The pace of change in the telecommunications industry seems faster than ever today. That's why it's good to know when to call "time out" and have a map of the concerns, pain points, and perspectives of the main market leaders. Otherwise, we would run a risk as old as contemporary civilization, if we refer to the quote from the Latin philosopher Seneca: "Those who run in a maze are confused by their own speed." EY's latest survey of senior executives around the world in this market, entitled Accelerating the Intelligent Enterprise. The result? Operators must transform themselves, one way or another, with digital technologies as the main driver.
This obligation is in line with IT spending trends in major companies, which continue to evolve in complexity to establish a solid foundation for digitization. "In the coming years, the balance will shift decisively from conventional IT to digital, including new cloud infrastructure, edge computing systems, content delivery networks (CDNs), and other elements." We are talking about four-fifths of the capital that will be invested within a few years (2024), as emerging technologies such as artificial intelligence, analytics, and automation consolidate, which are essential to meet growing customer expectations while offering greater levels of agility and operational efficiency.
The main challenge in all of this, despite progress in all areas and across all companies, is how to reconcile this behavior with profitable growth. "Overall, the digital transformation of the telecommunications industry has not yet translated into sustainable financial gains," the report states. "Revenue growth has fluctuated over the past 10 years, while earnings before interest, taxes, depreciation, and amortization (EBITDA) margins remain low compared to the previous decade." Thus, the underlying task facing telecom leaders today is to find a way out of this pattern.
The EY study identifies five "key" findings, which we will detail below, as follows:
- AI, 5G, and automation are the key technologies driving digital transformation.
- Customer experience is the primary reason for AI, and agility is the key factor in automation.
- Lack of skills, poor data quality, and lack of planning are holding back the transformation agenda.
- Customers and technology are considered the main beneficiaries of artificial intelligence and automation.
- Feelings differ depending on the maturity of the market studied.
Let's take it one step at a time.
1. AI, 5G, and automation are the key technologies driving digital transformation
More than half of the respondents in this survey rated these technologies as one of their top three drivers of transformation. According to the interviews conducted, "5G moves the IoT from being a data network to being a control network. The network becomes more predictable and you can control things, and 5G helps move this control to the cloud. It is vital to restore the value of the connection."
It is striking, however, that other emerging technologies such as blockchain are at a much more nascent stage, with less than 10% of respondents mentioning it. In the case of other technologies that are on everyone's lips, such as quantum computing and edge computing, the responses that place them as key technologies for digital transformation fall below 1 in 20 respondents. In the specific case of blockchain, it is considered valuable for overcoming problems related to data and asset ownership, but its applicability in telecommunications is still unclear. In the case ofedge computing, the study states that its low score is somewhat more worrying, given that it has proven to play an important role in improving data processing and storage in a 5G world.
2. Customer experience is the main reason for AI, and agility is the key factor in automation
Telecom executives are clear: Artificial Intelligence (AI) and advanced analytics are essential for improving and optimizing the customer experience. There is virtually universal consensus on this issue, above other potential benefits identified in the use of these technologies. This is followed, but at a considerable distance (56%), by accelerated business efficiency, and in third place (40%) is the creation of new business models and services. Far behind are other possible applications such as reducing exposure to data loss, improving risk management, and improving forecasting and activity planning.
If there is general consensus around Customer Experience, this agreement is practically unanimous when asked directly about the application of "critical uses" in the next five years. Almost all respondents (96%) say they will be focused on Customer Experience. And in case it is not clear, 7 out of 10 (70%) reinforce this with a use that is often confused: customer service. Far behind are uses such as network behavior management (44%), cybersecurity (22%), and operations (22%).
This is somewhat antithetical to the reasons (drivers) given for adopting these technologies. Here, the customer's voice is distorted, and the most widely accepted reason (59%) is the increase in the agility and scalability of the company and its projects, followed by gains in employee productivity (48%), on a par with, now yes, improved customer service quality. Below that, we find reasons such as optimizing costs associated with low-value tasks and processes, streamlining back-end operational processes, or achieving an "incremental and non-invasive" digital transformation.
3. Lack of skills, poor data quality, and lack of planning are holding back the transformation agenda
But it's not all good news. The main challenges come from the biggest gaps in the market: talent, skills, lack of alignment, and the quality of the data that feeds the machinery driving this transformation.
Specifically, a lack of talent or inadequate skills are overwhelmingly the main weaknesses affecting the deployment of advanced analytics and artificial intelligence. This is cited by two out of three respondents. None of the other weaknesses, although important, reached even half of the consensus. This is the case with the lack of alignment between managers and executives (33%), the low quality of data and metadata (also 33%), and interdepartmental collaboration, cited by three out of ten respondents (30%). Below these, many other reasons are cited that also need to be analyzed: insufficient leadership, overly tight budgets, privacy and security issues, outdated governance frameworks, or issues as "non-digital" as poor relationships with industry partners and suppliers.
That's in terms of adopting analytics and artificial intelligence. If we focus on automation, the main barriers also have to do with a lack of alignment (42%), and even more so with the lack of a long-term "roadmap" (46%). But let's not stop at these two main reasons, because there is a long list of others that are more or less relevant: duplication of processes, whether automated or not (29%), inadequate change management plans or procedures (29%), the inability to prioritize the functions that automation should have (25%), poor alignment of AI/analytics/automation strategies (25%), and very little commitment from those with ultimate responsibility for processes (another 25%).
4. Customers and technology are considered the main beneficiaries of artificial intelligence and automation
And so we arrive at the highest level of specialization, if that term is going to survive in an era in which, as we have seen, increasingly multidisciplinary and interdepartmental functioning will be required. What have we seen to be the main field of application for new technologies? Indeed, the customer experience. Consistent with this, the greatest long-term impact on business functions is expected to fall on areas such as sales and marketing, operations, and customer service. But beware, because it is also estimated that the long-term impact will fall heavily on IT and network departments: three-quarters of the executives surveyed agree.
If we separate analytical disciplines from automation disciplines, clear signs of distinction can also be observed. The contrast is evident between marketing and sales teams and finance and treasury teams. For the former, there is near unanimity (96%) regarding the impact of analytics or AI, but not so much (54%) regarding what will happen with automation. This is the exact opposite of the "hard" teams in companies, where up to 43% estimate that there will be a long-term impact from automation, but only a meager 12% from analytics and AI. Something similar occurs in Human Resources, where the same contrast is perceived between automation (29%) and analytics and AI (4%).
5. Sentiment differs depending on the maturity of the market studied
In contrast, the assessment varies according to market maturity, which in the EY study is divided into two broad categories: developed markets vs. emerging markets. In general, it can be said that more mature markets have greater confidence in advanced analytics and 5G and IoT networks, while emerging markets place more hope in automation, AI, and network virtualization. This can lead to misinterpretations, such as the idea that automation is not important for developed markets. In reality, it is the second most popular technology in these markets, albeit with a lower degree of consensus than in emerging markets.
To understand this, it is worth noting the figures for each segment. Thus, if we take each of these technologies as vectors of transformation, the consensus is distributed as follows (in parentheses, two figures: developed markets – emerging markets):
- 5G networks and IoT (82% – 60%).
- Automation (55%–67%).
- Artificial Intelligence (45%–67%).
- Network virtualization (27%–47%).
- "Penetration" analytics (45% – 13%).
Similarly, there are marked contrasts in relation to what are considered "barriers." For example, data quality, or the lack of alignment between AI strategy and business strategy, are barriers that are much more perceived in developed markets than in emerging markets, while lack of leadership is a more serious barrier in emerging markets. Again, to see this clearly, let's take a look at the figures (developed market – emerging market):
- Lack of personnel, talent, and skills (64%–73%).
- Lack of strategic alignment (45% – 27%).
- Low quality of data and metadata (64%–13%).
- Poor interdepartmental collaboration (27%–33%).
- Insufficient leadership or support (18%–33%).
This comprehensive report by the renowned consulting firm concludes with four steps that, in its opinion, telecommunications companies must take if they want to maximize the value generated by technologies. We take note of these as a closing remark:
- Prioritize mutual reinforcement between the impact of emerging technologies and an informed, holistic mindset.
- Engage and empower the workforce as agents of change.
- Extend AI and automation efforts far beyond the customer.
- Review and update the foundations on which the company's digital transformation is based.
Five key findings and four steps that are designed precisely to ensure that this is not a blind race forward, which is tantamount to running nowhere. Or embarking on a race like the one Seneca warned against: in a labyrinth, with runners confused by their own speed.
Photo byAshley BatzonUnsplash
