Adoption of Digital Technologies for Finance Office

The decision support system plays a very important part for any organization, especially when it comes to finance the outcomes are often direct and measurable. 

As per Gartner, 80% of finance leaders agree finance must significantly accelerate the adoption of digital technologies, such as Analytics, Automation etc. to support the business by 2025. A survey of 400 finance leaders shows a broad expansion of the technology toolkit being used to drive efficiency, agility and productivity. And these technology need to be complimentary to each other to bring out the full potential. 

Pic Credit - Gartner (April 2022)

Now the question is how to build the capability for the adoption of digital technologies? 

As per MIT Sloan Management Review the digital maturity depends on 7 parameters,

1. Strategic use of (Advanced) Analytics 
2. Model Explainability
3. Cross-Functional Data Collaboration
4. Analytics Skill
5. Exploration and Experimentation
6. Data Driven Culture
7. Digital Inclusivity

And the following questionnaire helps to evaluate the maturity. Calculate the average score for each of the 7 parameters.

• Score ⫺ 4 : Leading in digital capability
• Score between 3 to 4 : Developing digital capability
• Score ⫹ 3 : Lagging in digital capability

Pic Credit - MIT Sloan Management Review

This metric will help the CFO to assess the Finance Office's digital maturity over time and can track current state and the progress over time. 

References: 

• How Digitally Mature Is Your Finance Office? by Kristof Stouthuysen, published in MIT Sloan Management Review - Summer 2023
• “Gartner Survey Shows CFOs Turning to Process Mining to Drive Better Returns From RPA,” - Gartner, April 27, 2022

Evolution of BI & the Future

Business Intelligence has come a long way from MIS reports to prebuilt dashboards to self-service to Chatbots. And along with this the end users have also evolved from mere consumers to explorers to data hungry power users.  

We can divide it into 3 periods,

1. Initial Era (1990 - 2005) - This was the beginning of the BI. There were static MIS reports and the end users were consumers who were heavily dependent on the IT team. 
2. Middle Era (2005 - 2020) - This was the middle ages, where BI was synonymous to interactive Dashboards with slice and dice capabilities. The end users have also evolved from consumers to explorers, who used features like slicers, drill down / through to envision different scenarios of the data.  
3. Modern Era (2020 onwards) - In the recent times there have been massive changes., The data hungry workforce wants more than dashboards, they want empowerment 💪, to create their own insights, or in other words self-service capability. With that comes SaaS models and cloud hosted platforms, which give flexibility of scale up and scale out with minimal effort. 

As per leading Marker Researchers, 

• Clients no longer concentrate on which BI platform provides better data visualization, dashboards, or OLAP (“slice and dice”) functionality; rather they are prioritizing platforms that are: 
• Native to their preferred hyperscaler platform
• Seamlessly integrate with business applications
• Built on API-first architecture
• In an ideal BI environment, 80% of all BI requirements should be carried out by the business users themselves 

But what lies ahead? What is beyond Self-Service? 

With introduction of AI, ML and other technology evolutions, the power users will no longer have create their own reports by themselves. The BI tools will be smart enough to understand their requirement and built reports for them. May be we can call it Autonomous Self-Service (like Autonomous cars 🚗) ..... 😇

In fact, it is no longer a thing of future. Let's take the following examples,

• Oracle Synopsis - It is the Mobile Analytics App that lets you quickly open and interact with spreadsheets and business data in a visual and intuitive way, while you're on the go.

It is a standalone mobile based BI reporting tool which takes excel as data source, available in both Android and IOS. Oracle Synopsis is very intuitive in nature and the end user do not need any technical training to use it or create and share reports. This app is ideal for the Travelling Salesmen, Medical Representatives, PMOs who are always on the go and have the need to share reports (mainly excel based) 24 x 7.

• Oracle Lens - It is also a mobile based tool, which can scan any scan any tabular data using mobile camera and create insights instantaneously. 

• ThoughtSpot Search - It helps Self-Service analysis using NLP. In the search bar the users can type the analysis / insight they are interested in, and the reports get generated. Therefore with minimal knowledge self-service can be performed.

• Power BI Insights - It creates auto insights from the data with minimal intervention. 

And the list goes on and on. 

That leads us to the next question about our future, what is going to happen to us the BI Consultants / Developers? Are we also get redundant and obsolete like our little Rexy 🦖(can't help it my son is a big fan of Rexy ... 😋) ?

To my opinion, we are not going to get extinct at least for now. However, with the advent of every evolution and modernization the old roles get replaced by new more advanced roles. I think the role of dashboard developer is going to get reduced as self-service becomes easier, smart and automated. But the backend structure and governance will become more important, the following activities would become more and more important. 

• Advisory - Helping clients and end users choose the right tools as they are going to get spoilt by choices. The set of tools must fulfil the requirement and complement the organization's long and short term technology roadmap.
• Designing BI Architecture - As BI tools becoming more advanced and complex and there are significant number of integration opportunities both upstream and downstream. Therefore designing a robust, scalable architecture becomes more important to support all the smart things on top.  
• Designing Data Mart - Somethings don't change, a solid scalable data model (Normalized, Denormalized, Star, Snowflake) is the foundation of the BI solution. And thanks to Mr. Ralph Kimball and Mr. Bill Inmon, there is enough of confusion already on which approach to choose, a top down or a bottom up.  
• Defining Metadata (Metrix, Dimensions, Hierarchies) - Once the ground work is done, the calculations and the logics need to be defined, so that the automation can use them create the answers / analysis users seek. 
• Governance - With empowerment comes governance. As more and more user are empowered the create their own analysis, that would lead to more and more confusion about the version of truth. To maintain single version of truth and standard across the organization, a governance process is very important. There has to be a Heimdall protecting the Bifröst. 

Working with Power BI Bookmarks - Cross filtering

Unlike few other data visualization tools such as Tableau or Qlik, for Power BI the cross filtering interaction across reports are limited to a single page, the only alternative being Drill Through, however that requires multiple clicks. I was trying to find out a way to recreate similar experience of cross filtering interaction across reports in Power BI. 

Let me first show the end output, I have created a simple sales dashboard using some dummy data. 

There are two pages Summary and Details,

And the interaction is present between the two pages. To illustrate that, let me select Product Category 'Furniture' from the top, and as expected other reports are showing for 'Furniture' only. 

Now, if I go to Details, it is also showing for 'Furniture' only. 

Let us try to explore the technicalities. I initially thought, this would be fairly simple using Bookmarks and Selections. I have created a single page with all the visuals, and have added a small empty section at the bottom.  

Next I have performed 3 steps,

1. Enabled the Bookmark and Selection view
2. Hidden the Details table
3. Created a bookmark called Summary

The same way I have hidden other charts to create another bookmark called Details.

Next I have added a Bookmark Button at the bottom and made it appear like tabs. And point to be remembered everything is in a single page. 

And I thought this would be it, but to my surprise I found out that cross filtering interaction is not working between 2 bookmarks also 👺👿💀. I have to find a work around to overcome this, and make it appear like cross filtering interaction across tabs. 

To overcome this I have added a white shape, and instead of hiding / unhiding the Details table I am hiding / unhiding this white shape in the bookmarks.

So essentially my Details table is always visible it is the shape that is acting as a curtain. 

And that does the magic of deception, it appears that we are cross filtering across two pages.

However, to emphasis this is not a full proof solution just a work around.