with your process. Remember that you should always have a defined goal, be able to document and explain your design considering an ever-changing business environment, and finally understand the peculiarities of the sources you are leveraging for the report.
Happy Reporting!
