Consultants should look before they leap with AI, but benefit could be huge

13 December 2017 Consultancy.uk

While AI is already revolutionising the way consultants explore data, the industry should be mindful of their business needs rather than adopting technology for its own sake, according to industry experts present at the 2017 Alternative AI conference. The impact of AI on graduate intake and regulatory compliance were also discussed at the event, which took place in London, gathering industry leaders, experts, academics and journalists to consider digital innovation in the UK professional services community.

Around 300 delegates from the professional services industry have attended an event aimed at informing accountancy, consultancy and law firms of the potential of Artificial Intelligence (AI), both in terms of commercial opportunities as well as its potential to transform their own operations. The programme, which took place on the 27th of November, featured a broad mix of strategic plenaries, panel debates, case studies and round table discussions, and showcased how consulting industry players such as PwCKPMGBearingPoint, JLL, CapitaEY and Deloitte are presently incorporating AI into their solutions.

With growing appetites for the use of technology across industries as diverse as manufacturing and healthcare solutions, as many as 5% of global jobs could be set for complete automation in the coming years. Digital disruption is threatening to overwhelm unprepared companies who attempt to leverage revolutionary automation technologies without a long-term plan, however, and so many global companies have been seeking help on the matter, leading to a booming digital consulting market.

However, while top professional service industry players are usually quick to recommend long-term digital strategies to clients, they are also prone to be underprepared themselves, and could well be missing out on the full potential of AI in their own business structures. According to PwC’s UK AI Leader, Euan Cameron, one of the many industry leaders speaking at the conference, consulting is the victim of its own success, as it has relied on caution to deliver top results for generations. Cameron contended, “Traditionally, conservatism has generated value in the professional services industry. Now, though, once the evidence has been collected [to show clients], AI could add huge value to the sector.”Consultants should look before they leap with AI, but benefit could be huge

The event was hosted in London, a location of prime significance, as the UK’s capital has recently witnessed an explosion of start-ups leveraging technology, with as many as 100 law tech start-ups in the city, alone. According to Richard Goold, Global Head of Tech Law at Big Four firm EY, firms which previously had no direct relation with professional services (PS) are moving into the sector now, and have the potential to “eat the lunch of bigger firms,” should industry incumbents fail to adapt to digital technology.

Look before you leap

To that end, conference organisers aimed to give delegates the tools necessary to make informed decisions about AI in a rapidly changing market environment, leaving with reinforced knowledge of the opportunities, threats and potential impact on professional services at the front of their minds.

One of the key themes of the day that ran through multiple talks was the need for experimentation. Amid the heating competition across global markets in all industries, it would be easy for consultants to succumb to pressures to commit hard and early to a particular method or technology in order to get a leg up on competitors. However, numerous sources at the conference warned against leaps of faith, instead favouring periods of experimentation to yield best results.

Speaking in the opening discussion, Peter Waggett, an Emerging Technology Director at IBM, said firms would do well to take a step back to consider their business needs, stating, “What not to do, is just rush out and buy AI. Organisations must research the needs of their business before investing. While the work to adopt AI should begin now, professionals should first work out the right strategy to go forward.”

An industry example of how to get this right was supplied by JLL IT Development and Delivery Services Director for EMEA, Andrew Crow, who spoke about AI-driven valuation tools implemented by his firm. On the subject of putting the cart before the proverbial horse, Crow said, “we absolutely fell into that trap with AI learning,” continuing that JLL had initially let leveraging innovative technologies get ahead of them, before they returned to re-evaluate their business’ needs to build a solution around it.

According to Crow, who said the property consultancy were lucky enough to see the error of their ways after early experiments had not yielded the results they needed, “firms need to be clear about what they have before they think about changing their business model.”Quote Euan CameronIn the use case in question, JLL now leverage an AI analysis system in order to drastically streamline workloads. The real estate consultancy advises on client portfolios that can be from anything between 1 and 100,000 properties, which traditionally took professionals weeks to analyse.

Now, the AI system can compile client data, JLL data and external data into an Azure platform, which scales the information to client demand, using big data statistic algorithms to identify value for those clients. The more the models are used, the more accurate they become, with the machine learning ability of JLL’s system enabling advisors to compile detailed client reports and valuations much more quickly, with greater accuracy, while enabling them to concentrate only on areas of interest, focusing their talents where they would be best applied.

Needles in data-stacks

Following on from this, another running theme at the conference was of AI’s potential to weed out points of interest from the glut of data most firms face in the age of digital information. IBM’s Peter Waggett, who also introduced himself to the conference as a former rocket scientist, gave an example of his time examining climate data, stating, “A lot of the data that has been put out there is not curated, like when a hole was discovered in the ozone layer above Antarctica. I looked at that same data for three years and never saw it,” whereas now, Artificial Intelligence could have sifted through that data en masse relatively quickly to point scientists toward the anomaly in question.

The same case applies to consultants and professional services players. AI has the potential to find needles amid haystacks, as more and more data is gleaned. These functions would take weeks or even months for professionals to examine before points of value could be identified and advised on. However, now technology can point to these areas after minutes of analysis.

Beyond the application of data, another important point made by numerous speakers was the potential for AI to bolster legal compliance efforts, amid a shifting regulatory environment. As they handle an increasing amount of data, firms have become especially vulnerable to major legislation changes, such as the infamous GDPR. EY’s Richard Goold said that the digital trust and ethics questions underpinned by AI presented a major opportunity – as well as a threat – to firms as the regulation of data looks to become more stringent as of May 2018.

Goold argued, “Some medium and even larger companies may even cease to exist because they fail to handle user data appropriated,” but that while some companies potentially undermined their entire operations with such failures, it presented a key chance for start-ups wielding AI to make waves in multiple markets, with more reliable handling of data handled by innovations such as blockchain.

Vijay Rathour, a Partner in the Digital Forensics group at Grant Thornton, gave the use case example from the consulting world of his company using AI to prevent fraud and revenue leakage. According to Rathour, the majority of fraud in the UK is procurement-based, which ultimately ends up on consumers’ plates, or impacting on their wallets. Grant Thornton’s use of scalable AI investigation tools means the accounting and consulting firm can help detect incongruities amid huge data piles.
Speakers during 2017 Alternative AI conferenceRathour said that rather than the traditional, time-consuming, and limited manual procedures of looking through recent records, now, “working with AI, we can examine years of behaviour before focusing human talent on their points of interest it finds.”

Professional service changes

Adopting such revolutionary technology into the heart of firms will not occur effectively without some significant structural changes. While the price of established technology tends to fall quickly, with the potential of AI still being realised, leveraging it can be costly – a price that consultants and professional services firms are keen to avoid passing on to their clients.

KPMG’s Shamus Rae, who is the firm’s UK Head of Innovation and Investment, summarised the strains on firms to provide value for money amid a slowed post-crisis economy, “Pricing hasn’t gone up in the past ten years, and it has been a problem. So why do we think that now we can put prices up in order to recoup investment on AI?”

While services firms might feel justified in commoditising their output due to the upped quality of work, they may still struggle to convince clients of those benefits in a UK economy that continues to enjoy sluggish growth, at best. Subsequently, another area that could be considered for absorbing the cost might well be headcount. While speakers were at pains to downplay the size of this scale-back in recruitment, PwC’s Euan Cameron notably stating that such fears were “overblown” – and that if the base of the pyramid of organisations does shrink, it will not be by much – others seemed to suggest there would be a decrease in trainee and graduate intake of some kind.

Shamus Rae said that over the coming years, client demand will mean intake will have to be maintained. He contended, “CEOs think that there will be more change over the coming three to five years than the past 50,” stating that businesses would have to consult external expertise, and that firms would therefore have to hire to keep up with the glut of digital transformation work.

In the concluding round-table discussion on how AI might change the partnership model, Deloitte UK’s Director of AI & Cognitive Computing, Matthew Howard echoed this, arguing, “Consultants have a key role to play in fulfilling the demands of the market as part of the AI ecosystem – marrying business needs with technology.”

Quote Shamus Rae

One change that he did (hypothetically) foresee, was that AI and technology would see widespread change to the partnership model,  albeit without a total overhaul. “Perhaps,” Howard pondered, “we will see the first data scientist partnerships soon.”

However, beyond that, the future might well see less work at firms in admin and other entry-level areas due to AI. As such, low-level work becomes increasingly self-service oriented for clients, who can receive such provision via subscriptions to AI solution platforms, this would also imply a declining need for the graduates and trainees currently assigned that low-level workload. With the increasingly competitive UK graduate scene proving a popular recruiting ground for professional services firms, such speculation may give rise to concern among future university leavers. 

On the other hand, the implementation of AI might also help to soften the impacts of Brexit on the industry. Leading firms are currently large-scale beneficiaries from the free movement of top consulting talent across EU member states. With that supply suddenly threatened by a no deal scenario, or hard Brexit, Artificial Intelligence may be key to taking up slack, while a new generation of professionals are trained to replace a potential exodus of EU nationals.

In line with this, the UK Government’s autumn budget set aside £75 million for the development of AI – as well as funding of 200 new PhD positions in the field. The budget also saw a further £76 million pledged to boost skills in the digital and construction industries. The developments followed recent criticism that most UK secondary schools did not offer a Computer Sciences GCSE.

Embattled Chancellor Philip Hammond’s spending plan centres on making Britain a technology hub following Brexit, in order to avoid economic shrinkage following the lengthy separation from Brussels. While Hammond suggested the nation already was a “world leader” in cutting edge technology, a new report from the Organisation for Economic Co-operation and Development said the UK was in decline in both terms of top-cited scientific research, and AI inventions.

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Four ways digitalisation is transforming car brands and dealers

16 April 2019 Consultancy.uk

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.”