Isn’t it funny that so many of the workflow “enablement” tools we adopt with great expectations eventually become our greatest source of frustration?
When Good Platforms Go Bad
A great rant on the topic appeared recently in Business Insider: “Everyone Hates Workday.” The punchline, essentially, is that the behemoth platform used by half of the Fortune 500 is making the work of talent data and process management ironically burdensome, as its promise at inception was to simplify that same work. In the article, the author beautifully captures the absolute nightmare end users experience trying to get real work done with Workday: “Getting someone onboarded using Workday is like trying to get water from your sink to your stove using a colander.” He further offers some insight as to why what was a well-intentioned early-days product with strong customer-market fit has evolved into such a ponderous Frankenstein: the oft-referenced “ensh*ttification” of platforms, which results from revenue-hungry providers trying to serve yet another user and find yet another application worth paying for.
Of course, HR isn’t the only important function in the business with really important jobs to be done suffering from the vagaries of an inflexible central platform beast. In Account Management and Sales, the same love/hate relationship exists with Salesforce. For fun, just google “why do people hate salesforce,” and enjoy your favorite adult beverage while sifting through the “about 2,250,000 results” returned (or give in to the persistent Google “AI Overview” feature that interrupts your search for the page-long if less colorful TLDR). Entire Reddit and Quora forums are dedicated to the topic.
Tech Stacks Run Amok
The problems of the typical functional tech stack are greater than just the one unwieldy box in the middle. Tool proliferation all around that big box plagues time-pressed professionals across most functions. With all the enablement and analytics tool “innovation” happening around the professional suites of business, however, nowhere is the irony of the situation greater than in customer- and prospect-facing roles. In the “State of Sales” report available on the company’s website, Salesforce reports the average commercial team is using 10 tools (just imagine the right-hand tail of that distribution curve) and that 9 out of 10 companies are looking to consolidate the tech stack because 70% of employees are “overwhelmed” with the array of tools and related administrative work. (Points for honesty to the source, though no doubt they have a “solution” to the problem.)
Thanks to the rise of AI and its incorporation into tech stack tools, one by one up, down, and across the stack, this proliferation problem is worsening as we speak. As just one example, AI enhancements on current communication platforms (think Zoom AI and Slack AI) and available as frictionless bolt-ons (think Gong and Chorus) represent incremental–useful, of course–process inputs that commercial teams need to spend time learning and extracting insight from to establish a comprehensive view of the customer and to tune their pitch. As of the time of this writing, there are 65 or more of these products now available.
No Time for Job One
Unsurprisingly, we see stats on time spent with customers and in commercial conversations dropping precipitously. Gartner research reports the average salesperson spends only 18% of his or her time actually selling, with the number-one driver of the time suck away from selling being administrative taskwork.
Account Management and Customer Success teams may well have it the worst. They suffer the same time-suck realities associated with tool proliferation and burden, but they’re constantly asked to do more with what little time they have.
- Take on more accounts as the company drives for revenue efficiency
- Increase product proficiency as the roadmap yields new versions, features, and use cases
- Use that proficiency to raise utilization levels within accounts and across the portfolio
To name a few. It’s a wonder there’s ever a moment to ask for the renewal, much less plan and execute a strategy to grow account revenue.
Most concerning, commercial teams, in a moment of honesty, would also say they feel less effective in the moments they have doing customer-facing work. Manually assembling a single view of the customer from across the myriad internal and external input sources available is nigh impossible. Yet, at the same time, customer teams can’t live without that view: customer relationships are so complex, with so many points of interaction–and right now so fraught with economic and competitive pressure–that reps don’t feel they can trust their gut any longer, and rightfully so.
Calgon, Take Me Away!
In summary:
- Our foundational tech tools have become unmanageably burdensome;
- The overall tech stack is overflowing with utilities (however well-intentioned each might be);
- The number of tools is expanding as we speak with each new AI-powered innovation; and,
- With all this “enablement,” commercial teams are spending less time selling and feeling less effective when selling.
Where does one look for salvation in all this?
Well, the good news is that the same proliferation-accelerating capability of AI can also be deployed as an integrative, intelligence coordinating mechanism. We’re starting to see the rise of meta tools that sit across many of all of the component parts of the tech stack, whose purpose is to pull together a single critical view of what matters most for whoever the user persona–and configurable to whatever the relevant scope (so, in Account Management, as example, think: Customer Manager, Team Director, Functional Leader, CRO, CEO).
More than just provide a single view, these tools bring the AI-powered distinction of inference: not just seeing all the relevant data associated with a particular customer’s situation, but also seeing that combination of data through the lens of a learning model that predicts which combinations for which customers either spell retention trouble or point to a promising growth opportunity.
To be clear, yes, this is, in fact, another type of tool. But a very different one.
To the motivating starting point in this piece–frustration–the intelligent agent approach solves for each of the major pain points of today’s tech stack:
- First, it saves massive amounts of time that could be spent with customers. Trying to reach the same conclusions that the intelligent agent spits out in real time would take countless trips across multiple internal and external data sources, a grand exercise of synthesis and analysis, and several hours per account. Multiply by the number of accounts and frequency of the exercise, and the math starts adding up pretty quickly and discouragingly.
- Second, and even more importantly, it produces superior insight and guidance. By tying together the independent utilities of the other tech stack tools and their data sets, it improves insight and guidance for the user far beyond what would be possible by manually pulling from each individually. Without the experience of the larger data set and model as a real-time reference, the diligent Account Manager might still draw the wrong conclusion from what they perceive to be relevant in the data after spending all that time.
- Third, it’s always on as an early warning threat detection system. Perhaps the most important point of all, the system is running queries constantly, looking for the combination of data points that suggest an impending customer event or action, and forwarding the intelligence–or recommending (or taking) action–proactively. This moves beyond solving the problems of today’s tech stack and moves into a world of new and important capability. Think of it as using technology to perfect and scale gut instinct.
Knownwell on the Case
At Knownwell, we have taken on the challenge of helping companies find their way to a better future in managing and enhancing customer relationships using this approach. To learn more and express interest in becoming one of our pilot users, let us know of your interest here. The right member of our team will be in touch soon.
