Central Finance Exchange Customer Survey: Key Business Objectives and Priorities of leading SAP Central Finance Customers

This past June, TruQua, in collaboration with Magnitude SourceConnect and SAP, hosted the annual SAP Central Finance Exchange event in New York City at SAP Hudson Yards office.

This year’s event brought together 40 Finance and IT professionals representing 11 different companies and provided the opportunity for these individuals to connect, listen, learn, and share experiences, related to their Central Finance deployments and planned innovations.

Leading up to the Central Finance Exchange, SAP conducted a survey to better understand the audience’s current landscape, business priorities, and objectives for Central Finance to help drive the discussions at the event.

SAP Central Finance Exchange Company Profiles
At this year’s event 6 industries were represented, with Consumer Goods/Appliances (33%) representing the largest portion. Organization sizes varied from 0 – 25,000 employees (33%) to more than 100,000 employees (40%).

While most of the attendees were based in the North American region, 89% of those surveyed identified themselves as being a part of global organizations.

All of the projects (100%) are integrating non-SAP systems as part of their initiative, with JD Edwards and Oracle being highlighted as the most prominent non-SAP systems.

Central Finance Business Priorities and Project Goals
Respondents shared their business priorities, which included the key driving factors of Speed & Efficiency (100%), Transparency & Accountability (78%), Operating Costs & Productivity (56%), Strategy & Planning to Execution (30%), Revenue (11%), and Service Level (11%).

As it relates to Central Finance goals, the top performers included Application/System Consolidation (78%) Finance/Business Transformation (78%), Central Finance as a Stepping Stone to S/4HANA (67%), Application/System Consolidation (57%), and Shared Services Process Executions (56%).

In addition, Central Finance business objectives that ranked the highest among the group included Cross-Entity Reporting, Single Source of Truth (100%), Process Standardization (78%) and an Advanced Finance Data Model (100%).

Live and Targeted Solutions
As it relates to SAP Central Finance live and targeted solutions, Intercompany Reconciliation was listed as a planned solution above the rest (78%). Financial/Management Reporting, Business Analytics (33%) was the most popular live solutions. From there Accounts Receivables/Accounts Payable (22%), Real-time Consolidation/Group Close (22%), and Financial Accounting/Entity Close (22%) were evenly distributed.

This year’s Central Finance Exchange proved to be a wonderful opportunity for customers to connect and share challenges, successes, and ideas among their peers. TruQua and Magnitude will be sponsoring the European version of this event this September in Berlin, so we’re looking forward to gaining even more insights!

For the latest information and updates on SAP Central Finance, contact the TruQua team today at info@truqua.com.

New Perspective Blog Series: Achieving Success in Recruiting and Talent Development

Welcome to TruQua’s New Perspectives blog series.  This blog series provides a platform for our consultants to share their perspectives, insights, and experiences on emerging technologies such as SAP HANA and SAP Analytics Cloud. 

As this is our fifth installment of New Perspectives, we are mixing it up a bit. Today we are not speaking with a Consultant, but instead with a critical member of our management team – Stephanie Hettrich. Stephanie is the Director of Recruitment for TruQua and has been incredibly successful in her 20 years of experience in recruiting, talent development, marketing, and business development. This should be an interesting read for SAP customers, as well as current and prospective consultants.


Perspective 1:
Cultivating a Diverse Team

JS Irick:  As anyone who has built something more complex than an Ikea dresser knows, diversity leads to stronger organizations. The ability to draw on different experiences and different skill sets leads to more flexibility and better overall project results than homogeneous teams can provide. On any large enterprise IT project, there is at a minimum the need for expertise in the customer’s business area, computer science, accounting, finance, and mathematics.

Stephanie, I am consistently impressed with your ability to recruit diverse talent, both in terms of background and cultural origin. How do you go about identifying this talent, and what do you do to ensure a good corporate culture fit? I’d be especially interested in any insights you have on foreign or neuro-atypical talent.                

Stephanie Hettrich: Resumes are the most common currency for any job applicant trying to get their foot in the door with hiring managers. I personally think what a person portrays on paper is often misrepresentative of what he/she really brings to the table, or worse, misaligned with other skills that can’t translate on a resume. I tend to zero in on the summary applicants write about themselves and pay less attention to the ensuing details. The personal story people can write reveals far more than chronological job history descriptions. If the hard skills match the role at hand and the resume is succinct (one-page resumes with a smart layout and key points beat endless pages of data any day!), the next key qualifier is how well they engage with me during the recruiting process: Are they responsive and timely in communications? Can they write professional emails? Is their level of enthusiasm and drive palpable in communications leading up to their interview? Everything communicates, and I value this process as a key qualifier when searching for new “unknown” talent.

TruQua is also extremely well connected in the SAP world. LinkedIn plays a key role in revealing who knows whom, and their respective connection paths. This is a driving search criterium for me and one I rely on quite a bit. I don’t use any other search platform outside of LinkedIn as it occupies a reign supreme for professional recruiters, but more importantly because the best talent is on LinkedIn whether they’re actively looking for new opportunities or not. Some of the best finds are the result of passive searches on LinkedIn, where I can leverage connections with our current employees. Additionally, as a top social media platform, LinkedIn also allows for wide-ranging searches across the globe, hence allowing us to find top international talent.

The pre-screener is the first one-on-one interaction between applicants and TruQua. I like to start off this meeting by letting candidates know I am looking to get to know them better, as well as answer any questions they may have. Allowing recruits to feel comfortable usually reveals who they really are and avoids perfunctory, rehearsed answers. Once nerves are calm and I make candidates feel comfortable, I like to dive into behavioral questions that allow me to best evaluate culture fit along with our internal motto of “Smart Driven Nice.” Here I’m assessing EQ more than anything else; not hard skills as this is further drilled down during technical interviews. Also, we believe at TruQua that “culture eats strategy for lunch” so this is a pre-requisite to moving on to the next level. At this point, my goal is to glean more out of the individual than what appears on his/her resume. Some of the questions I ask for example are:

Gives us a piece of feedback you recently received from your boss that depicts something about you we may not read on your resume.

Describe a good hustle you went through at work or in your own life.

What do you consider the nicest skill you possess?

As to diversity, no doubt it enriches a company’s culture and skills across the board. As an intimate firm, we represent 12 countries with employees from Mexico, Brazil, China, Korea, Rwanda, South Africa, Argentina, France, India, Lithuania, Moldova, Taiwan. This rich mix of cultures is rare for in any company, let alone a small start-up like TruQua.

We also take a very holistic approach to our recruiting and talent development to promote diversification of skills. We believe great consultants need to know how to speak to both CFOs and CIOs at any large organization. Our consultants are encouraged to continuously grow and acquire news skills around four key areas: Functional (finance, accounting, business), Technical (all-things-SAP-Finance but mostly latest & greatest on a continuum), Business Development (pre-selling and selling), Project Management (knowing how projects are run from blueprint to reporting).

As to further diversifying our talent pool, the two big areas of opportunity would be:

  1. Hiring more female consultants. The fields of IT and Consulting have historically been predominantly male, especially in the U.S. Times are changing, however, and younger children are learning how to code as early as elementary school. Girls are also bolstered and encouraged to get into STEM fields through visionary organizations like org, Girls Who Code, Kode with Klossie etc. The gender chasm in what used to be a male-only vocation is closing, and we want to further represent this progressive mindset and positive change.
  2. Hiring neuro-atypical talent. I would personally love to embark upon this next frontier (1) as a mother of a child with autism and (2) given SAP is a huge investor in hiring Differently Abled People:

At SAP, we believe that differently abled does not mean unable. Differently abled individuals are typically able to find unique and innovative solutions to challenges. Their perspectives, experiences, and backgrounds support the diversity SAP needs to achieve our strategic objectives. Our focus is on skills and strengths, rather than what others may see as impairments. This view has helped us see new possibilities. SAP’s internationally recognized Autism at Work program, operating in 13 countries, shows this commitment, employing more than 160 colleagues with autism. By embracing differences, we help spark innovation — while challenging assumptions and inspiring change.

JS Irick: Perfectly said. I am so happy you mentioned Girls Who Code. In my work supporting underrepresented communities in tech, the number one intervention was simply showing positive role models. The work of charities like Girls Who Code and My Block, My Hood, My City (formyblock.org) are transformational.



Perspective 2:
Getting into Consulting

JS Irick: Our Data Science summer interns started last week, and one of my key goals is to help prepare them for their eventual job search. A big part of this is the preparation of their project and writing portfolio so they can go into an interview with concrete examples of their work. Obviously, this comes from my perspective as an interviewer and manager, I’d like to hear your perspective from the recruiting and talent development side.

Stephanie Hettrich: Without a doubt, concrete examples of work are a great measure of a candidate’s current stock and future potential. As I mentioned before, resumes only reveal so much, but the same could be said about interviews. When you think about it, interviews are similar to being up on stage and putting on your best act; rehearsing lines, dressing up, memorizing questions and thus not necessarily reflecting your real self. On the other hand, seeing actual work says much more about what candidates can actually do. It’s the difference between saying what you can do versus seeing the end-result of it.

JS Irick: Knowing what you know now, put yourself in the shoes of a College Sophomore. What would be your strategy to best prepare yourself for a consulting career?

Stephanie Hettrich: There are no undergraduate degrees that teach consulting, let alone SAP consulting. That said, the SAP Finance portfolio of products has evolved from being purely technical to being much more functional over the past few years, especially with S/4HANA and Central Finance playing such key roles in the market. As such, I would say majoring in Finance, Accounting or Business would offer a great foundation to learning the functional side of SAP consulting. On the other hand, Computer Science, Computer Engineering, Applied Mathematics, Economics/Econometrics, Data Processing using algorithms are great fields of study to learn the purely technical side of SAP software. MIS is likely the closest hybrid between technical and functional ability that resembles the core skills needed to learn what we do. Regardless of hard skills or college majors, however, SAP consulting can really only be learned on the job as consulting is a way of life in and of itself. It also requires myriad soft skills and EQ, which is seldom learned at a college level. We take great pride in offering our very own TruQua TONE – Training and Orientation for New Employees – to cover the fundamentals of SAP and Consulting over 3 intensive weeks of hands-on courses.

Perspective 3:
Career Development

JS Irick: At TruQua, we take a tremendous amount of pride in the growth and development of our employees. I consider the first year on the team to be a transformative one, not only for new hires but for newly hired senior team members as well. We are in an industry that moves incredibly quickly, in order to provide long term stability and growth for our team members it is imperative that we provide the ability to consistently upskill.

What can organizations do to ensure an environment where their team can continually grow?

Stephanie Hettrich: Our people are our best asset. It is thus paramount that we allow our talent to continuously develop their skills set, as well as advance their careers in a direction that is meaningful to them. We’re lucky that our Leadership is obsessed with always being cutting edge with SAP technology and its advances in the market. By extension, our company ethos is about constant learning and always running ahead of the technology (1) to be highly competitive and relevant in the market and (2) to foresee how we can pivot our internal skills set accordingly. It trickles down from above, but it also requires access to the right people at SAP in order to gain the right knowledge and resources. As a trusted SAP partner, we pride ourselves on cultivating key relationships, growing our network of connections by regularly attending and speaking at marquee SAP conferences around the globe, investing in R&D, as well as exponentially increasing our marketing presence across strategic channels. All these efforts have made our reputation and brand name as a premium provider of bleeding edge SAP Finance software and services stronger than ever. As we grow externally, it is imperative that we synergize efforts internally by giving our consultants access to the newest learning tools. In parallel, we strive to align key skills sets with our consultants’ areas of interest to capitalize on their core strengths and passions for optimal future development. In order to get there, we promote open and regular internal communications, mentor assignments, regular check-ins with consultants of a higher ranking, and regular internal training. These initiatives are done as a complement to our formal yearly performance review process so as to ensure consultants can grow and learn new skills based on their own subjective drive, versus as a product of management goals.

JS Irick: That’s an inspiring answer! You recruit based not only on a person’s current capabilities but their potential as well. What is one way in which you identify candidates that will continue to grow and excel?

Stephanie Hettrich: TruQua gives a lot of autonomy to its employees. There is a lot of work to do, deadlines to meet, pressure and stress to endure, but the most common goal amongst our employees is to achieve “weightlessness,” an internal concept that promotes quality, diligence, and self-efficacy. Weightlessness is about seeking out new skills in order to advance to new levels of professionalism. It is about increasing one’s strengths so that ever-greater challenges can be surpassed once previous struggles are mastered and newly gained knowledge is internalized along the way. Through weightlessness, anyone can grow and make an impact at TruQua no matter their background, tenure or previous experience. I see potential in people who embody weightlessness in all its forms: By going outside of their comfort zone to learn new skills, by conquering complex problems that involve struggle, by selflessly making time for their teammates to teach them those same steps, by volunteering to alleviate a colleagues’ workload even if the work isn’t directly in line with a given workstream. You can do a good job of staying in your lane, but you can do a great job by facing ambiguity. Those who grow and excel usually take on new challenges first and foremost for the betterment of the team, and secondarily for themselves.

JS Irick: Stephanie, thank you for taking the time to speak with me today. Your answers were both incredibly detailed and truly aspirational. We are so proud of the team you have helped to build at TruQua, and I hope this discussion helps other organizations build stronger, more inclusive groups. Thanks so much for sharing your expertise, and I look forward to our future discussions.

About our contributors:

Stephanie Hettrich

Stephanie Hettrich

Director of Recruiting

Stephanie Hettrich has been spearheading Recruiting at TruQua Enterprises, LLC since the company’s inception. With expertise in relationship management, communications, marketing, and project management, Stephanie has leveraged her skills to find talent and manage TruQua’s growing team of experts.

JS Irick

JS Irick

Director of Data Science and Artificial Intelligence

JS Irick has the best job in the world; working with a talented team to solve the toughest business challenges.  JS is an internationally recognized speaker on the topics of Machine Learning, SAP Planning, SAP S/4HANA and Software development. As the Director of Data Science and Artificial Intelligence at TruQua, JS has built best practices for SAP implementations in the areas of SAP HANA, SAP S/4HANA reporting, and SAP S/4HANA customization.     

Thank you for reading this installment in our New Perspectives blog series. Stay tuned for our next post where we will be talking to TruQua Interns Nicole Aragon and Treeank Patnaik on breaking into consulting and learning new technologies.

For more information on TruQua’s services and offerings, visit us online at www.truqua.com. To be notified of future blog posts and be included on our email list, please complete the form below.


Engaging Experiential Data (x-data) in Financial Planning

Nicole Aragon, Consulting Intern

Treeank Patnaik, Consulting Intern
JS Irick, Director of Data Science and Artificial Intelligence

Bill McDermott’s SAPPHIRE keynote focused on the Experience Economy – how businesses must enrich their financial and operational processes with customer feedback. To quote McDermott, “Experience is now the organizing principle of the global economy”. This blog will examine how experiential data or (X-Data), can be combined with operational data or (O-Data) and how SAP Analytics Cloud, in turn, supports the concurrent analysis of multiple data sources (“Data Blending”) to create more powerful analytic applications for the Experience Economy.

To show the power of blending X-Data and O-Data, we will review data from the 10 highest grossing movies of the summer. Our operational data set includes box office performance, ticket sales, and production cost data for each of the films.  (“Information courtesy of Box Office Mojo. Used with permission.” – see more great movie analysis at boxofficemojo.com). For our experiential data set, social media postings for each movie are analyzed based on data collected from Twitter (i.e.- keywords, hashtags, and the Twitter handles). Utilizing a Machine Learning technique called Natural Language Processing (NLP), we’re able to understand the emotion present in each tweet (this is also called sentiment analysis) and by combining the NLP analysis and location data, we can then begin to understand how each market is reacting to the various films.

To account for the informal language used on Twitter, the NLP library used in this analysis weighs capitalization, punctuation, and emojis. Including these features in the analysis of sentiment allows it to be as accurate as possible.


Data Blending

SAP Analytics Cloud (SAC) allows any number of local or remote data sources to be present in a given story, allowing analysts to avoid the data silos which are often present in legacy reporting tools.  SAC can join separate models together based on their corresponding dimensions in a process referred to as, Data Blending. This process makes it possible to draw conclusions from one model in relation to another and to identify patterns that can be used to establish a correlation between two sets of data. By linking the sentiment analysis model to the box office performance model, it is possible to analyze how the financial performance of a movie is influenced by the customer experience.

SAC makes it incredibly simple to couple models based on similar dimensions between them. For instance, we were able to link our Twitter and box office data models by their dimensions related to movie titles and dates.

By linking these two models and blending their data, visualizations can be created in SAC that displays information from both simultaneously. This allows us to discover connections on a larger scale, and focus on specific elements within each model. In the visualization below, the financial metrics of approximate ticket sales and studio revenue are contextualized and presented alongside a graphic related to the volume of posts made on Twitter and their overall sentiments.  This uniform presentation makes it possible to then observe our X-Data and O-Data for individual movies and examine the relationship between their financial and social media metrics. For instance, the first image below shows data for the movie Booksmart, while the second shows the same data, but for the movie Brightburn.

Visualization displaying box office and social media data for the movie Booksmart.

Visualization displaying box office and social media data for the movie Brightburn.



Combining these two streams of data with the modeling capabilities of SAC allows for the creation of robust visualizations, which can be used to more effectively examine relationships within the data and provide context for key business problems. These visualizations provide an avenue for furthering the insights generated by the models created in SAC and offer a means of integrating predictive analytics technology with already existing data.


Certain functionalities allow for the creation of charts showing financial measures, such as unit sales, and measure them against Twitter sentimentality. This allows for the analysis of patterns that may predict the performance of a product. For instance, in the case of the movie Pokémon Detective Pikachu, a high volume of tweets that were predominantly positive were immediately followed by a spike in ticket sales.

By mapping the number of Tweets posted that associated with specific films across days in the month of June, we can see how overall Twitter activity related to each movie varies as days go by. As demonstrated, this visual can display this data for the entire month of June but can be effortlessly adjusted to do so by day in order to offer more detailed insights. The visual language capabilities of SAC allow for this relationship to be expressed in a distribution chart that not only utilizes engaging aesthetic elements but takes advantage of these elements to communicate information directly and effectively.

Modeling in SAC also allows for geo-enrichment, after which data can be presented in dynamic map visuals such as the one above. This map contains two layers of information related to our X-Data and O-Data. The size of each bubble indicates how many tweets related to our set of movies were posted in each country, while the shading of each country indicates the average positivity of these tweets in that region. The visualization separates the data in a way that makes it easy to measure activity by region and displays it in a coherent and interesting manner. In the same way that other charts can be filtered to highlight relevant data, these maps can be altered to focus on specific geographical areas or movies.

Map filtered to show global social media activity related to only the Pokémon Detective Pikachu movie.



Within this blog, we have examined some of the powerful ways in which experiential data can be used to better understand operational performance. Using SAP Analytics Cloud, we can visualize these insights and easily follow trends over time as well as compare them to different metrics, driving “Experiential KPIs”. Collaborative Enterprise Planning with SAC replaces data and process silos with seamless collaboration to present and analyze data from different angles. The visualizations presented to allow for greater discovery of patterns and causation that may have been previously hidden in large spreadsheets, divided among separate department and buried in vast amounts of data. With the facilitated discovery, drawing insight becomes less of a challenge and easier to transform into planning and solutions. The experiential economy is won and lost on data insights, and the analysis shown today are just some of the ways to achieve those insights.

This blog was created by TruQua’s Summer 2019 Interns, Nicole Aragon, and Treaank Patnaik. Stay tuned for our upcoming “Movie Watch” blogs, where we will continue to analyze social media trends for this summer’s hottest films.

About our authors:

Nicole Aragon

Nicole Aragon

Consulting Intern

Nicole Aragon is a Senior at the University of Texas at Austin, where she studies Management Information Systems in the McCombs School of Business. She plans on continuing her experience working in data science after college.

Treeank Patnaik

Treeank Patnaik

Consulting Intern

Treeank Patnaik is a Consulting Intern at TruQua, working on improving business intelligence by using advanced analytics and machine learning software. He is currently pursuing a degree in Mechanical Engineering at the University of Texas at Austin, along with certificates in Applied Statistical Modeling and Foundations of Business Administration. 

JS Irick

JS Irick

Director of Data Science and Artificial Intelligence

JS Irick has the best job in the world; working with a talented team to solve the toughest business challenges.  JS is an internationally recognized speaker on the topics of Machine Learning, SAP Planning, SAP S/4HANA and Software development. As the Director of Data Science and Artificial Intelligence at TruQua, JS has built best practices for SAP implementations in the areas of SAP HANA, SAP S/4HANA reporting, and SAP S/4HANA customization.     

Editor’s Note

TruQua is currently hosting a closed beta for the Social Media analytics tools described in this article.  If you are interested in joining the beta program, please contact js.irick@truqua.com


Movie Sources

Aladdin, Directed by Guy Ritchie. https://www.imdb.com/title/tt6139732/

Brightburn, directed by David Yarovesky. https://www.imdb.com/title/tt7752126/

Booksmart, Directed by Olivia Wilde. https://www.imdb.com/title/tt1489887

Pokémon Detective Pikachu, Directed by Rob Letterman. https://www.imdb.com/title/tt5884052

For more information on TruQua’s services and offerings, visit us online at www.truqua.com. To be notified of future blog posts and be included on our email list, please complete the form below.


New Perspectives Blog Series: Digital Transformation with SAP S/4HANA

Welcome to TruQua’s New Perspectives blog series.  This blog series provides a platform for our consultants to share their perspectives, insights, and experiences on emerging technologies such as SAP HANA and SAP Analytics Cloud. 

Today we are speaking with TruQua Senior Consultant, Trainer, and Speaker, Matt Montes. Matt specializes in digital financial transformation, using the Central Finance deployment option to help customers leverage the financial and controlling components SAP S/4HANA without disrupting their current landscape.



Perspective 1: Looking Back to ECC

JS Irick: Matt, you represent a new generation in that you started your consulting career just before Simple Finance was released, so you are one of the first industry experts who “Grew Up” with S/4HANA. Obviously, you spend a lot of time with previous ERP versions working with Central Finance, as well as needing to communicate effectively with business stakeholders who are in the system day-to-day. There are hundreds of articles about what people with extensive ECC 6.0 think of S/4HANA, but I’d like to flip that on its head. What is your perception of ECC 6.0?

Matt Montes: This is a great question, especially in the context of how my SAP career started. My first implementation as an SAP consultant was actually a BPC Standard (10.0) Financial Consolidation project for one of the largest utility companies in Texas. To provide some context here, this project dealt with 55+ company codes and an enormous amount of master data. As you can imagine, I was in SAP terminology overload and immediately overwhelmed. Insert ECC6.0. Once I gained access to ECC I realized that all the information I needed was at my disposal, and quickly began analyzing and dissecting the Enterprise Structure.

From here I was able to better understand how SAP modeled core FI concepts (Company Code, G/L Account, Version) and tie them back to BPC. This was my lightbulb moment per se, which allowed me to start connecting the dots between the various financial modules and their integration points.

Taking what I learned in FI and figuring out how that tied into the Controlling and Logistics modules allowed me to gain a more holistic understanding of ECC. ECC to me is a revolutionary ERP that can be strategically leveraged to improve financial proficiency throughout an organization. Today’s strategic conversations are hyper-focused on S/4HANA being the next generation ERP, specifically for those organizations looking to undergo a financial transformation and gain the benefits of a relational database, real-time centralized financials, and a unified financial table (ACDOCA). However, I will argue that without the core concepts and modules within ECC, S/4HANA wouldn’t be as profound as it is today. This is bolstered by the fact that when I deliver customer demos of S/4HANA I tend to focus on the Fiori user experience, as this is an added benefit to the core concepts and modules that the customer is already used to in ECC” Ultimately, my perception of ECC is that it is the foundation for what an ERP should be, while simultaneously allowing S/4HANA to build upon that core foundation and deliver additional value.

JS Irick:  I love the positive take.  ECC stands as a true technical accomplishment, weathering major infrastructure, network, architecture and industry changes. It is refreshing to hear someone talk about the benefits of S/4HANA without denigrating the parts of ECC that have aged poorly.

You talk about three key benefits – being on a relational database, real-time centralized financials, and the Universal Journal.  Frankly, all three are critical, can you dive down on one of them a bit more to give our readers some more insights?

Matt Montes: Absolutely. As you are aware, financial reporting in ECC today can be quite convoluted as there are a variety of tables that house actuals data (BSEG, BKPF, COEP, COBK, FAGLFLEXA, etc). This often leads to a BW driven reporting solution with multiple cubes pointed to multiple tables, and data is loaded via batch jobs. The Universal Journal (ACDOCA) is a game-changing concept as it allows enterprises to persist all of their actuals data in one central table, which is a stark contrast to the complexity associated with a BW reporting solution. In addition to housing actuals data in one universal table, the data is also written to ACDOCA in real-time, which eliminates the need for batch jobs and provides the business with quick access to their data. Centralized reporting and real-time data can significantly increase how businesses operate and conduct their financial reporting and analytics.



Perspective 2: Hidden Advantages of SAP S/4HANA

JS Irick: With its strategically limited scope and replication-based architecture, Central Finance implementations are an order of magnitude faster than a full-blown S/4HANA rollout. This means users get into the system on live data fast. Based on the compressed timeline, I would expect the transition to the Universal Journal and Fiori based applications to be even more refreshing. Everyone’s S/4HANA talk track seems the same “single source of truth, profitability on all dimensions, role-based mobile enabled user experience, etc. etc.”. What are some of the S/4HANA advantages in process, UX, reporting or operation that doesn’t get enough press in your opinion? Sell me on S/4, “What nobody mentions, but you’ll love is ______”.

Matt Montes: There are some benefits of S/4HANA that are going to steal the headlines, such as increased performance, coding block simplification, digital core, and unified financials. However, those benefits barely scratch the surface on what makes S/4HANA the ERP of the future. Fiori gets a lot of praise, rightfully so, but the praise usually highlights the tile-based user experience or mobile accessibility. What isn’t as talked about is the innate drill-down functionality and linkage amongst the financial tiles.

For example, within Fiori, a financial analyst can select from a variety of tiles such as display financial balances, display financial line items, manage journal entries, or journal entry analyzer. However, if they were to start with the financial balances tile (summary level data), they can seamlessly drill-down to the line items without having to open another tab or access a different tile. Furthermore, from the line item tile, the end user can now manage journals from a specific document or run a journal entry analyzer report. To me, this adds an enormous amount of value for the financial analyst or accountant who needs quick and easy access to their data. When accessing data via ECC or S/4HANA you are susceptible to multiple sessions and multiple TCODES to access data, and this isn’t efficient nor effective. Everybody talks about “single source of truth”, but doesn’t mention the operational benefits of having an actual, plan, and consolidated data spread across ACDOCA, ACDOCP, and ACDOCU. Think about the reporting landscape today for an ECC environment, which is almost always a batch process populating various BW cubes in which reports are subsequently built off of. In addition to the batch processing causing a delay in real-time reporting, there is also a concern of reconciling the data in ECC vs what was loaded into the BW cubes. The operational benefits of having three core financial tables with actual, plan, and consolidated data persisted in real-time, which can then be queried through Analysis for Office, Fiori, or CDS views is unquantifiable. S/4HANA’s value proposition lies with its ability to integrate a multitude of technologies and software’s into one all-inclusive ERP that meets statutory, management, and internal requirements.

JS Irick: That’s a great way to describe the tangible benefits of the improved user experience. I hear “Role-Based UX” so often, but you’ve really explained what that means in terms of the user experience within discrete processes.

I’m a huge fan of the Launchpad UX in S/4HANA and SAC. Not only for the simplified way to change your shortcuts/tiles, but also the fact that you can introduce key metrics into your Launchpad. A question for you – Have you seen much adoption of the Fiori KPI tiles? To me, they’re one of the 4 pillars of S/4HANA reporting (along with AO, SAC and Fiori Reports), but I don’t see them mentioned very often.

Matt Montes: This is a great point JS, I haven’t seen much adoption of the Fiori KPI tiles; however, I do have some hands-on experience using them. In one of my previous engagements, we leveraged Fiori KPI tiles and SAP Smart Business to create utility-centric tiles. In the utility industry companies have to report two sets of financials, one for GAAP accounting and another to abide by the Federal Energy Regulatory Commission (FERC) standards. Within the FERC reporting requirements are metrics like Rate of Return, Rate Base, Return on Equity, Capital Structure, and Revenue Requirement. Each of these metrics is vital to a utilities regulatory decision-making process, as well as determining the amount of money they can recoup on their infrastructure-based investments (Power Plants, Natural Gas Pipelines, Water Treatment Plants, etc). The Fiori KPI tiles and SAP Smart Business enabled us to create a utility-focused dashboard within Fiori that gave business users a medium to analyze their regulatory data. I think as Fiori continues to evolve, we will start to see a lot more integration of the KPI tiles, specifically as companies work towards building an S/4HANA environment with actual, plan, and consolidated data.



Perspective 3: Upskilling for the Future

JS Irick: In my opinion, your dedication to educating and training our Central Finance customers is crucial to our project success, and one of the reasons your customers are so happy with the final result. Any major technology disruption can be really scary to IT organizations because their day-to-day requirements don’t slow down, even as this major shift in their role is on the horizon. What’s your actionable advice for gearing up for S/4HANA, especially on a tight schedule?

Matt Montes: You bring up a really good point here. Digital transformations or changes in technology can be very demanding on the IT organization. Asking someone to acquire a skillset in new technology while simultaneously maintaining their day-to-day duties can be incredibly cumbersome. My advice would be simple, understand your organizations business processes and financial data model as best you can in order to reduce any uncertainties and close any knowledge gaps. Said more precisely, understand what modules of your ERP are being utilized and what data is associated with those modules. As an SAP consultant, we often analyze business processes, master data, and configuration to gain an understanding of an enterprise. Therefore, IT organizations can also embark on a similar exercise to analyze and digest the business processes, master data, and configuration that make up their organization. This understanding helps to eliminate any uncertainties and close any potential knowledge gaps as the gearing up for S/4HANA occurs. Another approach to gearing up for S/4HANA is to undergo a POC that is designed to address the potential uncertainties or gaps that may exist within the ERP. POC’s can be extremely informative if positioned correctly, and they help to ramp up the end users by giving them hands-on experience prior to the full implementation. A majority of the configuration and master data that exists within ECC will be leveraged and reimplemented in some form or fashion into S/4HANA; therefore, truly understanding the inner workings of your ERP will help to reduce some of the barriers to entry that come with S/4HANA.

Another approach to gear up for S/4HANA is through training or knowledge transfer sessions. At TruQua, we understand that a lot of the changes that come with a digital transformation often produce more questions than answers, so we have developed a repository of training material known as TruCert. The TruCert material can be compiled and constructed to address one technology in detail, or multiple technologies at a high-level. In conclusion, understanding your ERP at a process level, gaining hands-on experience with S/4HANA, and ramping up on your S/4 knowledge are all ways in which the digital transformation to S/4HANA can become less intimidating.

JS Irick: “Truly understanding the inner workings of your ERP will help to reduce some of the barriers to entry that come with S/4HANA” – I think you’ve really hit the nail on the head here. Those who truly understand their current system are indispensable in a Financial Transformation. Can you lay out a couple of areas where customer knowledge is crucial? I know that’s a super broad question, but I’m looking for something along the lines of “Understanding Customer/Vendor enhancements vis-à-vis the move to Business Partner”. 

Matt Montes: Customer Vendor Integration (CVI) to Business Partner is definitely a big component of the transition to S/4HANA; however, for me the most important area of customer knowledge lies in the ability to understand and speak to the cost flow and end-to-end business processes associated with your ERP. It is one thing to understand your ERP at a process level, but even more important is understanding what master data and configuration points are being leveraged throughout those processes. It is critical to not only understand how things are done, but why they are being done as well. For example, a quick analysis of an ERP can uncover the fact that certain costs booked to sending Cost Centers are ultimately settled to a Fixed Asset; however, understanding why those costs are being settled and what configuration is dictating that settlement is exponentially more valuable. To me, this type of skill-set and knowledge can be the difference between a good implementation and a great one.

Matt Montes, thank you for taking the time to speak with me today. S/4HANA and Financial Transformation are such broad topics, with so much content published daily, that it is really refreshing to sit down and speak with an expert about a few key areas. All the best in your upcoming projects and I look forward to speaking with you again.

About our contributors:

JS Irick

JS Irick

Director of Data Science and Artificial Intelligence

JS Irick has the best job in the world; working with a talented team to solve the toughest business challenges.  JS is an internationally recognized speaker on the topics of Machine Learning, SAP Planning, SAP S/4HANA and Software development. As the Director of Data Science and Artificial Intelligence at TruQua, JS has built best practices for SAP implementations in the areas of SAP HANA, SAP S/4HANA reporting, and SAP S/4HANA customization.     

Matt Montes

Matt Montes

SAP Financials Senior Consultant, Trainer, and Speaker

Matt Montes Montes is a Finance and Data-driven professional currently working as an SAP Financials Senior Consultant. He received his education from the University of Texas at Austin with a degree in Finance and a minor in Accounting. His professional experience is comprised of financial analysis, budgeting, consolidation, accounting, and data analytics. Matt Montes has 4 years of financial consulting experience utilizing Central Finance, S/4HANA, ECC, Fiori, and BPC. In addition to 2 full lifecycle implementations, product development, and 6 POC’s, Matt Montes also works as a trainer and content developer. Matt Montes has conducted two internal and external training covering Central Finance, Group Reporting, SAC, and Reporting & Analytics. Additionally, Matt Montes has written and delivered two blogs, a webinar, and a 3-part demo series on Central Finance.

Thank you for reading this installment in our New Perspectives blog series. Stay tuned for our next post where we will be talking to Recruiting Director Stephanie Hettrich on identifying and developing young consulting talent.

For more information on TruQua’s services and offerings, visit us online at www.truqua.com. To be notified of future blog posts and be included on our email list, please complete the form below.


TruQua Expands its Thought Leadership with Key Strategic Hires

Chicago, IL USA – May 3, 2019 – TruQua Enterprises LLC, a leading Finance and Business Analytics software and consulting services provider, is proud to announce the recent hires of Kirk Anderson and Leo Schultz from SAP and Parminder Ghatahora and Marc Six from the Big Four consulting firms.

“We believe in quality over quantity, especially for finance transformation initiatives at our customers,” says David Dixon, co-founder, and partner at TruQua. “The larger the change and project, the greater the need for top-tier talent and leadership to catalyze change, otherwise, you risk a big and hard fall.”

TruQua’s strategic new additions and their roles are:

Kirk Anderson who was a leading authority at SAP as a Chief Solution Expert and VP of Solution Management. He is widely recognized as a leading financials expert both at SAP and at customers with over 25 years of deep SAP experience including the specialized areas of corporate financial reporting, operational and tax transfer pricing and financial planning and analysis. Kirk is a Chartered Accountant and worked a number of years in public accounting prior to joining SAP.  He joins TruQua as the Chief of Financial Solutions bringing his SAP relationships and insights into SAP S/4HANA.

Leo Schultz who was the lead Solution Engineer for SAP S/4HANA Finance for North America at SAP. During early customer engagements in the sales process, he provided finance expertise, business case development support, benchmark advisory consulting and system demonstrations. He joins TruQua with over 25 years of experience in Finance and Accounting. At TruQua, Leo Schultz is the Senior Vice President of Global Sales.

Parminder Ghatahora was a Director of Advisory at a Big Four consultancy. He led the North American Consumer Markets Enterprise Performance Management practice in engagements that assisted clients’ development of strategic vision, solution implementation and performance improvement enabled by SAP in the area of finance. that assisted clients’ development of strategic vision, solution implementation, and performance improvement enabled by SAP in the area of finance. He brings over 20 years of experience in the finance and technology space and is a member of the Chartered Institute of Management Accountants. Parminder joins TruQua as a Principal and Practice Lead.

Marc Six who was a leading SAP S/4HANA and SAP Financials expert in the Enterprise Solutions practice at a Big Four consultancy. Prior to that, he was a specialist in the SAP Max Attention team working on the earliest implementations of SAP S/4HANA Finance and Central Finance including co-development projects. Marc joins TruQua as a Principal and Practice Lead.

Kirk Anderson, on his rationale for joining TruQua, explains, “Having had the good fortune to work with TruQua in the past, I knew that joining their team would afford me the opportunity to work with a great group of highly skilled and creative people who are truly dedicated to the concepts of quality, integrity and commitment, both to customers and their employees. This is a company where I feel my contribution can really make a difference.”

Scott Cairncross, co-founder, and partner at TruQua, concludes, “Our team is really excited to welcome this exceptional group of individuals to our smart, driven and nice culture. And our customers benefit not only from an expertise perspective but, more importantly, the deep, meaningful and long-lasting relationships that our all-stars are able to foster.”


TruQua is an SAP service and software development partner specializing in software solutions, project implementations, and deployment strategies for SAP S/4HANA, SAP Financials, SAP Analytics, and overall SAP Platform and Technology solutions. TruQua continues to influence the direction of these products and build custom solutions to bridge any gaps in product functionality. TruQua also actively helps SAP customers derive value from maturing areas such as Machine Learning, Artificial Intelligence, and Blockchain. For more information, please visit www.truqua.com or follow us on twitter @TruQuaE.

Marketing Contact:
Allison Murtagh, Marketing



New Perspectives Blog Series: Bringing AI to the Realm of Corporate Finance

Welcome to TruQua’s New Perspectives blog series.  This blog series provides a platform for our consultants to share their perspectives, insights, and experiences on emerging technologies such as SAP HANA and SAP Analytics Cloud. 

Today we are speaking with Senior Cloud Architect Daniel Settanni. Daniel’s passion is bringing AI to the realm of corporate finance. With his deep expertise in time series analysis, cloud architecture and SAP planning solutions, Daniel is able to not only create impressive Machine Learning models but also deploy them in an integrated, accurate and explainable way. As you will see below, Daniel does an exceptional job at both demystifying the technologies behind AI/ML and “defeating the black box” through explainable AI.

Perspective 1: Getting Started with Machine Learning for Finance

JS Irick: Daniel, a few weeks back you and I hosted a pre-conference session at SAP-Centric where we led attendees through building their first Machine Learning model to predict OPEX (based on published financials for a Fortune 500 company).  In that case, it was easy for our attendees to be successful because the problem was already defined. When it comes to the enterprise level, identifying the opportunity and success criteria is the first major roadblock customers face. Can you talk a little bit about how customers can set themselves up for success in their foundational ML projects?


Daniel Settanni: Sure JS.  Figuring out where to start with ML can seem like an insurmountable challenge and for good reason.  ML and AI pop up in the news every day.  Topics like ML generated movie recommendations and AI created art are cool, but not relatable to most enterprises.  On the flip side, Enterprise Software usually incorporates ML/AI in tasks that are common across wide swaths of the market that focus on automation.  These are much more relatable, but don’t speak to how Enterprises can use ML to solve their own problems… from the mundane to the highly strategic.

So, now to your question. 

If an Enterprise is just starting out with Machine Learning and is having a hard time finding the right opportunity, then pick something relatively simple like a basic forecasting project.  These are a great place to start because the models can be kept simple, the predictions can be easily integrated with the existing business processes, and the results deliver real value (I haven’t met an Enterprise yet that isn’t looking to improve their forecasting accuracy in one area or another).  But above all, projects like this provide real-world experience with the ins and outs of ML – plus they always generate a ton of new ideas on where to use ML next.

If the Enterprise has already identified the opportunity, then I’d make sure that their success criteria include delivering a way for users to interact with the model.  This could be as simple as pulling predictions into an existing business system as a new Forecast version or entail developing a custom dashboard for what-if analysis.  In any case, if the success criteria is simply to build an accurate model that never sees the world beyond the data science team, they will be losing out on the vast majority of ML’s true Enterprise value.

JS Irick: “But above all, projects like this provide real-world experience with the ins and outs of ML – plus they always generate a ton of new ideas on where to use ML next.”  That’s definitely my favorite part of working on these projects with you. We get to see the lightbulb go on in real time which leads to fascinating strategic discussions. I believe that best consultants not only help their clients with their current project, but they also help chart the way forward through education and enablement.  

Can you talk a bit more about “interacting with the model”, with some examples? I think this is important for folks just getting started with AI/ML.

Daniel Settanni: Absolutely. The main point here is that the more completely people can interact with something (an ML model in this case), the more they will understand it and the greater the understanding, the greater the potential for meaningful insights.

This “interaction” can look very different depending on the business problem being solved.

For example, if we built out a Forecasting model the minimum level of interaction would result in a spreadsheet.  This isn’t a great option for a lot of reasons, the most basic of which is that it’s not in the same place as the related business data.

We can fix that by integrating our hypothetical Forecasting model with the related Enterprise Application.  Now the forecasts can be viewed in context, but there isn’t any transparency around how the model came to the conclusions it did.  The best case here is that the forecast is proved to be accurate at which point the business will just accept it – but being overly reliant on a model in this way is dangerous.

So, next, we’ll add explainability to our model.  Based on this, our analysts gain insight into not only what the model predicted, but what why it arrived at the answer as well.  Since our analysts are the true experts, this can lead to valuable feedback on ways to make the model better.  Because there’s transparency, it can also become more of a trusted tool.

We’ve made a lot of progress from our spreadsheet, but we don’t have to stop there.  We could make the model truly interactive by allowing analysts to tweak its assumptions and see its impacts on the prediction and explanations.  At this point, you have what I like to call a Strategic model, one that can aid in making business decisions.

Before moving on, I’d like to highlight another example to show how this methodology can be applied to other areas.  As you know, we built out an Employee Retention model last year that was integrated with SuccessFactors.  The basic output of the model was the likelihood an employee would leave during the next year.  The predictions were based on factors like salary growth, time at the company, historical promotions, etc.

To make this model most valuable, we didn’t stop at the raw prediction.  We created a dashboard where HR analysts could actually predict the impact of interventions, greatly increasing the chance they could retain their top talent.

These are just a few examples of why I believe interaction is one of the core pillars of a successful, and valuable, ML-based solution.

Perspective 2: From Prediction to Explanation to Intervention

JS Irick: From my work in medical science, I’ve always felt that researchers first seek to understand so that you can intervene. While the moment of discovery is exciting, it pales in comparison to using that discovery to impact change. Machine Learning changes the paradigm a bit, in that first you predict, then you explain, then you intervene. This leads to two questions – first, how do you get predictions into analysts’ hands quickly enough so that there is time to intervene? Second, can you explain to our readers how you go from a raw numerical prediction to actionable insights?

Daniel Settanni: You bring up some great points here.  Without insight, there can be no action and without action, there can be no value. 

The answer to the first question is easy to answer, but not always simple to implement.  To get predictions into Analysts hands quickly enough to intervene, a model must either be integrated with their business system or directly accessible in some other way.  If Analysts have to wait for quarterly or even monthly reports, then they’ve probably missed their chance to act.  On the other hand, allowing them to perform some degree of what-if analysis in real time can put them dramatically ahead of the curve.

One quick anecdote before I move on to question number two… in my experience, the initial success criteria for an ML project is accuracy.  This makes complete and total sense but once you deliver an accurate model the next logical question is “Why”?  No one likes a black box, and even more importantly, no one trusts a black box.  Without some degree of understanding, trusting the results of an ML model can feel like a leap of faith and who wants to bet their career on that?

So how do you get from raw numerical predictions to actionable insights?  It starts with deeply understanding the problem you are trying to solve and building your model around that (instead of just accuracy).  This involves carefully selecting features (model inputs) that are related to the question at hand.  Having relatable features can give analysts some confidence in a model, but adding in Explainable AI, a technology that figures out each features contribution to a prediction, can really deliver the trust needed to go from prediction to action.

JS Irick: Without getting too deep into the technical side, can you talk a bit more about feature selection? In a lot of ways, I lean on my research experience; which means I focus on explaining statistical malpractice “this will pollute your results because….”. I’d love to hear a positive, actionable take on the value of feature selection.

Daniel Settanni: You’ve picked a topic close to my heart. Before diving in, here’s a quick recap on what a feature is.  In its most basic form, a Machine Learning model uses a bunch of inputs to predict an output. In Data Science lingo the inputs are called features and the output is called the label.

There’s one more topic we need to touch on before we can really talk about features… the different reasons models are created in the first place.  This may sound like a silly question – we create models to predict things of course! 

But… there are different types of predictions.

For example, I may want to create a model that can remove human bias from my Sales forecasts, or I may want a model that can accurately predict the impact of a certain business decision to my Sales forecast.  In both cases, we’re forecasting the same thing, but our goals are very different. 

How can we do this?  The answer lies in feature selection. 

In the first scenario (where we want to remove human bias), we would focus on factors outside the scope of control of the business.  These would likely include macroeconomic data, sales trends, consumer (financial) health, and the like.  By training a model with this type of features, we would be capturing the historic performance of a company.  These types of models tend to be very accurate, especially for mature organizations.

In the second scenario, we want to do pretty much the opposite.  Instead of focusing on things we can’t change to capture historical performance, we look at the things we can – so it’s much more of a microeconomic viewpoint.  By adding explanations to the solution, a model like this can empower decision makers to get accurate information on the impacts to the bottom line of many decisions.  That said, this model is going to be extremely vulnerable to human bias so while it can be an amazing strategic solution, it isn’t a great pure forecasting one.

And there’s no law that says all features have to be macro vs microeconomic.  In fact, many are mashups if you will.  So ultimately the key isn’t to match the features to what you’re predicting, it’s to match the features to the question you’re trying to answer.

Perspective 3: Into the Wild

JS Irick: As you know, many wonderful forecasting tools never make it out of the “validation” phase. Integration, maintenance, retraining, and continuous validation are critical for the long term health of any project, but especially an ML/AI project. Unsupervised predictive models tend to fail “silently”, in that there’s no production down moment. Our product Florence is one way for customers to ensure not only the best practices in model development but also long term model health. Can you talk a little bit about the challenges customers face and how Florence solves them?

Daniel Settanni: Glad to.  ML/AI projects often focus, in some cases solely, on building an accurate model.  This is a fine approach if you’re in a scientific setting, but in the Enterprise simply building the model is only a small piece of the puzzle. 

To get the most value out of an Enterprise ML project, it has to be:

  • Accurate
  • Interactable
  • Explainable

A model alone can only deliver on accuracy. 

To be interactable, the model has to be accessible in real-time.  This means it has to be deployed somewhere and either integrated into an existing system or a net new application has to be created. 

To be explainable, the appropriate technology must be deployed alongside the model and integrated into the prediction process.

The challenges that come with making a model interactable and explainable are considerable and often require ongoing collaboration with the DevOps and Development teams.  I highlighted “ongoing collaboration” because this is commonly missed cost/risk.  During the lifetime of an ML/AI project, its’ model(s) will likely have to be retrained many times.  When a model gets retrained, the data preparation steps often have to update, and when that happens corresponding changes have to be made by the DevOps and Development teams.  The worst part is if the changes aren’t made exactly right the models will keep on delivering predictions.  They’ll just be less accurate, probably way less accurate.  And if you’re making decisions off of those predictions, that could be very costly.

Most solutions only deliver on a few pieces of an ML/AI project, leaving it up to each customer to figure out everything else.  We took a very different approach with Florence.

Florence covers the entire process, from creating accurate and explainable models to make them available in real-time, to provide the APIs and security necessary to integrate with practically any Enterprise system. 

One of my favorite technological advances is the way Florence abstracts away things like data preparation, so all the Developers have to focus on is creating the best user experience and users can be confident that predictions aren’t wrong due to integration issues.

JS Irick: Excellently put.  I’m a big believer in Eric Raymond’s “The Art of Unix Programming”. I find that the rules still hold up (also, it’s interesting that some of the proto-ML techniques are coming back into vogue). Some of the rules speak strongly to the strengths of ML – “Avoid hand-hacking; write programs to write programs when you can” and “Programmer time is expensive; conserve it in preference to machine time” come immediately to mind.  However, you’ve touched on something that shoots up red flags – “When you must fail, fail noisily and as soon as possible”. Some of the toughest technical issues we face come when a system is failing silently, producing unintended consequences downstream. Especially when it comes to algorithms whose results are making financial decisions. Ask any futures trader, they’d rather the system crash than give incorrect responses due to a bug.

You hit the nail on the head when you noted that Florence applies the necessary data prep on the decision side as well as the training side. If numbers need to be scaled, normalized, etc. that should absolutely be on the server side. As a user, I get so salty when I hear things like “Oh, you forgot to turn your image into an array of integers before submitting it”. Let people speak in their language, and if there’s any data prep that needs to be done, it needs to be done in an abstracted, centralized way.

You’ve been doing some tremendous UX work in Florence recently, got a teaser for us?

Daniel Settanni: I’ve got the perfect images for this conversation.  It’s of Florence’s model validation view for a Macroeconomic model. 

The first screenshot shows the incredible accuracy we obtained, but perhaps, more importantly, the explainability Florence delivers.  Information like this can drive extremely valuable insights, and with Florence it doesn’t come with any additional work – it’s baked right in.

Thank you so much for spending time with me today Daniel. I always learn a tremendous amount when we speak, and even better, I get fired up to build new things. Hopefully, our readers were both educated and inspired as well.

Daniel and I consistently share articles/podcasts/news on AI/ML topics, and we’d love it if you all joined the conversation. Be on the lookout for our upcoming weekly newsletter which will go over the most interesting content of the week.

About our contributors:

JS Irick

JS Irick

Director of Data Science and Artificial Intelligence

JS Irick has the best job in the world; working with a talented team to solve the toughest business challenges.  JS is an internationally recognized speaker on the topics of Machine Learning, SAP Planning, SAP S/4HANA and Software development. As the Director of Data Science and Artificial Intelligence at TruQua, JS has built best practices for SAP implementations in the areas of SAP HANA, SAP S/4HANA reporting, and SAP S/4HANA customization.     

Daniel Settanni

Daniel Settanni

Senior Data Scientist and Cloud Architect

Daniel Settanni is living the dream at TruQua, using innovative technology to solve traditionally underserved Enterprise challenges. Making advanced technology more accessible with thoughtful design has been Daniel’s passion for years.  He’s currently focused on Florence by TruQua, an innovative Machine Learning solution that delivers Interactive and Explainable AI in a fraction of the time, and cost, of any other product on the market.

Thank you for reading this installment in our New Perspectives blog series. Stay tuned for our next post where we will be talking to Senior Consultant Matt Montes on Central Finance and the road to S/4HANA for mature organizations.

For more information on TruQua’s services and offerings, visit us online at www.truqua.com. To be notified of future blog posts and be included on our email list, please complete the form below.


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