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Picture this: a tech executive stands in the spotlight on a stage proclaiming that a new partnership will revolutionize the industry. The crowd applauds, investors get excited, the media buzzes with anticipation, and customers begin to dream about new possibilities.
A year later, the promised transformation is nowhere to be seen. Sounds familiar? That’s because partnerships and integrations often overpromise and underdeliver, leaving companies disillusioned and consumers wary.
Big Promises: A Tale as Old as Tech Itself
Partnerships and integrations are like the shiny new toy in a tech world full of dull promises. Companies join forces, pooling their data to unlock new insights, improve efficiencies and offer better customer and employee experiences. The theoretical benefits are hard to resist:
- Enhanced insights through combined datasets.
- Improved operational efficiency and decision-making.
- Better customer experiences through personalized services.
- Competitive advantages by leveraging unique data capabilities.
These promises can be compelling, driving organizations to invest heavily in partnerships and integrations.
A recent high-profile example is the alliance between Salesforce and Workday. Announced with great fanfare, the partnership aims to revolutionize the workplace with advanced AI-driven solutions. But will it deliver? Is this the future of work?
You’ll have to forgive me if I wait and see.
Combining CRM, Sales, Finance, HR — and AI Bots
The announcement at the end of July promised new possibilities for Workday and Salesforce’s shared customers.
Enhanced EX and CX
By integrating Salesforce’s CRM capabilities with Workday’s HCM solutions, the alliance aims to provide a seamless and enriched employee experience, which ultimately leads to better customer experiences. This includes personalized skill development, automated processes and improved employee outcomes.
Combined Bots
The partnership also intends to leverage both of their AI solutions to provide insights from the vast amounts of data generated by both platforms. By combining the AI power of Workday and Salesforce, organizations can (hopefully) make better-informed decisions regarding workforce management and customer experience.
Efficiency, Efficiency, Efficiency
By automating routine tasks and providing predictive analytics, the alliance seeks to reduce administrative burdens and enhance overall productivity. A common promise of almost any new tech — that is not always realized.
While the potential of the Salesforce and Workday alliance is admittedly interesting, it’s best to approach these promises with cautious optimism (or, perhaps, a healthy dose of skepticism). Historical examples remind us that even the most promising partnerships can encounter significant challenges.
Related Article: What 'Value' Means in the AI Era
Reality Check: Things Can Go Really, Really Wrong
Data partnerships can be alluring, promising unprecedented insights and operational efficiencies, but real-world examples often tell a different story.
In one example, Quirky, a startup focused on crowdsourced invention, partnered with General Electric (GE) to co-develop smart-home products. Despite initial excitement, the partnership struggled to deliver successful products. Misalignment in company cultures, operational speeds and strategies led to the partnership’s failure. Quirky eventually filed for bankruptcy, and the collaboration ended without significant market impact.
In another example, IBM Watson partnered with various healthcare providers to bring AI-driven insights into oncology treatment plans. The ultimate big promise: Better cancer treatments were just a tech integration away. Reports emerged that Watson provided incorrect or unsafe treatment recommendations. The AI struggled with integrating and interpreting complex medical data, leading to a loss of confidence in the technology. The ambitious promises of revolutionizing cancer treatment fell short, demonstrating that even the most advanced AI systems can falter when faced with real-world complexities.
Related Article: Microsoft Backs Down on Teams Connectors – For Now
What Tech Companies Should Consider Before Embarking on Partnerships
The potential pitfalls of partnerships and integrations are always there, highlighting the need for cautious optimism, thorough evaluation and clear communication in any data-driven collaboration.
While partnerships are often attractive, hidden costs and risks can derail even the most promising collaborations.
- Operational Disruptions and Integration Challenges — Integrating systems from different companies can be a nightmare. Different data formats, incompatible systems and varying operational practices can lead to significant disruptions. These integration challenges can delay project timelines and inflate costs far beyond initial estimates.
- Security and Privacy Risks — Sharing data between organizations increases the risk of security breaches and data leaks. Each company involved in a data partnership must ensure robust security measures are in place, which can be costly and complex. Additionally, privacy concerns can arise, particularly if sensitive customer data is involved. The fallout from a data breach can be devastating, leading to loss of customer trust and potential legal repercussions.
- Legal and Regulatory Challenges — Navigating the legal landscape of data-sharing can be tricky. Different jurisdictions have different regulations regarding data privacy and protection. Compliance with these regulations requires careful planning and ongoing monitoring, adding another layer of complexity and cost.
- Brand Reputation — If a data partnership goes wrong, it can damage the reputations of all companies involved. Customers and clients may lose trust if they perceive that their data is not being handled responsibly. The long-term impact on brand reputation can be far-reaching and difficult to repair.
Nobody wants a partnership to go wrong, but getting them right is more challenging than it looks from the outside. Add the sometimes unpredictable nature of integrating AI with everything and it could do unknown damage, something that Workday is working through right now.
Related Article: When AI Discriminates, Who's to Blame?
How Can End-User Organizations Evaluate Partnerships
Given the potential pitfalls, how can companies that want to use these new, promising solutions approach partnerships more wisely?
Do Your Due Diligence
Before considering using the result of a new partnership, conduct thorough due diligence. Assess their track record, data-security measures and compatibility with your processes. Understand their goals for the partnership and ensure it aligns with yours to avoid clashes.
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Create Clear, Measurable Goals
Set clear, measurable goals for your ambitions. What specific outcomes do you hope to achieve with this combined offering? How will success be measured? Having well-defined objectives helps keep you focused and your partners accountable.
Consider Pilot Projects Before Full-Scale Implementation
Whenever possible, start with a pilot project to test the waters before committing to a full-scale implementation. This approach allows you to identify and address potential issues early on without significant investment or risk.
Be Pleasantly Surprised, Not Disappointed
Keep your expectations moderated until you start to see some traction. Work leaders who have promised radical transformation and fallen short because of a not-as-advertised partnership have to worry about their credibility. Instead, use caution and allow yourself to be pleasantly surprised when an alliance works out exactly as they say.
Beware of Red Flags
Overly ambitious promises that seem too good to be true, lack of transparency about data-handling and security measures and a poor track record or history of failed partnerships all should give you immediate pause. Workday and Salesforce aren’t giving false positives on cancer, but that doesn’t mean it is all smooth sailing from here.
Skepticism, Not Cynicism
Skepticism is not just healthy, it's necessary in the world of partnerships and integrations. While the potential benefits can be substantial, the risks and hidden costs are equally significant. These partnerships can work, so there’s no need to be cynical about them being doomed to fail.
By approaching partnerships with caution, conducting thorough evaluations and setting clear, realistic goals, companies can navigate these collaborations more effectively. Remember: well-chosen partnerships can provide value, but only if managed wisely and with an eye on potential pitfalls.
