In 1983, Isaac Asimov was asked to predict the world of 2019, 35 years into his future. It is weirdly disorienting to read his words, somewhat akin to reading George Orwell’s “1984” if you were around to enjoy that serendipity.
He observed that three considerations should dominate their thoughts at the time; Nuclear war, Computerization and Space utilization.
He decided to assume, correctly as it turned out, that there would be no nuclear war. Despite the passage of time, his insights on the impacts of automation (‘computerization’ seems a quaint term now) on society are worth a read, as are his comments on space utilization, which are thought provoking in this era of SpaceX, Virgin Galactic and dozens more. You can read his thoughts here
In looking at the future, it is important to consider not just what may change, but what may stay the same. Maybe what doesn’t kill us can make us stronger!
Our research both explores new thinking and developments and occasionally creates them! We continue to challenge received wisdom with an open mind and we have developed our view on some of the key challenges, trends and opportunities that will absorb our time, and that of our customers, this year. We have had some robust discussion and debate with customers and business partners around the world, as well as leading lights in business, technology, sociology and philosophy! It is enlightening and exhilarating to absorb and consider as many perspectives as possible.
For those who want to delve into a single topic, follow the links below to the relevant section. If you have more time, enjoy the full range of perspectives below:
- Business Transformation & The Role of Digital
- Global ‘End-to-End Process’
- Artificial Intelligence, Machine Learning and Data Science
- Data, Insight and Analytics
- Process Placement, Outsourcing and Offshoring
- Regulatory Change
- Risk and Risk Management
- Technology, Operations and Shared Services
- Sourcing, Procurement and Supply
1. Business Transformation and the role of ‘Digital’
Recent CFO surveys indicate that “growth” strategies are set to overtake process optimization as a CFO priority. However, this seems to slightly confuse an outcome with an enabling strategy. Transformation can be both a customer facing growth strategy and a scalability enabler, to ensure the business can serve the needs of the customer at the right cost. As such, transformation remains on the strategic agenda for CEOs and CFOs. We tend to talk about transformation as a pre-emptive strategy when in practice it is much more commonly a reaction to changing, challenging, even threatening, circumstances. Such transformations represent a fundamental reboot of a company, with the goal of achieving a dramatic improvement in performance in dynamic markets. But transformation is a much-abused term. Maybe this is the year of realisation.
Transformation is often used to describe technology improvements, exploiting the latest tools to drive improved productivity. Whilst all progress is important, these are not the metamorphoses that the word ‘transformation’ describes. The growing evidence is that changing business models are what transforms business. Think about the ‘sharing’ economy of Netflix, Uber, AirBnB. The way in which these businesses view the consumer and their economic customer (not necessarily the same thing) represents a massive shift in business thinking and operation. Consumer convenience enabled by deep intimacy is driving even the oldest businesses to reconsider their models from classic Business to Business marketing and distribution, to a Business to Consumer (B2C) model. The biggest brands that rely on distribution networks are waking up to the fact that they need a direct connection to their consumer, even to survive, let alone thrive. I call this the “Uberization of business”.
2. Global ‘end-to-end’ Processes
Driving consumer intimacy and convenience requires a standard operating model. Even the businesses we like to think of as the most entrepreneurial, operate their consumer facing processes with military precision. It becomes clear that all processes that drive consumer value, and one would hope that they all do directly or indirectly, need the same end-to-end attention. Apple easy”, “Google fast”, and “Amazon convenient” are great watchwords.
Harmonized, simplified, global processes are becoming a necessity not a trendy option. The global process drives a consistent consumer experience, and we will start to see the new Global Process Owner drive both operational excellence today and the new operating model of tomorrow. Common approaches to guide this ‘dual operating model’ of optimised process execution and transformation will emerge.
Despite the agreement on the value of globally integrated, “end to end” processes, for many mature global businesses there is an ‘elephant in the room’. While we all ‘talk a good game’ there are still genuine barriers. Effectively aligning sub-processes that are managed and operated by functions that have differing views of their own value, remains a massive change management challenge. The functional stovepipes of yesterday reinforce the siloed thinking, and functional leaders with different target outcomes and performance measures can be part of the problem. I had my eyes opened to an additional ‘drag’ on change momentum in this area recently, when I was reminded that the offshoring wave had moved much transactional effort to low cost locations, reinforcing the view that these activities were also low value. So ironically, the fact that our ‘strategic’ high cost activities are not co-located with the perceived ‘transactional activities’ has actually been a limiting factor in progress. Alignment is essential for effective end-to-end processes, which themselves are critical for genuine transformation. So, the ‘chicken and egg’ problem is alive and well!
The advent of new and rebranded tools, aligned with powerful marketing, have given us an exciting couple of years of imagining a digital future. None has had a bigger share of attention than Robotic Process Automation (RPA), which continues to morph marketing wise into ‘Intelligent Automation’, whose acronym has raised the profile of many an Internal Audit department! As we pass the ‘peak of inflated expectations’, through the ‘trough of disillusionment’ to eventual ‘plateau of productivity’ (terms courtesy of Gartner’s Technology Hype Cycle), we are learning valuable lessons for the future.
The evidence is clearly that RPA has been largely ‘Robotic Task Automation’, and the massive productivity benefits at a task level do not tend to scale to end to end process improvements, and the ease and ‘freedom’ of agile approaches have been challenged. We have learned that traditional disciplines, of business process understanding, governance, risk management, change management and service management, among others, are critically important in the new world. It has raised the bar on expectations on leadership and talent. RPA is here to stay, as one of the key tools in the toolbox for point integration between systems, eliminating ‘swivel-chair’ frustrations of data integration between Excel and the ERP system, for example.
However, we have also learned that rumours of the death of traditional ERP have been exaggerated, and that our investments in new technology must be matched by our focus on making the current tech work harder. The role of ERP is changing. No longer the “one stop shop” for all “back office” system requirements, the traditional barriers between front and back office are breaking down. ERP is being recognised as the central system of record for key finance and manufacturing processes, with a hub and spoke architecture to integrate the newer industry and process specific applications.
Cloud-based SaaS models continue to gain traction as businesses recognise the value of the hub and spoke architecture, and economics dictate a preference for operational costs aligned to value (pay as you go) rather than over optimistic capital expense business cases with a long tail!
In a recent CFO survey, the single most important digital transformation lever was an interesting ‘league table’;
- Process automation/robotization 45%
- Data analytics 29%
- Leveraging dashboards and visualization 11%
- Moving from paper to digital 10%
- Other 5%
But as ever, the key point is to remember that ‘the best automation is elimination’!
5. Artificial Intelligence, Machine Learning and Data Science
There is much discussion on these topics. Simply put, Machine Learning is the link that connects Data Science and AI.
AI is often confused and conflated with RPA and other technologies, but a different kettle of fish (or discipline’ if you prefer), AI has been with us for a long time now and we experience its value in our daily lives. Exploiting AI does not require us all to hire armies of PhD data scientists, rather we can exploit AI enabled services that already exist. Machine Learning, specifically, is well tuned to a service-oriented SaaS model.
We will see more AI and specifically, Machine Learning, entering enterprise business processes this year. Low hanging fruit includes improving the quality of master data, identifying errors and exceptions and streamlining processes. We are learning the nuances of the AI world and some of the dangers, such as confusing causation with correlation. The availability of large bodies of data has made Machine Learning techniques much more practical than before. With so much data to evaluate, the chances increase that random correlations are discovered by learning models and misunderstood. One such study correlates the age of Miss America and the total number of murders by steam, hot vapours and hot objects and shows a relationship. The lesson? Don’t Confuse Causation with Correlation. On a more optimistic note, there have been some great ideas developing rapidly. The idea of the ‘Generative Adversarial Network’ has been hailed as the ‘coolest thing in Deep Learning in the last 20 years’. In this scheme, two deep neural networks challenge each other to create and improve content, teaching themselves as they go along! The technique has been used to create images and music and is touted as having huge future potential. Maybe AI could develop imagination! Even better, a sense of humour?
Also, often conflated, Blockchain will get productive in business applications such as ‘ethical sourcing’ and will actually become boring this year! But getting past the frothy days of inflated expectations is always a good thing. In response to the somewhat rhetorical question “Blockchain? Or are your pulling my chain?” 31% of CFOs surveyed now feel broadly positive about its potential applications, with 61% taking the diametrically opposite view. As with Machine Learning, the trend seems to be that Blockchain enabled solutions delivered as a service will win out over single entity attempts to deliver value.
6. Data, Insight & Analytics
It is widely reported that up to 80% of finance effort is spent acquiring and preparing data for reporting, leaving as little as 20% for value added analysis and decision making. This is a challenge that automation advances over recent decades were supposed to have resolved. A recent CFO survey asked the question “are your reporting and analytics keeping pace with business demands?”. The answer told a sad story – 37% said yes, and 63% said no. 66% of respondents said that they were consuming too many resources in mining and interpreting data for analysis and decision making. We still have a lot of work to do here.
We have developed concepts and strategies to address the problem, but big challenges remain.
‘Data Lakes’ and ‘Oceans’ are great concepts, but experience indicates that it is easy to re-create the “sediment and sludge” of the 1990’s ‘data warehouse’. Smart, Process-Aware, Self Service Analytics/Business Intelligence may yet prove to be the answer. Analytics, Decisions & Actions need synchronization and alignment.
The ‘Big Data’ moniker has largely been simplified to just ‘data’ We will continue to see a big swing to focus on exploiting available data and creating actionable insight, for the right people at the right time. This is the era of analytics -the time for talk is over – Just Do It!
Data modelling comes back into fashion after 30 years in the cold – data models are the foundation for data exploration and visualisation. It helps frame the what, and thus the why, how, who and where questions to fully understand a business problem.
7. Process Placement, Outsourcing and Offshoring
In the post-digital world, no one cares much about “offshore” as a strategy. It is now just one of the many tactical options. Increasing numbers of traditional outsourcing customers aren’t looking to increase offshore investments. The offshore model is being disrupted by intelligent automation in a similar way Amazon completely disrupted the traditional retail supply chain. The emerging brand of more packaged operational services, outcome based services, and as-a-Service offerings will be much more location neutral.
The process placement discussion remains central to global processes, but the cost arbitrage argument is losing favour as the evidence of smarter ways to automate transitional activity becomes clear.
8. Regulatory Change
There has been a continued growth in consumer driven regulatory change from the “sugar tax”, taxes on single use plastics, to GDPR data protection. The environment and consumer protection remain big themes, and impacted businesses are very focussed on these topics. This looks set to keep regulatory compliance complexity and uncertainty front and centre in 2019.
While compliance functions will shoulder most of the risk burden for new regulations, business operations and internal audit will remain key lines of defence and will need to work collaboratively to ensure that everything is on track for key deadlines.
Brexit concerns continue with the impact of potential outcomes affecting process placement decisions and supplier risk management activities, among others.
9. Risk & Risk Management
Fraud and Cybercrime remain the highest reported systemic risks for CFOs, although economic headwinds, regional trade issues, and consumer demand concerns seem to be spiking as we enter 2019.
Reports indicate that 62 per cent of businesses expect cyber risk to cause disruption within the next three years, yet nearly three-quarters reported poor cyber maturity. Cyber threats have also raised awareness of issues traditionally viewed as ‘internal’, not least the question of identity & authorised user access to corporate data and systems. This is no longer just a joiners, movers, leavers problem, as systems are ever more interconnected, with suppliers, subcontractors, operational partners, service providers and customers all having access in our streamlined end to end processes. This has led to some unfortunate breaches, and organisations becoming aware that up to 20% of the individuals currently authorised to access systems and data have either left their employer or are no longer appropriate for access.
Culture & tone at the top has hit the headlines again in recent months, with CEO behaviour at Uber and others and the artist formerly known as Elon Musk getting into hot water on some “market moving” comments.
Enterprise Risk Management (ERM) has been a long time maturing. We are moving from a world which has been dominated by policy and control, driven in large part by the compliance regimes of the last decade, towards a broader, more holistic approach to understanding and managing risk and opportunity in the business. With the emergence of so many compliance, regulatory and industry requirements, duplication of risk management and controls effort has become commonplace. Now is the time to take a broader view and eliminate redundant or duplicated effort. Enterprise Risk Management (ERM) provides a stable framework for considering risk across the business, and is becoming the language of business decision making and recognising that risk is part of achieving any outcome.
Our view of risk in today’s world needs to recognise that consumers, shareholders, other stakeholders and the world at large, have a growing keen interest in the ‘how’ as well as the ‘what’ of business. This means that financial results are no longer the sole measure of success. Ethics risk is no longer just about our own organisation, but the overall ecosystem including supply chains, service providers, manufacturers and distribution channels. Risk Management now really is a team game!
The Institute of Internal Audit (IIA)’s “Three Lines of Defence model” is undergoing review after 20 years, responding to criticism that it is overly defensive and reactive and does not address the risk/performance dynamic. There is still too much consideration of risk as a ‘compliance’ issue and dealing purely with ‘harms’ rather than the upside of risk. Business opportunities, big and small, are only created by taking risk. There is much debate on this topic, but it reflects a growing appreciation that risk management is just that: ‘management’. It is essentially about increasing the likelihood that business decisions are informed and intelligent. Accounting Today produced a useful summary on the discussion here
When it comes to technology for risk management, there is great interest and some excellent developments in the use of data analytics and process mining, AI and Machine Learning, and the application of Robotic Process Automation. Possibly stimulated by the need to maintain ‘buzzword relevance’, it seems that “ Integrated Risk Management” (IRM) is set to displace “Governance, Risk Management and Compliance” (GRC) as the guiding term for this discipline. I remain sceptical that there is any fundamental shift in thinking, but sometimes labels matter. But other than the psychological impact, does this label change actually offer any substantial advantage?
10. Technology, Operations and Shared Services functions combine under common leadership
CFOs are no longer managing the “rear view mirror” of business and have an important input on technology decisions. The boundaries between technology, operations and shared services are blurring. The concept of Global Business Services, which comes in and out of focus as a trend, embodies a solution to this dilemma.
Looking beyond the needs of today, some organizations have set up “Next Generation” tech labs to cut their teeth on new technologies, although this is nothing new to 2019. However, the last word should be always based on strategic outcomes and overall business priorities with a healthy balanced view on the best recipe and blend of process, people, data and technology. The CIO of the future may very well see their key objectives becoming much less about creating or delivering technological systems, and much more about ensuring the business outcomes through the application of technology, change and data across all business processes, maximising the value from the company’s people assets as well as their technology and data ones.
11. Sourcing, Procurement & Supply
In addition to end-to-end process thinking with “Source to Pay” global process initiatives, there is considerable focus on procurement transformation to speed the process up, drive down barriers, reduce complexity and deliver more value. Agile Procurement methodologies are being developed, to separate high complexity/low agility requirements from those requiring low complexity/high agility, enabling greater automation focus on the latter and expert focus on the former.
Supply and Supplier risk management is taking centre stage, especially in businesses affected by BREXIT implications, as organizations focus on minimising external disruption of any kind. Supplier risk management helps assess and plan for smooth operations independent of the vagaries of individual suppliers, or even whole supply chains. Even changing weather patterns are the subject of supply risk management, both from volatility in consumer demand and at the source of supply.
Controlling spend and reducing fraud remain on the agenda, with considerable effort focussed on better visibility into suppliers behaviour, suppliers sources, reducing maverick spend and driving contract and PO compliance.
Technology is helping deepen supplier relationships, although many transformation programs are foundering on strategy and process issues, having assumed the technologies would drive the outcomes. Chatbots are seeing a rich seam of value as a ‘customer service aid’ to answer those often simple queries that can take up a large part of procurement effort. However, “buyer beware” (no pun intended) in that a Chatbot is purely a user interface. Access to, and availability of, the right data to address the questions is often the core issue.
There is a gap in skills between what we aspire to and what we are, and what we have. How will finance leaders re-invent themselves to embrace and exploit the full potential of new digital technologies, insights, intelligence, and analytics? But it is not just about the new tools and kit, but about a balance with new ways of thinking (innovation & acceleration) and ways of collaborating across the business. New roles such as business partnering are already widespread, but do we have the skills to do these well? Defining the future operating models will force us to work hard to identify the skills we need to hire, develop and retain in an environment where expectations on employment are changing. What are the skills we need in business operations as we extend the reach of global processes and advanced technologies? What is the role and limitation of the ‘gig economy’ in that context? How do we get the level of deep end to end business process skills and knowledge into our business?
We need smart people who are “broad” as well as “deep”; these “T-shaped people” will always be in demand. They have the depth of expertise in one area, but they’ve got the breadth across lots of other domains as well.
Thanks for reading and thanks and credit to contributions from our global customers, CFO.com, The Hackett Group, KPMG, Deloitte, PwC, SharedServicesLink.com, HfS Research, the FCPA Blog, IIA and apologies to anyone I have omitted!