A View From The Corner Office
April 5, 2023
#DigitalTransformations in their fundamental form aim to reduce a reliance on people, maximize the use of digital tools and algorithms to support better decision quality and reconfigure the enterprise to support a new business future state that represents a discontinuity from its past past trajectory. Atleast, so the marketing/PR campaigns of the sponsor companies proclaim to their stakeholders.
A more tangible message to shareholders talks about transformation initiatives being launched with the dual promise of reducing structural costs, and supercharging growth.
Indeed evidence from our Digital Transformation research identifies operating cost reduction and margin improvement as the primary “low-hanging fruit” goals of nearly every company’s DT objective, however implicitly stated.
Budget re-allocations that involve investments in new hiring and related opex spend focused on employee training/reorientation programs combined with targeted layoffs, are executed to achieve the necessary churn of skill-sets to the one that aligns with the enterprise future state. All this to support the above stakeholder commitments.
Investors almost always react positively to such Digital Transformation announcements and signal their approval of this enterprise future state by triggering an improvement in the company’s stock price & market valuations. Of course, Wall St.investors are far happier when such initiatives are followed up with announcements of substantial layoffs – a cumulative reduction in the operating expense line.
Margin improvement and cost reduction impact of digital transformations among our target cohort of industrial players are clearer to identify. They are routinely and closely tracked as part of our analyst research.
Assessing and judging growth impact attributions of digital transformations directly from publicly disclosed data however can be a noisy exercise. Snapshots of revenue trajectories pre (launch announcements) and post initiative ( 2+ years in flight) scatter companies into diverse groups. While this pattern is not uncommon, the effects of extraneous factors and near-term events (such as normal macroeconomic cycles, Covid pandemic effects, the systematic industry cycle) further muddy up the picture forcing several economic adjustments. Industrial (and industrial-allied) players have broadly made good strides in revenue in their normal business trend.
#MONETIZATION – That Unspoken Elephant In The Room
Almost all industrial Digital Transformation players chosen narratives that include the promise of unleashing ambitious new revenue streams enabled by “servitizing” their physical products, and by “productizing” their service offerings.
Assessing and judging growth impact attribution of digital transformations uncover a fork in the road that separates the highly ambitious players, from the not so ambitious ones.
Early results indicate a mix of strategies to deploy new #analytics-enabled products and services. Early results also indicate companies have had mixed success in #monetizing them. This may well be due to the fact that
(A) some industrial companies jumped too early on the DT bandwagon without working through a rigorously tested hypothesis about their path to tangible outcomes; or,
(B) it may well be too early to expect tangible results, if at all.
Nevertheless, its evident some players are yet to demonstrate they can leverage digital transformation initiatives into successful monetization strategies.
A rigorous examination of industrial transformation success demands a combined commitment of time and attention of the same managers who until recently were heads down for weeks and months implementing changes and solutions identified in their digital transformations roadmap.
It also requires that the same operating personnel confront outcomes of their own efforts impassionately and judge what worked and what mostly didn’t, using an objective benchmark. This is often a big ask when promotions, pay-raises, bonuses and newer career prospects (at other employers) hinge on this. More importantly, its a challenge to re-engage them once they have dismantled project-teams/ war rooms and regrouped back into their regular operating roles.
Its not surprising therefore that consultants and analysts who spent so much energy in the press putting out large ambitious market opportunity and TAM numbers in the early part of the cycle, rarely have anything substantial to say about the success and failure of large scale digital transformations barring passing references and aggregated survey charts with little actionable insight.
Assessing success of digital transformations also requires the rigor of highly structured methodologies, and it helps to use the independence of an advisory firm with deep expertise in working with companies to guide the process.
TESTING THE GROUND REALITY OF INDUSTRIAL DIGITAL TRANSFORMATIONS
There are several tests necessary to ascertain success of of successful industrial digital transformations. While most are familiar to industrial players, the tests aren’t often applied with significant deliberation.
Nevertheless its important we remind ourselves once again of the tests that are necessary for a successful digital transformation.
1: WIDE IMPLEMENTATION OF INDUSTRIAL-IoT FRAMEWORK IN FULL STACK
Connecting a few industrial assets to monitor their performance remotely in the cloud is one thing. Demonstrating pervasive connectivity and actionable predictive analytics across an entire worldwide fleet (either owned or installed at client sites) is quite another. Testing the market value is one, having clients paying for that incremental value is yet another.
Implementing industrial-IoT makes for good press but they are merely one part of the transformation test.
IIoT is still evolving and it hasn’t quite seen the quantum leap that many predicted. Instead it has taken a decade to become mainstream. Automation users are conservative about change, particularly concerning security. In addition to that hesitation, early IIoT implementations were cumbersome and extremely expensive. These issues led many users, such as small machine builders, to be disinclined to get involved. That situation has improved substantially both in terms of costs and flexibility. Industrial players are coming round to the view that they cannot compete unless they include IIoT-related features in their equipment.
Any assessment of success in this test requires to move beyond technology stack implementations (still a core requirement), onto the hierarchy of enterprise business processes and metrics they impact.
2: INDUSTRIAL-GRADE CYBERSECURITY DESIGNED-IN
The bottom line of having industrial grade cybersecurity designed into a digital transformation strategy is to enable an operating environment free of business disruptions and downtime, triggered by rogue actors. As attack surfaces multiply on account of industrial IT/OT convergence, proliferation of remote workers logging into key industrial networks and the need for online monitoring in real time, so have the risks of having critical assets becoming disabled for long periods and causing havoc in production and shipping schedules for customers.
Does your risk assessment include the possibility of a cyber-attack on one of your critical suppliers, and the impact that would have on your company’s operations? With increasing closely integrated relationships with suppliers and partners, the risks are magnified many fold. An attach on an extended partner network has an easy way of reaching your own network unless effective protocols for asset inventory, state monitoring and remediation procedures are in place and reviewed routinely. Its also important to ensure that companies are quantifying the likelihood and impact of that risk correctly in light of the current threat environment.
The use of multiple protections is a key to in-depth defense of industrial networks. OT has unique environmental challenges that need to be managed across industrial assets, ones to which IT’s tools, integrations, and processes are not designed to meet. The hardware and software that is deployed to automate industrial operations are unique, and traditional IT services firms typically are not equipped or trained on such specialized tools.
Adversaries seek to target assets that organizations have little visibility into as a way to quietly persist on the network. Perimeter based Cybersecurity strategies such as a firewall and border routers or separation of plant-floor intranet networks from internet-connected enterprise systems using demilitarized zones were once recommended as high level security tactics. However, these alone are no longer viable in a world where businesses may develop and deploy applications in corporate data centers, private/public clouds, or SaaS models that require maintaining a connection to the broader internet. As a result, new vectors are opened up to malicious actors looking to enter the industrial networks. A separate report will delve into deeper aspects of industrial and ICS security. Meanwhile, this link provides additional insight into challenges in implementing industrial cybersecurity, especially one that involves OT/ICS security.
3: EVOLUTION OF THE CLOUD ENABLED BUSINESS MODEL
Enterprises launched transformation initiatives with a message to shareholders about the dual promise of supercharging growth while tangibly reducing structural costs. This makes Business Model Evolution an important test of digital transformation success. One might argue this is easier said than done.
ArcInsight Research has conducted analysis of transition paths of many companies changing their go to market revenue models in order to support their transformed focus. While this change of revenue model to SaaS subscriptions keeps most CFOs awake at night, the real depth of change goes well beyond the finance function. The SaaS model takes many forms for an industrial enterprise, responding to a range of their customer’s needs – deploying an on-prem solution, a single-tenant cloud solution through to a truly cloud-enabled multi-tenant offering. The cost, complexity and security implications change accordingly.
4: ORGANIZATION MODEL TRANSFORMATION
A very critical test and one that forces a transformation of the sales organizational processes and roles (#presales, account pursuit, post sales), and their connections to other enterprise processes in finance quote-to-cash, field service, even the enterprise technology applications in use.
ArcInsight Research’s ongoing survey of enterprises transitioning to a subscription business model revealed interesting insights.
– A majority of survey respondents (over 60%) are new to subscription business models and #SaaS rev-shares are still low.
– Early transition efforts show ongoing sales strategies mirroring product/licensing era practices – mix of geographical & account-based coverage leaning towards latter.
– The most important new learning brought into the organization is an appreciation of the critical #CustomerSuccess role. One that determines and influences their product’s Time-to-Impact for the account, effectively setting the base for continued #renewals, upsell & cross-sells as the relationship matures.
– Incentive strategies tend to lean more towards EXPAND than on LAND, among the respondents indicating a slow transition of sales processes and attitudes. Contributing to this is a possible reluctance to let go of the long practiced sales motions and a pushback to the acceptance of newly designed sales comp plans to support the SaaS #subscription business model.
– Departure of key salespeople and increase in SaaS administrative costs have been the other internal organization impact.
– While revenues have certainly benefited somewhat from a shift to subscriptions, there has also been significant client pushbacks to switching over their entire business to the new model.
Industrial Digital Transformations are far more complex and challenging, compared to that in any other industry sector.
High value capex investments, long asset lives, their mission criticality for client’s core manufacturing operations, long service-driven customer relationships, embedded legacy technologies that cannot be ripped-and-replaced without costly consequences, a shrinking pool of experienced personnel, a newly emerged generation of workers with a digital-only mindset, a rapid commoditization of products, have made industrial digital transformations a future-survival imperative, not merely a nice-to-have.
This makes the task of successfully transitioning to a future-state enterprise and delivering on that promised path to value all the more critical.
Making sure all bases are covered on this path to success demands a structured methodology and experience of skilled advisors that understand the business environment, have deep knowledge of internal enterprise operations, have the ability to navigate cross-functional differences in perspectives, know how to structure external communications to stakeholders (most notably its customers and investors) and finally, have the ability to assess the success of digital transformations objectively. In a way that captures the cumulative value of experiential learning and the targeted financial benefits.
Contact us for a confidential briefing about your own Industrial Digital Transformation experiences. Participate in our ongoing research survey TRANSITIONING TO A SUBSCRIPTION BUSINESS MODEL. https://lnkd.in/gmstbkiK
About the author: Praas Chaudhuri is a Silicon Valley based industry analyst & co-founder of ArcInsight Research Partners, a strategic research & advisory group focused on digital transformation driven by analytics, algorithms & pervasive connectivity.
Broad areas of research interest at ArcInsight Partners include – (1) Industrial-IoT enabled manufacturing & production process transformations. (2) Evolution of intelligent cities enabled by new mobility design, urban dynamics & renewables. (3) Emerging business trends enabled by SaaS models and new monetisation strategies.
Praas Chaudhuri spends a lot of time with executives at many interesting companies around the world discussing industry dynamics across sectors such as industrial equipment, transportation, process, healthcare & financial services, communications, agtech & mining, AI & computer vision, process control & IoT, as well as city managers & CIOs. He has written & presented on a wide range of strategic topics related to industry & vertical dynamics and on business related subject areas. He is also a frequent speaker & panelist at conferences & professional forums, and has published many research-based articles, white-papers and points-of-views.
A chemical engineer in his early years, Praas had a long stint as strategic management advisor with firms such as KPMG and Monitor, as well as at Hewlett-Packard, besides several early stage technology & bioinformatics companies. He has a bachelors degree in engineering, a MBA and a PhD. in decision sciences.