.jpg)
In this insightful interview with Thomas Lah, the Executive Director of TSIA, we explore the transformative trends in the technology and services industry over the past decade. Thomas sheds light on the significant shift from transactional business models to XaaS models, emphasizing the challenges and successes of companies like Adobe, Autodesk, and Microsoft. He also delves into the impact of AI on operational efficiency and the necessity of a profitable XaaS model amidst economic challenges. Furthermore, Thomas discusses the barriers to digital transformation in B2B companies, the role of AI and automation in the tech industry, and strategies for successfully transitioning to XaaS models. His extensive experience offers valuable insights into business outcome engineering, customer success funding models, and future predictions for the industry. This conversation highlights the importance of strategic leadership in navigating these dynamic changes.
As the executive director of TSIA, what are the most significant trends you’ve observed in the technology and services industry over the past decade, and how have these trends influenced your approach to leadership within the association?
Over the past decade, the primary trend facing technology providers has been the pivot from transactional business models (selling products) to XaaS business models (selling technology as a service). This is not an easy transition. Companies like Adobe, Autodesk, and Microsoft navigated this well. Most legacy technology companies continue to struggle with this business model transition. The second trend started in 2020 when inflation and high interest rates became a thing. This is the trend to have a PROFITABLE XaaS business model. The latest trend is related to AI. How will AI improve the operational efficiency of technology companies? All these trends have anchored the research we do at TSIA. As a leadership team, we have have our research engine focused on how technology companies operate profitable XaaS business models.
In your latest book, “Digital Hesitation: Why B2B Companies Aren’t Reaching Their Full Digital Potential,” what are the key barriers you identify that prevent companies from fully embracing digital transformation, and how can they overcome these challenges?
Quite frankly, the key barrier to B2B companies fully leveraging digital transformation is that management teams don’t think big enough. Digital transformation has always been about leveraging data. Management teams have not internalized how a data driven business model can create both higher profitability and a better customer experience. Interestingly, we published that book right before the explosion of generative AI capabilities. The wider availability of AI capabilities has opened more eyes to the potential of overall digital transformation.
Can you share some insights from your experiences with major tech companies like Salesforce, OpenText, and Microsoft in navigating the rapidly evolving landscape of AI and automation?
Well you named three companies that are leaning hard into leveraging AI. Our research involves scanning the industry for real world use cases of AI. These are three companies that have provided these use cases to members. OpenText has reduced their effort to create educational materials for their customers by over 40%. Microsoft is leveraging AI to increase the ability of customers to resolve technical issues on their own by over 30%. Salesforce is deploying AI to reduce the time and cost of deploying their solutions. Our concern is for the technology companies that are not leaning into AI capabilities to reengineer their workflows. There are still some management teams we work with that feel AI is more hype than reality–even though we have the research to show that is not true.
How do you see the role of AI and automation evolving in the tech industry, and what impact do you believe this will have on traditional business models?
We are tracking how AI use cases are unfolding in the following seven areas of technology business models: Offer Creation, Revenue Generation, Customer Success, Support Services, Education Services, Professional Services, and Managed Services. Right now, Support Services, Managed Services, and Education Services organizations are already achieving productivity improvements in the 30% – 60% range by deploying AI in specific workflows like the content creation of educational materials and customer self-help tools. Professional Service and Customer Success organizations are still in the early phases of leveraging AI in their workflows. Sales teams are currently lagging in AI adoption. Over the next three years, we see AI integrated into the workflows of all seven areas. The result will be a new revenue per employee benchmark in technology business models. The impact is going to be dramatic.
As someone who has been deeply involved in helping technology service businesses optimize their operations, what are the top strategies you recommend for companies transitioning to an X-as-a-Service (XaaS) model?
We wrote an entire book on this topic titled The XaaS Playbook. Having witnessed so many TSIA member companies embark on this transition since that book was published, I would emphasize the following learnings for any management team starting this transition:
- Understand this is a multi-year journey (3-5 years to make real progress)
- This transition impacts every part of the company (no department will be spared)
- Read every book and article TSIA has published on XaaS transformation
- Read Geoffrey Moore’s Zone to Win to create an organizational structure that will support the transformation
Can you discuss the concept of “business outcome engineering” and how it helps companies ensure that their technology solutions deliver measurable results for their customers?
If you visit the web sites of most enterprise technology companies, they will be promoting how their technology delivers real business outcomes. That is the process of “marketing” outcomes. Outcome engineering is the discipline of systematically mapping your technology capabilities to specific business outcomes a customer cares about. Unfortunately, most technology companies suck at this. The secret to successful outcome engineering is aligning product, service, and sales teams to a tight set of well understood target business outcomes. This requires two things many technology providers lack:
1. Sufficient vertical industry expertise.
2. A well defined offer creation process that aligns product, service, and sales teams. However, if a technology company can master outcome engineering, it unlocks the ability to get beyond pricing on feature functionality (which is commoditizing) and price based on the business value of a solution.
What are some of the most common challenges companies face in customer success funding models, and how can they address these issues to improve customer adoption and satisfaction?
The most common challenge facing Customer Success organizations is that they have no clear economic funding model. SaaS companies created Customer Success to keep customers from churning and they treated the function as a cost of doing business. Now that interest rates are high and every technology company is under pressure to improve profitability, management teams are questioning the value of Customer Success. For over a decade, TSIA has been advocating three strategies to fund and scale Customer Success:
1. Monetize premium Customer Success activities (everything should not be free)
2. Give Customer Success commercial responsibilities (lead generation, small account expansions, contract renewals)
3. Digitize customer success activities wherever possible (AI is accelerating this lever).
In your role as the host of TSIA’s podcast, TECHtonic: Trends in Technology and Services, what are some of the most interesting conversations you’ve had recently, and what insights have you gained from your guests?
I’m just going to point the reader to five favorite episodes to date:
Episode 13: Geoffrey Moore and I discuss his framework Zone to Win. Great episode for any management team starting the XaaS transformation.
Episode 21: Dione Hedgpeth, a Chief Customer Officer, discusses the value of a “spiral” career path.
Episode 30: Sue Barsamian, former Chief of Sales and Marketing at HPE and board member of several technology companies discusses how to manage through business crises.
Episode 49: Justin Rose, John Deere’s President of Lifecycle Solutions, discusses digital transformation in the agriculture industry.
Episode 58: Defining effective corporate culture with Culture Partners’ Chief Scientist Jessica Kriegel.
Looking ahead, what are your predictions for the future of the technology and services industry, and how can companies best prepare themselves to thrive in this ever-changing environment?
I have been in this industry for over thirty years. I remember sitting in a cubicle in Mountain View California, working for SIlicon Graphics when a coworker showed me “the world wide web.” I thought the advent of the internet combined with cloud computing and XaaS business models was going to be the most disruptive change I would witness in my career. I was wrong. There is a mantra I recommend every technology professional repeat to themselves at least ten times a day: “AI may not replace me, but AI will definitely change the way I work.”
