Enhancing the tech backbone

By making the right investments in this foundational asset, industrial companies will be better positioned to take advantage of next-generation, data-driven tech solutions.


Most industrial companies struggle to quickly and effectively deploy technology solutions for their customers and internal business functions. All too often, new technology-enabled initiatives—such as aftermarket solutions to create new revenue streams, Internet of Things (IoT) platforms to improve the efficiency of manufacturing processes, or analytics use cases that could transform core operations—fall short of expectations. One key reason is that a company’s tech backbone is outdated, inflexible, or insufficiently resilient to support the requirements of next-generation technologies.

Why is a tech backbone so critical to operations—to say nothing of a tech-enabled transformation? In short, the tech backbone manages the storage, aggregation, analysis, and provision of data across the organization. Companies with obsolete legacy systems face significant challenges in consolidating data from different sources, maintaining consistency and quality, and making the necessary updates within the required timelines. And because solutions based on analytics, AI, and the industrial IoT all rely on unfettered access to comprehensive, high-quality data to generate business insights, an inadequate tech backbone will severely limit the impact of these technologies.

Well-considered investments in upgrading the tech backbone can generate real value. Industrial companies that successfully modernize their tech backbones can improve efficiency of their end-to-end tech solutions by more than 20 percent. Further, optimized systems can be more than 20 percent cheaper to operate and maintain in addition to being more resilient and secure.

So how should industrial companies move forward? The path will be shaped by a company’s strategy and its starting point—each organization has its own advantages and obstacles to overcome. We have identified three archetypes for enhancing the tech backbone, from a complete overhaul of foundational systems to a more surgical approach. By explicitly connecting tech-backbone upgrades to specific use cases and priority domains, industrial companies can ensure these efforts translate into business value.

The elements of the tech backbone

As a first step, industrial companies must assess the current state of their tech backbones. Understanding what its elements are and how they work together to power technology solutions can help business leaders gain clarity on where they are falling short.


Core systems and integration architecture. To design, manufacture, and service a new product, multiple systems must work together effectively. With the right integration layers, critical data elements (for example, engineering data, manufacturing data, and bill of materials) can seamlessly move between the core systems of record—which include enterprise resource planning, product life-cycle management, and manufacturing execution systems—to create a “digital thread” from engineering to servicing. Furthermore, the divide between information technology and operational technology can be bridged to enable data exchanges across both areas. An effective integration architecture prevents manual rework, allows products to be brought to market faster, and supports data-driven decision making.

Data management and storage. To support operations and make better decisions, the way companies manage and store data must be improved. This effort applies to master both customer and product master data as well as transactional data that is often stored across many different systems. An effective tech backbone successfully manages data across the full ecosystem to provide relevant, quality data in an efficient way. Companies should define the “golden sources” of record for master data and set up a data warehouse, data lake, or other fit-for-purpose data-storage solution. Managing data correctly in the tech backbone significantly improves reporting quality, the performance of analytics, and overall business operations.

An API ecosystem. Application programmable interfaces (APIs) enable the IT function to conveniently build and implement new applications in the ecosystem. Having the right integration architecture and data-management capabilities is critical to effectively connecting the existing software solutions in the backbone. With the right API ecosystem, applications can be built and refined in days rather than months. APIs can seamlessly build on the data foundation and existing system functionality, which allows customer-facing domains (for example, aftermarket services) to respond flexibly to customer requests and new business needs.


The tech backbone manages the storage, aggregation, analysis, and provision of data across the organization.


Next-generation approach to hosting and infrastructure delivery. The software solutions and data need to be stored on the right infrastructure (such as servers and networks). In the past, many companies avoided their own data centers and hosting solutions. With next-generation cloud solutions, companies can design and implement infrastructure that features unprecedented cost efficiency and security. In the past, companies would sometimes need weeks to execute new servers. Now, however, the latest infrastructure offerings reduce provisioning time to mere minutes.

Agile execution model. The tech backbone is one critical building block for faster and more effective solution delivery. However, new hard- and software solutions alone are not enough; IT and business employees will need to work together using agile delivery methodologies to unlock their full improvement potential. If the infrastructure allows for multiple releases a day, for example, the joint business and IT teams must be able to coordinate their activities to capture the business improvements that come with this ability.

Secure environments. Organizations must ensure that the faster and more efficient delivery of software and analytics solutions doesn’t result in higher security and safety risks. The tech backbone needs to be designed and built to better protect intellectual property, sensitive data, and the overall stability of the systems. Companies that integrate information security effectively into the design and maintenance of the backbone can strengthen infrastructure security while retaining the necessary flexibility to support their operations. Furthermore, this can be done without increasing the cost of deployment and maintenance.

Challenges to improvement efforts

Once industrial companies have identified the gaps in their current tech backbone, as well as the necessary improvements to support business strategy, they must take on a more difficult task: overcoming the entrenched obstacles standing in the way of a renewed tech backbone. Several challenges can obscure a clear path forward.

First, changes in the backbone should always directly support business value. However, companies often struggle to determine which elements in the tech backbone are critical to support specific use cases or priority domains. The seemingly continuous procession of new solutions can also overwhelm organizations. Companies can get too fixated on technologies and software rather than asking how specific capabilities and features can help make a broader impact on the business.

In addition, companies can be discouraged by the scope of and commitment to renewing the tech backbone. It is usually a multiyear journey that requires significant investment, and a multitude of dependencies make it difficult to decide where to start. Specifically, if a company has limited funds, the key question is which changes should be made now rather than later. The complexity of a backbone transformation is characterized by a multitude of interdependencies and tight timelines. As a result, companies often fail to develop an integrated architecture plan and comprehensive road map. Overly long cycles (such as a yearly cycle rather than quarterly or monthly) and weak program management further hinder progress and execution.

Last, companies frequently overlook the work required to gain consensus with stakeholders. Backbone transformations are costly and require support across the organization. If stakeholders don’t understand the need and impact of the work, funding and support for these initiatives can falter when priorities change.


As a result of these challenges, we usually see two types of failures:

  1. Companies make investments in technology without demonstrating value in digital or analytics use cases or clearly articulating a long-term vision. This approach usually means that an organization’s large investments have little or no impact.

  2. Organizations create digital or analytics solutions without investing in the backbone, meaning that promising solutions cannot be scaled across the enterprise. As a result, many companies have found themselves in “pilot purgatory,” where multiple pilots run in parallel without enhancing each other and with no clear path to enterprise-wide application.


To avoid these types of failures, companies should ensure their backbone renewal efforts embody the following principles:


Link any improvements to business value. Replacing any part of the tech backbone without understanding how upgrades will help generate value for the business (in the form of increased revenues, reduced costs, or better performance) will risk the success of the overall transformation. Companies must recognize the importance of foundational elements. These elements may not appear to be directly linked to a business initiative, but they ultimately help accelerate the delivery of business solutions or otherwise improve a business- or customer-facing project. Understanding these motivators is important for the success of a backbone transformation.

Define the road map and vision for the backbone. Without a compelling vision for why the tech backbone must evolve and the path to improvement, every transformation will fail. Companies must articulate the vision and road map and then use these pieces to gain buy-in from stakeholders. To focus these efforts, business leaders should identify the capabilities or solutions they want to support during the next two to five years. For example, if a company is interested in developing a digital experience for customers that is tied to its products, then the transformation should concentrate on enabling connected products.

Establish a transformation office. A backbone transformation is a significant undertaking that touches many different IT and business functions and requires assistance from external parties: vendors that can help build and refine the backbone as well as the potential suppliers and partners that will connect to it. Therefore, a dedicated and well-resourced transformation office is critical to guide the transformation. This office should deploy an agile development approach to ensure that the road map is executed correctly and achieves the expected business value.1

Use a layered architecture. The tech backbone needs to remain flexible so that it can accommodate changing business needs and support growth (exhibit). The layers of successful architecture include core systems of record (data management), integration, and APIs. When assembled appropriately, these elements will enable greater flexibility.


Renewing the tech backbone: Three strategies

There is no single recipe for success in transforming the tech backbone. Indeed, the starting point depends on several factors: the current state of an organization’s backbone, the prioritized list of use cases, and internal capabilities (including talent). The trick is to balance immediate needs with long-term plans—all while ensuring the organization continues to operate with minimal disruption. Companies, both within industrials and across other industries, have followed three strategies successfully: the first involves a more ambitious overhaul of foundational elements of the tech backbone, while the other two are ways to improve the performance of the existing backbone in the short term.

1. Replace core systems of record

Some companies start to transform the tech backbone by strategically replacing core systems of record first and planning their new backbone around the enhanced capabilities. These systems are costly and difficult to replace, so this strategy requires a significant and sustained commitment of resources to be successful.

One large OEM, for example, recognized its outdated core systems of record were an obstacle to improved productivity. Rather than building work-arounds, executives decided to systematically replace its legacy systems to achieve company-wide data consistency. It also did a greenfield build of an integration layer around those new applications. This road map sought to transition the company to the target state over a five-year period and included milestones. Done right, we have seen that these transformations can generate a return on investment (ROI) of more than 20 percent.


2. Abstract data and APIs

In the event that replacing the core systems of record is not feasible, companies can start by transforming the data and API ecosystem. This approach involves creating a new data and API layer on top of legacy systems. Companies can thus gain greater access to data and quickly develop and deploy new solutions. By investing in this work-around, industrial companies can make immediate progress.

One large pharma company with dozens of fragmented legacy systems decided to build a highly structured data lake that could collect critical data and make it available for digital applications through advanced APIs. With this strategy, the highly fragmented legacy system was effectively “shielded” from the new digital landscape. In addition, the company was able to achieve performance improvements without immediately replacing core systems of record (a step that would still need to happen at some point).


Done right, these transformations can generate an ROI of more than 20%.


3. Adopt an agile delivery methodology

Some companies decide to first address the delivery methodology. These companies can include organizations with poor delivery processes as well as those that lack the funding to make larger technology changes. Once they have built the processes and capabilities to accelerate development cycles, organizations can start to address the underlying tech backbone to remove the respective bottlenecks.

A bank decided to implement an agile delivery methodology before replacing any of its systems. The plan was to ensure development teams were trained to be customer focused and build software solutions faster and more effectively. DevOps (development and operations) and other technology methodologies were introduced to further shorten delivery cycles. Through this approach alone, the bank achieved cost savings of more than 10 percent in software delivery as well as much shorter deployment cycles. This effort laid the methodological foundation to ensure the organization had the capabilities in place to start addressing its system challenges.


In any transformation, choosing the right path is critical. Given the complexity of the tech backbone, a company can start by conducting an assessment of the status of its current backbone as well as the most critical business initiatives and corresponding tech requirements. This assessment can help the company develop a portfolio of initiatives, which can be used to build a business case for investments in backbone upgrades—an important element to gain stakeholder support. Companies should then move as quickly as possible on initial use cases by drawing on existing data (rather than waiting until the data is ready). This test-and-learn approach enables companies to make smarter investments, move faster, and develop better solutions.

Industrial companies that can successfully transform their tech backbones will have a crucial asset to not only power emerging solutions but also respond more rapidly to new opportunities.


COVID-19 has pushed companies over the technology tipping point—and transformed business forever

Image by Luca Bravo

In just a few months’ time, the COVID-19 crisis has brought about years of change in the way companies in all sectors and regions do business. According to a new The Jeeranont Global Survey of executives,1 their companies have accelerated the digitization of their customer and supply-chain interactions and of their internal operations by three to four years.


And the share of digital or digitally enabled products in their portfolios has accelerated by a shocking seven years.2 Nearly all respondents say that their companies have stood up at least temporary solutions to meet many of the new demands on them, and much more quickly than they had thought possible before the crisis. What’s more, respondents expect most of these changes to be long lasting and are already making the kinds of investments that all but ensure they will stick. In fact, when we asked executives about the impact of the crisis on a range of measures, they say that funding for digital initiatives has increased more than anything else—more than increases in costs, the number of people in technology roles, and the number of customers.

To stay competitive in this new business and economic environment requires new strategies and practices. Our findings suggest that executives are taking note: most respondents recognize technology’s strategic importance as a critical component of the business, not just a source of cost efficiencies. Respondents from the companies that have executed successful responses to the crisis report a range of technology capabilities that others don’t—most notably, filling gaps for technology talent during the crisis, the use of more advanced technologies, and speed in experimenting and innovating.

Digital adoption has taken a quantum leap at both the organizational and industry levels

During the pandemic, consumers have moved dramatically toward online channels, and companies and industries have responded in turn. The survey results confirm the rapid shift toward interacting with customers through digital channels. They also show that rates of adoption are years ahead of where they were when previous surveys were conducted—and even more in developed Asia than in other regions (Exhibit 1). Respondents are three times likelier now than before the crisis to say that at least 80 percent of their customer interactions are digital in nature.

Perhaps more surprising is the speedup in creating digital or digitally enhanced offerings. Across regions, the results suggest a seven-year increase, on average, in the rate at which companies are developing these products and services. Once again, the leap is even greater—ten years—in developed Asia (Exhibit 2). Respondents also report a similar mix of types of digital products in their portfolios before and during the pandemic. This finding suggests that during the crisis, companies have probably refocused their offerings rather than made huge leaps in product development in the span of a few months.

Across sectors, the results suggest that rates for developing digital products during the pandemic differ. Given the time frames for making manufacturing changes, the differences, not surprisingly, are more apparent between sectors with and without physical products than between B2B and B2C companies. Respondents in consumer packaged goods (CPG) and automotive and assembly, for example, report relatively low levels of change in their digital-product portfolios. By contrast, the reported increases are much more significant in healthcare and pharma, financial services, and professional services, where executives report a jump nearly twice as large as those reported in CPG companies.

The customer-facing elements of organizational operating models are not the only ones that have been affected. Respondents report similar accelerations in the digitization of their core internal operations (such as back-office, production, and R&D processes) and of interactions in their supply chains. Unlike customer-facing changes, the rate of adoption is consistent across regions.

Yet the speed with which respondents say their companies have responded to a range of COVID-19-related changes is, remarkably, even greater than their digitization across the business (Exhibit 3). We asked about 12 potential changes in respondents’ organizations and industries. For those that respondents have seen, we asked how long it took to execute them and how long that would have taken before the crisis. For many of these changes, respondents say, their companies acted 20 to 25 times faster than expected. In the case of remote working, respondents actually say their companies moved 40 times more quickly than they thought possible before the pandemic. Before then, respondents say it would have taken more than a year to implement the level of remote working that took place during the crisis. In actuality, it took an average of 11 days to implement a workable solution, and nearly all of the companies have stood up workable solutions within a few months.

When respondents were asked why their organizations didn’t implement these changes before the crisis, just over half say that they weren’t a top business priority. The crisis removed this barrier: only 14 percent of all respondents say a lack of leadership alignment hindered the actual implementation of these changes. Respondents at both B2B and consumer-facing companies most often cite a failure to prioritize as a barrier, but the responses to other challenges differ. Nearly one-third of B2B respondents say that fear of customer resistance to changes was a barrier, but only 24 percent of those in consumer-facing industries say this. After these two challenges, B2B executives most often cite organizational and technology issues: the required changes represented too big a shock to established ways of working, IT infrastructure was insufficient, or organizational silos impeded commitment to and execution of the required changes.

The largest changes are also the most likely to stick in the long term

Of the 12 changes the survey asked about, respondents across sectors and geographies are most likely to report a significant increase in remote working, changing customer needs (a switch to offerings that reflect new health and hygiene sensitivities), and customer preferences for remote interactions (Exhibit 4). Respondents reporting significant changes in these areas and increasing migration to the cloud are more than twice as likely to believe that these shifts will remain after the crisis than to expect a return to precrisis norms.

Respondents report that the crisis spurred shifts in their supply chains as well. The nature of these shifts varies significantly by sector, and they have taken place less quickly than other changes because of contracts that were already in place before the pandemic. Respondents in consumer-facing industries, such as CPG and retailing, often cite disruptions to last-mile delivery (that is, who interfaces directly with customers). Other shifts, such as building redundancy in the supply chain, are reported more often in sectors that create physical products.

The results also suggest that companies are making these crisis-related changes with the long term in mind. For most, the need to work and interact with customers remotely required investments in data security and an accelerated migration to the cloud. Now that the investments have been made, these companies have permanently removed some of the precrisis bottlenecks to virtual interactions. Majorities of respondents expect that such technology-related changes, along with remote work and customer interactions, will continue in the future. Nearly one-quarter of respondents also report a decrease in their physical footprints. This signifies a longer-term shift than would likely occur among the 21 percent reporting a drop in their number of full-time equivalents—at some companies, that could represent a temporary move in the earlier days of the crisis. What’s more, when we asked about the effects of the crisis on a range of company measures (including head counts), respondents say that funding of digital initiatives has increased more than anything else—more than costs, the number of people in digital or other technology roles, and the number of customers.

We also looked at the underlying reasons some changes would or would not stick: their cost-effectiveness, ability to meet customers’ needs, and advantages for the business. In addition, we examined the relationship between the length of the crisis and the permanence of the changes as “new” becomes “normal” over time.

Of the 12 changes, remote working and cloud migration are the two that respondents say have been more cost effective than precrisis norms and practices. Remote working is much less likely to meet customer expectations better than it did before the crisis; the changes that have done so best are, unsurprisingly, responses to the increasing demand for online interactions and to changing customer needs. Investments in data security and artificial intelligence are the changes respondents most often identify as helping to position organizations better than they were before the crisis. Across these changes, remote working is the likeliest to remain the longer the crisis lasts, according to 70 percent of the respondents.

Technology-driven strategy for the win

We’ve written before about the need for digital strategies to be true corporate strategies that take digital into account. And from earlier research, we know that at leading companies, digital and corporate strategies are one and the same. The COVID-19 crisis has made this imperative more urgent than ever. While the alignment on overall strategy and strong leadership have long been markers of success during disruptions or transformations, the extent of technology’s differentiating role in this crisis is stark (Exhibit 5). At the organizations that experimented with new digital technologies during the crisis, and among those that invested more capital expenditures in digital technology than their peers did, executives are twice as likely to report outsize revenue growth than executives at other companies.

The results also indicate that along with the multiyear acceleration of digital, the crisis has brought about a sea change in executive mindsets on the role of technology in business. In our 2017 survey, nearly half of executives ranked cost savings as one of the most important priorities for their digital strategies. Now, only 10 percent view technology in the same way; in fact, more than half say they are investing in technology for competitive advantage or refocusing their entire business around digital technologies (Exhibit 6).

This mindset shift is most common among executives whose organizations were losing revenue before the crisis began (Exhibit 7). Those reporting the biggest revenue hits in recent years acknowledge that they were behind their peers in their use of digital technologies—40 percent say so, compared with 24 percent at companies with the biggest revenue increases—and also say that, during the crisis, they have made much more significant changes to their strategies than other executives report.

What’s more, respondents say that technology capabilities stand out as key factors of success during the crisis. Among the biggest differences between the successful companies and all others is talent, the use of cutting-edge technologies, and a range of other capabilities (Exhibit 8). A related imperative for success is having a culture that encourages experimentation and acting early. Nearly half of respondents at successful companies say they were first to market with innovations during the crisis and that they were the first companies in their industries to experiment with new digital technologies. They are also more likely than others to report speeding up the time it takes for leaders to receive critical business information and reallocating resources to fund new initiatives. Both are key aspects of a culture of experimentation.

The notion of a tipping point for technology adoption or digital disruption isn’t new, but the survey data suggest that the COVID-19 crisis is a tipping point of historic proportions—and that more changes will be required as the economic and human situation evolves. The results also show that some significant lessons can be drawn from the steps organizations have already taken. One is the importance of learning, both tactically, in the process of making specific changes to businesses (which technologies to execute, and how), and organizationally (how to manage change at a pace that far exceeds that of prior experiences). Both types of learning will be critical going forward, since the pace of change is not likely to slow down.

Image by Lenin Estrada
jee design .png

Winning tomorrow’s car buyers

using artificial intelligence in marketing and sales

AI holds great potential for the automotive industry. Here’s what you need to know about its applications in marketing and sales.

Jeeranont AI
The Jeeranont

Issued by The Jeeranont Company Limited is authorised and regulated in the USA by the Financial Conduct Authority. UNITED STATES OF AMERICA