Nilly Essaides

Nilly Essaides is the Senior Research Director of Finance/EPM/FinOps Advisory at The Hackett Group. In that capacity, she devises quantitative surveys, analyses findings, builds models, authors research reports, blogs, and delivers webcast, presentations and facilitates peer-to-peer exchange.

Ms. Essaides has nearly 30 years of experience researching, writing, and speaking about finance topics, with a focus on the way finance adds value to the enterprise through excellence in financial management and planning processes. Previously she led the FP&A practice at The Association for Financial Professionals.

Ms. Essaides is often quoted in the Wall Street Journal and other publications. She’s a prolific blogger with thousands of LinkedIn followers, and writes for external publications such as Digitalist Magazine. In addition, she co-authored a book about the internal transfer of best practices, If Only We Knew What We Know (Simon & Schuster, 1998). 
 

Author's Articles

There are currently no published articles of this author.

SBB Cargo: Using AI to Build an Intelligent Business Simulation Engine

By Nilly Essaides, Senior Research Director Finance/EPM at The Hackett Group 

I was recently invited to join FP&A-Trends’ Artificial Intelligence/Machine Learning (AI/ML) Committee by Larysa Melnychuk, managing director. The committee is comprised of finance practitioners and data-management/science experts and focuses on identifying and sharing the practical application of AI/ML-enabled technologies in Financial Planning & Analysis (FP&A) and controlling. This blog is based on a case study presented at the June 2018 meeting.
  
Artificial Intelligence and Machine Learning are on course to become the most revolutionary technologies in enhancing finance’s decision-support role. While automation (even through RPA) has eliminated many repetitive tasks and unnecessary human intervention, the next step for finance is to develop advanced analytics capabilities so it can deliver business value through actionable recommendations. 
 
That’s what drives Swiss rail freight company SBB Cargo to replace its traditional management accounting system with an intelligent business simulation engine that optimizes its shipping operations.
 
According to CFO Stefan Spiegel, over the past seven years, finance has relied on a traditional management accounting system; the system provided granularity in terms of cost allocation and calculation of contribution margins. But it didn’t offer a clear insight into the specific ways shipment are organized (often trains ship goods from multiple clients). So, it couldn’t help SBB ensure it maximized its capacity based on business data.

The company relied on its ERP to make the complex cost calculations. This was expensive and did not provide visibility of concrete improvement measures. “We had accurate cost allocations, but we didn’t know how financial performance would be affected if we lose or acquire a new customer. We couldn’t say directly what’s happening in the business,” Spiegel said. 

Switching Gears

That’s why SBB decided to leverage AI to build multiple models that are customer-made for different business areas. The objective was to simulate the behavior of different operational planning activities and understand their impact on financial performance. “We wanted to know what would happen if we made a business shift. When a customer is added, it cascades through the entire business. The models allow business and finance leaders to dynamically see what’s happening to margins and the cost.”

The models make up an intelligence business simulation model that links the accounting/ERP system to the operations’ planning and scheduling applications to identify the impact of business choices on other activities. (See Image Below.)


Comparing Old to New

SBB identified multiple benefits based on the difference between traditional management accounting and its new simulation engine (see image below). Overall, the new approach, which is set to replace the preexisting management accounting system, produces direct business recommendations; it’s cheaper than the old ERP model, and offers dynamic interaction with front-end information. 


“We found that if we place the shipments in an intelligent way into our logistics network, we can improve asset utilization by more than 30% ,” Spiegel concluded. “Of course, the hardest part is to unlock this potential as all business processes need to be changed. But the way to do it is shown very clearly.”

The full text is available for registered users. Please register to view the rest of the article.
Why and How to Build an FP&A CoE?

By Nilly Essaides, Senior Research Director Finance/EPM at The Hackett Group 

Financial Planning and Analysis (FP&A) Centers of Excellence (CoEs) are an increasingly potent solution to a very timely challenge: How to improve the analytics and decision support capabilities of FP&A, when finance is under continued pressure to do more with less. According to The Hackett Group 2017 Key Issues Study, finance’s major enterprise objective is now to help formulate strategy through delivering better analytics and reporting. That’s right up FP&A’s alley. Yet the study also found the finance budget is expected to contract by 3.8% and its headcount by 4.4%.

A Two-Part Answer

That means FP&A must find new ways to improve the quality of its service to internal customers but keep costs down.  There are two interrelated ways it can achieve this goal:

Approach #1: It can leverage new technologies to speed up its ROI on EPM tools and improve the quality of analytics and efficiency of core processes execution. Our 2017 Key Issues Study shows finance expects digital transformation to bring about step improvement in its performance as well as significant changes in its service delivery model; although it also shows the function is way behind on its digital execution capabilities. At the same time, the study predicts big adoption jumps in technologies like cloud-based tools and predictive analytics. Wider adoption of new technologies will help FP&A improve the quality of its reporting while making it more efficient by reducing the data-to-insight cycle time.

Approach #2: Concurrently, FP&A can pull together the execution of these analytics and core processes into a central entity to help develop the talent and expertise to more efficiently and effectively serve internal customers. By pulling its resources from activities often performed piecemeal at business unit finance organizations (see image below), FP&A can reduce headcount; but more so, it can develop better expertise to improve the quality of its service.
Activities still performed at the Business Unit Level.

Source: The Hackett Group 2016 BU Finance Study

What’s in a CoE?

A CoE is an organizational entity, physical or virtual, that consolidates activities requiring critical and/or specialized skills, with a focus on developing a core competency. CoEs are typically established for processes requiring knowledge-based skills that are of higher value to the function rather than commodity-type, transactional tasks that are often pulled into a global business services (GBS) entity. A lot of the high-value activities that are currently handled by business units (see image above) can be more effectively handled by a CoE, leveraging the analytical capabilities of a core group of experts.

If activities like forecasting and management reporting are pulled into the CoE, along with business intelligence (BI) and analytics, the CoE can reduce overall headcount. More importantly, it can free up business unit (BU) finance staff to focus on a core mission of working closely with business, developing a strong understanding of the operations and solving business problems in real time, all the while interacting with the CoE to supplement advice with sophisticated analytics.

How to Design a CoE?

FP&A teams looking to create a CoE should consider the four following steps:

  • Establish the purpose and case for a future-state CoE. Articulate why a CoE is needed to support FP&A, as well as the overall purpose of this construct in executing and delivering against finance’s strategic objectives and those of the broader enterprise; make sure to identify improvement opportunities for cost, service, value and/or use of technology.
  • Determine the scope and activities to be performed. Decide which FP&A services to offer through the CoE vs. BU-based FP&A teams. This includes evaluating the current state of FP&A and identifying the barriers prohibiting the function from delivering higher-value services. In many cases, the efforts will require a progressive build-out over time before advancing to more complex areas.
  • Align on organizational design and reporting relationships. Re-architect finance for value creation, while delivering on core planning and reporting activities in a consistent and reliable way. That means fulfilling current FP&A demands, while considering how needs differ between BUs and/or regions, as well as the role of a GBS if it exists.
  • Determine the interaction model. Articulate how the CoE will support and interact with the business, by delineating its intended role and how involved it’s going to get within its scope of activities. CoEs evolve over time as their experience and credibility grow. Depending on its starting point, CoEs may begin in a “reporter” role, and progress into an “advisor” role.
  • Define the skill set. Finally, FP&A should figure out what is the talent profile (profiles) required to staff the CoE in order to deliver on its improved service promise. It needs to begin to inventory its existing skill set to assess readiness. It then must come up with a hiring and development plan to build the capabilities to offer services to support the CoE’s defined scope and activities.

The CoE can create a center of expertise that can feed internal constituents with key analytical and core services, like forecasting and budgeting support; it reduces the need for multiple FTEs at the BU level and brings together subject matter experts and centralizes activities in one location. That model simplifies the interaction with business units, other parts of finance and senior management. It becomes a one-stop shop for providing high value-add services to internal customers and the new part of the finance operating model, enabled by digital technologies.

The full text is available for registered users. Please register to view the rest of the article.
to view and submit comments
IBP is Going Digital: The Why and How

By Nilly Essaides, Senior Research Director Finance/EPM at The Hackett Group 

Economic uncertainty, intense competition, and continuous technological disruption present new challenges for companies and their FP&A teams. To survive and thrive, organizations must become “super agile,” i.e., make and execute decisions at market speed. This puts pressure on FP&A to rearchitect the enterprise planning process, by integrating business and financial planning activities. 

Integrated business planning (IBP) is not a new concept. Yet it’s still hard to find organizations that have fully embrace it, because their efforts have been hampered by the proliferation of legacy systems and data silos. IBP is characterized by aligned planning processes and calendars, full integration of cross-functional data, and cross-functional and business collaboration. In many organizations, sales and operations planning (S&OP) has evolved separately from financial planning. IBP’s goal is to merge the two and produce a holistic plan that considers overall growth and profitability objectives (see Fig. below). 

Identify an IBP Champion

When a company decides to integrate the two, a question arises: Who should be the ultimate owner of IBP, finance or the business?  The S&OP process has typically been driven by business units, whereas financial planning is handled by FP&A, which leads annual and strategic planning, forecasting, performance management and business analysis. Some elements to help make the choice: 

  1. One of the issues many companies face is that their S&OP teams are not adept at translating supply and demand plans into monetary terms due to a lack of understanding about the financial drivers of each service or product. On the other hand, finance leaders may lack operational expertise. 
  2. Executives work under different planning horizons: S&OP runs on a monthly cadence, often with a short-term, quarter-end focus. In contrast, leading FP&A organizations forecast quarterly and take a much longer-term, rolling view (i.e., beyond year-end). 
  3. Finally, the two processes rely on different data and metrics. 

In practice, IBP frequently becomes a finance charter, because FP&A is the center for analyzing corporate performance and has robust forecasting capabilities. To become an effective IBP leader, FP&A must not only expand its view, but also adjust its processes to align them with those of S&OP functions. In addition, it must translate operational metrics into financial ones.

Leveraging New Technologies

For many years, even companies with robust operational and financial planning capabilities muddled through IBP using a patchwork of spreadsheets and manual labor. Today, finance is accelerating the adoption of smart automation solutions that can bridge functionality gaps and enable new capabilities, e.g., next-gen ERPs, RPA, cloud-based dedicated planning and analytics and data and visualization solutions). FP&A can construct a robust technology platform that allows access to operational and finance data, harmonizes KPI definitions and synchronizes planning schedules. 

The Hackett Group’s 2020 Key Issues Study provides evidence of the finance function’s aggressive digitization plans. Finance respondents projected: 

  • A 26% growth in the adoption of data visualization tools 
  • A 24% rise in RPA deployment 
  • A 20% surge in next-generation, cloud-based core finance applications 
  • An 18% uptick in adoption of advanced analytics solutions 

Other contributors to the rapid maturation of IBP include the advent of new data management platforms and technologies, as well as the standardization of master data. Until recently, different parts of the company kept different sets of data in isolated source systems. Data definitions and KPI calculations were incongruent, and data management governance models were decentralized. 

New master data management (MDM) tools are helping companies overcome this problem. In addition, rising adoption of modern data-management platforms enables companies to more easily create single repositories of real-time data. Today, digitally-enabled organizations are implementing data architectures such as data lakes and data marts, which permit fluid collection of data from multiple internal and external sources.

Three Steps for Digitizing IBP 

The transition to an integrated business planning model does not happen overnight, because it requires broad-based participation. Here are some critical steps for those considering adopting this best practice: 

  1. Obtain senior management buy-in IBP is an enterprise-wide initiative that requires new forms of collaboration among different parts of the organization. It must be sponsored by senior management, which should fully understand the relevance and value of the process and commit to executing IBP-driven decisions.
  2. Just get started: It’s easy to delay the rollout of an initiative with such expansive consequences, or to wait until the organization adopts the “right” enabling technology. However, IBP is just as much about process and mindset as it is about systems. Even if spreadsheets still reign at the beginning of the integration process, there is much that companies can do to break down silos and synchronize planning processes. Holding off means losing time and opportunities for improvement.
  3. Leverage and integrate existing meetings when possible: An excessive number of meetings can overwhelm managers and make them less productive. Instead, take advantage of existing scheduled meetings and incorporate IBP into the agenda, making it integral to day-to-day operations. If finance is leading the process, the shift will require a change in its process management. It must join S&OP monthly planning meetings if it is to be effective in driving decisions.

Establishing an IBP process relies on the synchronization of existing planning efforts. That means aligning calendars and devising a common taxonomy to bridge the gap between S&OP and financial planning. Once the processes are aligned, IBP leaders can turn their attention to improving process quality and accuracy.

The full text is available for registered users. Please register to view the rest of the article.
to view and submit comments
Finance Fails to Deliver on Its Business Partnership Promise

By Nilly Essaides, Senior Research Director Finance/EPM at The Hackett Group 

Business partnering is something everyone is talking about right now. The premise is that the more low-value finance tasks are automated, the more time finance practitioners have to work with their “customers” in the business. The only problem is that many business leaders are far from satisfied with finance’s performance to date as a valued business partner.

The Hackett Group data shows that only about a third of finance stakeholders in 2018 perceive it to be a valued business partner. The rest (see image below) see it as much more of a traditional finance function, setting policy, processing transactions and offering financial insight.

What’s more important is the pie on the right: what stakeholders would like to see – a 2.6X increase in finance’s business engagement. Clearly finance has a long way to go.

 

The data looks largely the same for 2016 and 2014. So, there’s no real improvement, despite digital transformation; the broad agreement that the real value finance offers is its collaboration with the business; and the fact that management is asking finance to play a bigger business advice role.

Changing Perceptions

Perception does not necessarily equal reality. It may well be that finance is a lot more engaged with the business today, but its stakeholders have failed to notice. Here are five steps finance can take to alter this perception:

  1. Become more customer-centric. Design-thinking and like techniques used to fall strictly within the purview of sales and marketing. But customer-centricity is now at the core of the new, digitally transformed finance delivery model. That means finance needs to review and revise processes and outcomes by looking at them through the eyes of its various customers; i.e., what information does each segment of stakeholders wants and needs to receive? How frequently, and in what format? For stakeholders to perceive finance’s expanding role, it must deliver its customers the information they need when they need it, and in a format they can easily digest. It may be that interactive visualization is a lot more effective way to communicate with business leaders. Or that business leaders want the information delivered directly to their mobile devices. Increasingly, it also means offering self-service analytics capabilities at the business level.
  2. Allocate more resources. When business partnering is a part time job, it shows in both the level of staff engagement and the corresponding perception on the business end. Assigning enough dedicated resources to partnering demonstrates finance’s commitment. One potential approach is for finance to assign a dedicated partner to each business or region, to ensure business managers know who to contact, and give finance the opportunity to build strong relationships with their peers.
  3. Visit the operations. Finance is moving more resources into service hubs, and away from the business units. That may create the perception that finance is “deserting” the business and turning inward. To counter that perception, it’s important not only to assign a point of contact but physically spend time with operations’ managers, participate in their meetings, listen to their concerns, and provide fit-for-purpose analysis and recommendations, framed within the business KPIs so its message resonates with its business colleagues.
  4. Integrate the business planning process. Integrated or collaborative planning can do a lot to promote finance profile as valued business partner. At leading FP&A organizations, according to The Hackett Group data, finance is the design authority of the integrated planning process; it combines and syncs the operations, marketing, logistics (etc.) planning process with its own, demonstrating its commitment to work closely with the business to set targets and optimize performance.
  5. Actively seek collaboration opportunities. Finance shouldn’t sit around and wait for the business to approach it with a question or a problem. It’s important that finance reaches out to the business frequently, offering its performance analysis and decision-support expertise. By being proactive, finance can add value and build credibility with the business, while demonstrating its commitment to collaborate with business partners.

The reality is that finance rarely measures its value contribution to the business. So, it cannot tell how and where it needs to improve to affect the reality, and perception, of its role as a valued business partner. Collecting metrics of value contribution is not easy. It’s much easier to measure process cost, or number of errors. But there are ways. One possible approach is to track the performance of business projects that have benefited from finance’s recommendations. Another is to track the business processes improvement achieved through finance recommendations. Finance must evangelize its value as a business partner by sharing tangible results and socializing its potential contribution throughout the enterprise. 

The full text is available for registered users. Please register to view the rest of the article.
Who Should Own Enterprise Analytics?

By Nilly Essaides, Senior Research Director Finance/EPM at The Hackett Group 

advanced analytics Advanced analytics is fast becoming a core enterprise competency. Organizations slow to develop its risk falling behind competitors. Companies need quick and reliable insight into the current and future performance of their processes as well as the evolving needs of customers. Advanced analytics is no longer the purview of companies like Google or Amazon. It’s a critical competitive differentiator.

The foundation of advanced analytics is the integrity, diversity and accessibility of big data. The Hackett Group research shows that top performing finance functions are more likely to construct a single source of truth. They have better management and governance policies. Increasingly, they are also leveraging new data management platforms like data lakes and data marts.

Taking Ownership

Analytics is worthless without data. Data is worthless without analytics. So, they combine elements of performance analysis and forecasting (Finance’s realm), with the implementation of enterprise-wide platforms and applications (IT’s realm). Will IT or Finance become the owners of the analytics capability? Perhaps there’s a need for an entirely different service delivery model.

Traditionally, finance analyzed financial data. The functions/business analyzed operations and customer data. That is no longer the case. Finance is looking outside its four walls and pulling in business/operational information.

By integrating the planning and forecasting processes, finance can provide management with greater insight into enterprise performance -- today and going forward. As it comes to better understand how the business works and thus offer effective decision support, business leaders and management can make smarter decisions.

The ultimate owner of the analytics process depends on the delivery model companies use to develop and distribute analyses. Finance is the traditional, and predominant, analytics engine of the company. And since it has expanded its scope, it develops and delivers analytics/reporting to internal and external stakeholders.

However, in many cases, business units and functions also have their own analysts. The advantage of maintaining a hybrid structure is that analytics happens closer to the user/market. The disadvantages are duplication of efforts and the use of disparate systems that don't talk to each other.

The Benefits of Centralization

There are clear benefits to this centralization approach:

  1. It leverages the use of a single analytics solution across the enterprise
  2. It standardizes reporting so everyone is on the same page.
  3. It eliminates duplication of effort in different parts of the organization
  4. It reduces the need for hiring multiple analysts, essentially creating an analytics capability economy of scale.
  5. It helps the COE staff to share knowledge more effectively
  6. It has a clear, enterprise-wide view
  7. It can provide oversight for many companies that are still in the exploration and piloting phase and often initiate discrete projects related to a specific business problem, without coordination and cross-fertilization.

In our 2018 Key Issues Study we found the finance executives expect the amount of analytics work performed by the business to drop by half in the next 2-3 years, while more of the workload will be handled by COEs. Seventy-seven percent of finance executives in a COE poll we conducted last year either already have or expect to have analytics COEs in the next 2-3 years.

So, for now at least, there’s a clear trend toward the concentration of analytics in a single entity that reports into finance or IT. Is that the future?

The Pendulum Swings

After taking pockets of analytics activity and pulling them into a centralized entity, ironically the next phase appears to be a reversion to a decentralized model. As data platforms and robust MDM take hold, it’s possible for anyone (with some restrictions of course) to access the company’s vetted data set. At the same time, the volume of data and analytics activity is becoming overwhelming. It’s too much for one entity.

Hence the growing popularity of self-service analytics tools. Top performing finance organizations are 18% more likely to use them. COEs are pushing some aspects of the process to the users, empowering them to answer their own questions without creating a requests backlog. Just what and how much to push out is still unclear. There are different models for what’s retained in the COE and what’s handled by the consumers of the insight.

The democratization of analytics activities raises more questions about process ownership. The Hackett Group research shows that organizations with a high degree of end-to-end process ownership outperform those with low levels, across efficiency and effectiveness metrics.

Who should then be the process owner for what is an increasingly critical driver of growth and profitability?

What's the Future Analytics Service Delivery Model?

There are different ways to imagine the future:

  1. A COE that sets the guidelines, coordinates and governs analytics activity reporting not to finance but to a senior strategy leader.
  2. A COE that retains the most complex analysis – or in contrast the most standardized repeatable analysis – while handing everything else to the business, reporting into finance or strategy.
  3. A standalone analytics function that “explodes” the COE into a full-fledged organization under the lead of a chief analytics officer reporting to the CEO.

There are probably more.

However, no matter your view of the future of how analysis is created and shared:

(1) it’s already expanded into an enterprise-level capability; and

(2) the emergence of new technologies powered by AI and machine learning will surely cause a radical change in the current service model.

The full text is available for registered users. Please register to view the rest of the article.
to view and submit comments

Pages

Author's Articles

April 1, 2020

Integrated business planning (IBP) is not a new concept. Yet it’s still hard to find organizations that have fully embrace it, because their efforts have been hampered by the proliferation of legacy systems and data silos. IBP is characterized by aligned planning processes and calendars, full integration of cross-functional data, and cross-functional and business collaboration.

April 17, 2019

Business partnering is something everyone is talking about right now. The premise is that the more low-value finance tasks are automated, the more time finance practitioners have to work with their “customers” in the business. The only problem is that many business leaders are far from satisfied with finance’s performance to date as a valued business partner.

February 27, 2019

Advanced analytics is fast becoming a core enterprise competency. Organizations slow to develop it risk falling behind competitors. Companies need quick and reliable insight into the current and future performance of their processes as well as the evolving needs of customers. Advanced analytics is no longer the purview of companies like Google or Amazon. It’s a critical competitive differentiator.

January 25, 2019
FP&A Tags:

Several forces will reshape the way finance will be organized in seven to 10 years. Share your vision and help create alternative models for the future look of the finance function.

Pages