Internal auditing ramping up its data science and analytics efforts

25 April 2017

The growing ability to capture, assess and analyse data is spurring audit leaders to rethink their traditional audit models and approaches, according to a study by Protiviti. Data based decision making is the largest area gaining momentum – as it stands, two third of internal audit functions now employ some form of data analytics in audit processes, but, there’s a long road ahead. 

The report, titled ‘Internal Audit Capabilities and Needs Survey 2017’, asked more than 900 internal audit professionals globally to indicate their ambitions and maturity in the area of data analytics. The authors chose to zoom in on the topic in the eleventh edition of their annual survey as data analytics over the years has grown from a hype to a mainstream part of cutting edge operations. “The pace of change in our world is having a dramatic impact on how organisations operate. Internal audit professionals must be adept in applying new tools and techniques to understand and manage risk. The use of advanced data analytic techniques is the runaway winner as a best practice of the future,” remarks Brian Christensen, an Executive Vice President at Protiviti. 

The study finds that data analytics is gaining a foothold in internal audit – two out of three departments utilise the technique as part of the audit process, seeking valuable improvements, efficiencies and insights buried within internal workflows and cultural habits. Compared to a year ago, 73% of the respondents say that demand for analytics related services to support audits has increased, with 20% citing a marked increase. At companies where data analytics is a dedicated part of the governance (i.e. a separate team or function), the growth in demand was significantly higher, at 80%, with an 11% higher percentage score for ‘significant increase’.

Use of data analytics within internal audit

Data analytics maturity

The swift rise in demand and capability uptake means that, across the board, maturity is still relatively low. Most internal audit shops find themselves in their analytics infancy, with a strong majority of respondents judging their analytics capabilities to be at the lower end of the spectrum. Only 10% of those surveyed believe they can place their own performance in the top two maturity stages on a 5-point scale, described by Protiviti as ‘Managed’ (the process is quantitatively managed in accordance with agreed-upon metrics) and ‘Optimised’ (process management includes deliberate process improvement).

The low maturity comes with an opportunity cost, find the authors. According to the survey’s participants, the value that internal audit departments receive from utilising data analytics currently stands at 6.9, indicating that investments are paying off. “Many of the organisations that are already employing data analytics within their audit departments are beginning to experience significant value in the results,” states Christensen. Not surprisingly, the benefits derived from data analytics are found to correlate with maturity. Organisations with a dedicated analytics function score a 7.7, while those positioned in the two highest stages report a score of 8.1. This is according to the researchers the result of a more integrated approach (“they use analytics more pervasively throughout their audit plans and processes, enabling them to glean more value”), and a more dedicated team and skillset in place, among others.

Data analytics maturity within internal audit

“Although they are in the minority amongst their peers, internal audit functions with mature auditing programmes are achieving impressive benefits. These include strengthening risk assessments; more effectively tracking fraud indicators and key operational indicators; enabling a real-time view of organisational risk; and conducting risk-based audits,” comments Christensen.

Continuous monitoring is an important area which separates the wheat from the chaff. The approach, which helps audit functions serve the business more proactively opposed to the traditional retrospective way of working, can add value to a range of dimensions, including risk assessments, audit planning/scoping, the valuation of risk control self-assessments and the monitoring of operational key risk indicators. An area in which its value is heralded to be a potential game changer is in fighting digital and cyber risks, which are costing organisations billions in damages annually, and in turn has spiralled to the top of Chief Finance and Risk Officers’ agenda’s.

Among audit functions that use analytics, only 37% apply continuous auditing. Among organisations that have attained a ‘Managed’ or ‘Optimised’ state of maturity, the uptake of continuous auditing, which is becoming increasingly more feasible as innovative technologies enter the stage, stands at 62%. 

Furthermore, a deeper drill-down, among functions that employ continuous auditing, just 15% deploy “very mature” processes that span the full breadth of the business. “The developments are promising, but more progress with continuous auditing is needed,” says Christensen.

Data quality maturity and challenges

Jumping on the bandwagon

Against the backdrop of the booming technology scene and widening possibilities unleashed by data science, audit executives and managers are betting big on ramping up their analytics capacities. Of the group of respondents that currently do not apply analytics within the audit process, two thirds (64%) say they plan to do so within the next two years, while, among those that have already embraced the methodology, 34% highlight they are planning to add analytics headcount.

The road to a more mature operation is set to however come with a number of challenges. Identifying where data resides is a challenge for 60% of organisations, as are system constraints (56%). The source – data – is an issue as well, with only 22% of the respondents rating it to be excellent or good. Other commonly cited bottlenecks include a lack of defined protocols governing the extraction and usage of data, insufficient ability to objectively analyse data (through for instance benchmarks or industry averages) and legacy IT systems, a feat which complicates data warehousing and analysis down the line.

Value of data analytics for internal audit

Based on the study’s findings and their decade long track record in the domain, Protiviti’s experts have crafted several recommendations that can help those tasked with building more sophisticated analytics processes with overcoming the constraints. At the heart of the advice stands a clear strategy for analytics, supported by the commitment garnered from organisational leaders. This includes having a roadmap in place, including a business case, as well as plans for investment in skills, tools and expertise. Plans should further recognise that demand for analytics is only set to increase in the coming years, paving the way for an accelerated growth path. 

Whilst drafting agenda’s, decision makers are advised to understand the budget and resource constraints, along with business-as-usual workloads, that can limit internal audit’s ability to grow in maturity. The use of carefully chosen and well-crafted pilot programmes herein is key, in particular in realms where even modest demonstrations of analytical prowess can set an influential tone. Teams are further stimulated to explore avenues to expand access to quality data, to implement protocols that govern data management, to either build a team of champions or establish a dedicated function and to implement steps that measure the success / ROI of analytical efforts.

“Using data analytics can be overwhelming for organisations. There may be budget and resource constraints, employees need to learn new technologies and new processes need to be developed. We’ve found that companies need to pick a starting point and get the help they need so that, over time, they can truly optimise their internal audit functions,” concludes Christensen.

A recent study from EY found that legacy IT is mounting pressure on reporting effectiveness, while another white paper on data highlighted that also the HR function is increasingly embracing HR analytics and reporting.



Four ways digitalisation is transforming car brands and dealers

16 April 2019

From changing expectations from the customer to new stakeholders entering the industry, the digital transformation of global automotive industry means it is facing the wholesale transformation of its business model. In a new white paper, global consulting partnership Cordence Worldwide has highlighted four major digital trends that are transforming the relationships between car brands and dealers with consumers.

With digital transformation drives booming across the industrial spectrum, automotive groups are no different in having commenced large digital transformation programmes to improve productivity, efficiency, and ultimately profitability. Falling sales figures mean the automotive sector is facing an increasingly difficult road ahead, something which means companies in the market are even more hard pressed to find new ways to improve their bottom lines.

While it offers major opportunities, the industry’s move to digitalise is not without complications. It has triggered a series of major internal changes, which have presented automotive entities with the challenge of becoming a “customer-oriented” industry. A new report from Cordence Worldwide – a global management consulting partnership present in more than 20 countries – has explored how automotive companies are navigating the rapidly changing nature of digital business.

New business models

The level of change likely to be wrought on the automotive industry by digitalisation is hard to overstate. Automation could well lead to significant reductions in the number of accidents, higher vehicle utilisation and lower pollution levels, while leading to a $2.1 trillion change in traditional revenues, with up to $4.3 trillion in new revenue openings arising by 2030.

As a result of this colossal opportunity, it is easy to see why almost all automotive groups now have digital departments, with generally strong communication within the digital transformation and the customer approach. The changes to society which this may have are potentially distracting automotive firms from the change it is leading to in its own companies though, according to Cordence’s paper.

The automotive market is dead, long live the mobility market

Because of this, the sector’s business model is set to transform over the coming decades. With digitalisation speeding up the appearance of concepts such as car-sharing, a subscription package model will likely become more palatable. At the same time, car and ride-sharing models will cater to the sustainability criteria of millennials, who will rapidly become one of the automotive market’s leading consumer demographics in the coming years.

Antoine Glutron – a Managing Consultant with Cordence member Oresys, and the report’s author – said of the situation, “These ‘old school industries’ are now working on creating new opportunities, but in so-doing are facing challenges and threats: new jobs, new technologies, new ecosystem of partners, necessary reorganisation, different relationship with customers, and even new businesses. The customer approach topic is in fact a real challenge for car companies as it implies changing their business model and adjusting their mind-set to address the customer 4.0: from product-centric to customer-centric, from car manufacturer to service provider.”

Digital customer experience

In the hyper-competitive age of the internet, even top companies face an uphill challenge when it comes to holding onto customers through brand loyalty. Digital disruption has resulted in changes to consumer behaviour, which is forcing a range of marketing strategists to reconsider their old, possibly out-dated strategies. As modern customers wield an increasingly impressive array of digital tools and online databases, they and are now able to quickly and conveniently compare prices, check availability and read product reviews.

The automotive sector is no exception to this trend, according to the study. In order to adapt to the needs of the so-called ‘customer 4.0’, car companies will increasingly need to change their business model and move away from product-centric companies to customer-centric ones, from car manufacturers to service providers.

Glutron explained, “As an automotive company, you can no longer expect customer loyalty simply with good products; you must conquer and re-conquer a customer that “consumes” your service. The offer now has to be global, digital and personalised. Your offer has to be adapted to this customer’s needs at any given moment. A key issue related to data control is to build customer loyalty by creating a customer experience 'tailored' throughout the cycle of use of the 'car product': purchase, driving, maintenance and trade-in of the vehicle.”

One way in which the sector may be able to benefit from this desire for a tailored experience is via connectivity. Consumers are generally positive about new connective features for automobiles, and many are even willing to pay upfront for infotainment, emergency and maintenance services. Chinese consumers, where the connected car market is set to hit $216 billion, are already particularly interested in paying a little more for navigation and diagnostic features in their future new car. This can also enable automotive companies to exploit a rich vein of customer data, enabling them to rapidly tailor their offerings to consumer behaviour.

New automotive segments

Digital transformation has also brought with it the rise of completely new application areas. As mentioned earlier, the most well-known example is the autonomous or self-driving car, where the last steps forward were not taken by major automotive groups but by technology companies such as Tesla. While this may have given such firms the edge in the market briefly, a number of keystone automotive names will soon be set to take the plunge into the market themselves, leveraging their car manufacturing prowess and huge production capacities to their advantage.

Before companies rush to invest in this market, however, it is worth their while to remember that the readiness and uptake for such vehicles differs greatly geographically. For example, following a study published in 2018, 92% of Chinese would be ready to buy an autonomous car, compared with only around 35% of drivers in France, Germany and US. Meanwhile, the infrastructure of different nations will also be significantly less accommodating of the new technology.

Use digital for steering thr activity

Elsewhere, Cordence’s analysis has suggested that hooking the cars of tomorrow into the Internet of Things is also likely to see a rapid change in the business model for car maintenance, providing real-time diagnostics for problems. This presents chances for partnerships to improve the connectivity of cars, especially with tech companies; for example, PSA partnered with IBM for a global agreement on services in their vehicle. Meanwhile, data could also be sold to other parties with an interest in this data, such as the government, which could use it to manage traffic levels, or ensure that only adequately maintained vehicles take to the road.

Glutron added, “With the increase in the amount of client data and connected opportunities, the recommendation is to set up data-centric approaches. The value is now in the customer data. The general prerequisites are to rework the data model and the Enterprise Architecture and generally build up a data lake including data from all sources (internal and external, structured and unstructured).”

From automotive to mobility

Relating further to the idea of connectivity, the report claimed that automotive firms must now adjust their models in line with the provision of end-to-end mobility, rather than treating the sale of a car as an end point in their relationship with the customer. In order to realise this transformation, transformations are likely to become more and more important.

A network of partner companies means automotive firms can provide a global mobility experience. As the vehicle is increasingly connected to its environment, new partners can also be cities, governments, and other service providers within the global mobility services industry in which the car brands want to take part.

According to the study, the target is clear. Companies must look to a holistic transport service, offering to move customers from A to B in a unique and pleasant way – otherwise they might as well take public transport. At the same time, they should extend the services reachable “on-board” (especially the enhancement of the connectivity between the car and smartphones or other connected devices), and reach high standards in terms of user experience (online sales, online payment, customised experience during and after the use of the car).

Concluding the report, Glutron stated, “These mobility market transformations could be considered a threat for the car manufacturers. Quite the opposite: if they take up the challenge and review their business model so that they become the service provider – communicating no longer to a driver but to a ‘mobility customer’ – they can then take advantage of their expertise and their position as a historical player. The most convenient means of transport are cars, and building a car is highly-skilled work.”