Accelerating Analytics – United by a Cause

Business stakeholders increasingly rely on business analytics to make key decisions. Often, urgent business needs require new information to be available at a pace that is difficult to achieve leveraging a more traditional business intelligence stack. The Covid-19 Pandemic has driven this urgent need for many of our clients. These needs include monitoring the effect of the pandemic on their business and measuring the change to their business as more traffic is driven to different channels. Leveraging modern visualization technologies and an accelerated, iterative process can often produce timely, new analytics for business stakeholders with some reasonable tradeoffs.

The Challenge of Traditional Platforms

Traditional platforms typically optimize for quality, consistency and predictability of structure which is usually achieved via complex transformations from source data, investments in automation and data-quality processes to achieve these goals. These optimizations add a lot of value in the long-term but tend to take a significant investment of time and resources up front to achieve. The lead time required to add new data sources and expose data for business stakeholders to consume and analyze using a traditional stack often fails to meet the requested timelines.

A Potential Solution

Today’s visualization technologies, such as Power BI and Tableau, can directly read source data, perform basic data transformations, calculate metrics, refresh automatically and render visualizations of the information for stakeholders. In many situations, these tools can achieve much of the functionality of the traditional stack as described above albeit with some key tradeoffs. If getting your business stakeholders the information they need at the speed that they need it is your top priority and you understand and can tolerate the tradeoffs, this approach can work for you.

4 Keys to Success

The right teams using the right tools the right way can produce dramatic results. The following factors can set your team up for success:

1. Urgent business need – for many of our clients, COVID-19 has created the need for analytics that cannot wait for the traditional approaches to provide visibility.  What urgent business needs exist in your organization?
2. Agile process – An Agile approach will increase speed to value, reduce complexity, lower risk and offer project transparency. The faster the business can see results, the faster they can improve decision making. The Agile approach also provides leadership and project sponsors near continuous demonstrations of progress through data visualization tools confirming that the project is on the right track.
3. Engaged Sponsor – Everyone knows an effective executive sponsor is critical to the success of any project. With a data visualization project, success can be almost guaranteed if the executive sponsor is also an end user of the solution and is receiving most of the program's benefits.
4. The Right Team – Rapid delivery of complex visualization solutions requires the right team. In real life, we often observe teams that are basically formed with people who happen to be available at the moment of the request.  Who are the right people for an analytics project? The team must have a good mix of business knowledge, technical skills and the ability to design visualizations that speak to the end users. The mix of roles often includes a data architect with business and technical knowledge, source system subject matter expertise, a hands-on BI architect with technical knowledge and an engaged business partner to enable an analytics team’s success. 

Things to Consider

Visualization tools do a lot of things well but they are nota replacement for traditional analytics platforms. Visualization tools are focused primarily on rapid results and therefore can exacerbate some long-term challenges that traditional platforms address well. Below are some of the challenges:

1. Single Source of Truth – This approach can exacerbate "single source of truth" challenges related to metric calculation. Metrics are executed at run time on a report or dashboard with the results not persisted for reuse.
2. Curated Data – Perfect is the enemy of good enough in these solutions. If perfect data is needed this may not be the approach. This type of solution goes from the developer to UAT and into use without rigorous quality assurance.
3. Advanced transformation - The ability to apply advance data preparation transformation that is persisted and reused is limited. This includes transformations such as aligning master data, history tracking.
4. Automation –There may be times there are manual steps to refresh and publish your data until you have fully automated solution from end to end.

Over time your analytics environment may evolve to necessitate a more complex, traditional analytics platform as described above. If the core business requirements, KPIs, or visualization flows remain constant, you may be able to evolve the underlying solution to a more traditional model that addresses the challenges above while maintaining the front-end analytics that users have grown to love. Often these approaches work in parallel with the visualization tool providing rapid results and the traditional platform following over time with improvements to quality ,automation and overall availability of the data.

Delivering business value quickly has always been important. Events such as COVID-19 made that even more important for many businesses. Whether it is COVID-19 or some other compelling event that is driving your business needs, with the right team, engaged sponsors and an agile approach leveraging today’s visualization technologies will reduce the time to achieve business value. Starting this approach today will ensure your organization is able to rapidly adapt and quickly harness the power of data visualization.

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