6 team based best practices to multiple your analytic value

(Source:- ACL Blog)

I love seeing the usage of data analytics tools within organizations, but can’t help but see a huge opportunity being wasted by not expanding that beyond just a few experts in the department.

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Handing off Excel spreadsheets to others for analysis is not efficient in the long run as the experts will become the bottleneck as the demand for data analysis increases. Fortunately, I have witnessed successful enablement of team based analytics first-hand in quite a few organizations. Demonstrating that by taking a few additional steps the return in value far outweigh the extra time and investment.

Here are six common best practices we’ve learned from successful organizations to extend your analytics beyond the experts.

1. Make data analysis mandatory


The Board, oversight committee and executive management are looking to navigate the landscape of strategic risks; strategic risks often manifest as patterns in transactional data and if you are not analyzing the entire data set, you’re not providing risk assurance. Reviewing summary reports or sampling is not sufficient and not analyzing all of the data is no longer an option. Successful organizations have recognized this and have mandated data analysis in every project.

Executive management needs to set the tone for the organization by demanding that data analysis be incorporated into all projects — and if the team discovers that it is not possible for a project, they need to provide written explanation of what prevented this analysis along with suggestions on how it can be achieved in the future.

Once the organization knows that data analysis is mandatory, project planning will begin with the team looking for ways to incorporate data analysis rather than providing the common excuses that “it’s too difficult” or “we don’t have time.”


2. Harness the talent in your organization


It takes a bit of time to recognize the potential power of the data in your organization. For new users, it may seem overwhelming to determine where the data is stored and how to gain access to that data. You will need help from the experts to get you started.

There are probably already a lot of people in your organization that could help you get started. These people may include your IT staff, database administrators, ERP / business system process owners or existing ACL users. Even the end users entering the data into the system will have value to add as they know the context and business processes surrounding the data they enter. You could also look externally at the large ACL community of experts, such as the ACL User Forum. Or, you could consider hiring ACL consultants to get you started. You won’t need them all the time but it would be useful while you are beginning to work with a new system.

As you are building your expertise, ensure your staff have access to all of the great resources that are included within your ACL subscription, including:


3. Turbocharge your analysis by sharing


Data analysis typically requires a lot of creativity, exploration and sometimes trial and error. It can be full of interesting and challenging problems to solve. Many of these problems can be solved faster by involving more people with different perspectives and backgrounds.

Also consider Peer review, it is just as important as having someone else proofread your report. Messing up the wording in a report may be embarrassing; making a mistake in a calculation or an assumption about the data could be much worse. ACL Analytics makes this review easier through ACL Command Logs and table histories detailing the steps taken to create the results. ACL Analytics Exchange (AX) promotes this teamwork by providing a single location where the work can be performed, reviewed and saved.


4. Retain assets securely and learn from the feedback loop


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It’s always useful to document lessons learned while performing data analysis—from the minute details, like how a function works to a higher level, like what systems should be reviewed. These should all be written down and saved so that others can benefit from these experiences and learnings.

I’ve seen some great examples of data request documents from our successful customers. These documents not only start the process out correctly by clearly stating the purpose of the request, they are also maintained and updated throughout the project so it becomes a reference document the next time the team needs to access similar data.

Consider leveraging the information in your ACL command logs by copying commands key to your analysis into an ACL script. Even if you don’t think you’ll ever need to run that script in the future, a script is an excellent way to document the steps you performed. And by storing your scripts in AX, this ensures you have a provable, repeatable script for next year instead of losing it on an individual computer due to churn, rotation or computer upgrades.

To help organizations store and share this documentation, AX allows you to store additional documentation in the same location as your scripts and data tables. This provides an excellent way to organize your documentation, allowing others browsing your data and results to quickly see the relevant documentation.

As we have all seen, people shift roles and organizations. But when people move on, they take all their knowledge and skills with them. AX has built-in tools to help retain this knowledge within the organization by keeping work in a central location.


5. Repeat. Rinse. Reuse


Each project that involves data analysis will grow more information to make your team more efficient. Ensure you organize this information and make it available so that others can quickly and easily apply it to their current work. Use ACL Analytic Exchange to create a read-only library of tables, scripts and related documents that others can refer to and copy into their own projects.


6. Clone yourself by automating


As your team becomes more proficient with data analysis you will start to notice patterns of usage emerging. It could be a certain type of data file that you always refer to or maybe a specific report that is being produced at the start of each project to assist with planning. In any case, you will want to use scripts to automate these.

ACL Analytics Exchange makes this easy by allowing the scripts to be run on the server without affecting the local computer’s resources. You may find benefits from moving away from an ad-hoc data pull from your systems to a nightly download, since it will be more efficient. The data will be faster to access from your AX server and your IT department will thank you for not pulling data from their production system during peak times. If you’re looking for examples on how to create scripts for your AX server, there are over a 150 scripts available on ACL ScriptHub.

Conclusion

The journey to building data analysis is one that never ends, there will always be new things to learn and new challenges. But it can be an exciting and rewarding journey. Implementing some or all of these techniques will help ensure that this journey has fewer bumps and becomes easier and easier with time.

 

 

 

Thursday, June 25, 2015 In: Hot Topics Comments (None)

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