You can learn a lot by listening to your customers, and this is something Talkdesk seems to be very good at. The company has been building their cloud-native, AI-infused contact center story, first quietly, but now loudly, and Talkdesk was impossible to miss at Enterprise Connect 2019. With contact center being such a strong theme at the conference, this was a great opportunity to raise their profile, and the announcement of Workforce Management was likely their most important messaging.
The company’s strong momentum has them poised to get to the next level, and there’s a case to be made that owning-the-stack is critical to protecting your core engine. So long as the pieces that you own provide sustainable value and can support some form of differentiation, the strategy is sound. Clearly, Talkdesk feels this way about WFM, which is arguably the least sexy part of the contact center value chain. This begs the question of “why?”, along with what they’re seeing here that others are missing.
Nothing is for certain with constantly changing technology, but Talkdesk heard about a lot of pain points from customers that existing WFM offerings were not addressing. By re-framing the problem set around today’s digital technologies – namely cloud and AI – Talkdesk felt they could take a fresh approach with those particular challenges in mind.
We’ve seen this before with the PBX, and while it was the ultimate enterprise phone system for decades, successor telephony offerings were built on a different architecture using the next wave of technology. The installed base of PBXs remains large, but nobody buys them anymore, and all the innovation in telephony has shifted to IP, the cloud and mobility.
In the case of WFM, the value comes from having processes in place that optimize staffing, especially for having the right number – and the right type – of agents, all at the right time. This wouldn’t be hard to do if inbound contact volumes were steady and/or predictable, but life’s not like that. Effective WFM largely depends on forecasting accuracy, and with so many variables in play, there’s a massive data set to manage. In this day of Big Data and predictive analytics, it’s hard to believe that WFM is still so labor-intensive, and driven by legacy tools like Excel and Erlang formulae.
With that in mind, it’s not surprising to hear customers talking about how much time it takes to manage WFM software and administer scheduling around anticipated workloads. Furthermore, with limited analytics capability, supervisors cannot respond in real time, which is critical for making intraday adjustments. As a result, a multitude of small inefficiencies can translate into large-scale operational inefficiencies. Not only does that make contact centers more expensive to run, but scheduling snafus add stress that can impact agent performance.
I’ve long maintained that if UC was being created today, it would look like Slack, and Talkdesk is seeing the same thing here with WFM. Being formula-driven and data-intensive, it’s tailor-made for the cloud, and when AI is layered in, you get real-time analytics that keep improving with machine learning-based algorithms.
The exciting part about this brave new world is that there are no rules, so there’s nobody telling Talkdesk they cannot build their own WFM solution. Existing WFM players are well-established, and adding AI of their own, plus Talkdesk already partners with some of them via their AppConnect program – like Teleopti – so why do this? Talkdesk would simply say why not?
These other offerings aren’t cloud native, and if they were working so well, customers wouldn’t be telling them otherwise. As they have done with their broader Talkdesk iQ framework, they’re going tabla rosa and building WFM from the ground up. Rather than develop a solution to support a legacy environment, they’re using the building blocks for today’s applications needs, namely the scalability of the cloud, the adaptive learning model of AI, and a microservices architecture for rapid innovation. So, yes, it’s the PBX example all over again.
For Talkdesk, this isn’t just about building a better WFM to make the contact center run better; it’s also about being “agent-centric” and focusing on a better workplace experience for them. Of course, it’s a good thing when supervisors can map out big-picture scheduling with confidence, but it’s even better when agents can self-manage their schedules by sending requests to supervisors or even swapping shifts with other agents. Then consider being able to do this either from the desktop or a mobile device, and how empowering that can be for agents.
Labor may be the biggest cost input for contact centers, but what management really cares about is CX, and that won’t happen if agents with the wrong skill set are added to the next shift, or if the forecast is wrong and not enough agents are on call. When the right agents are on call at the right time – both for them and the customer – they’ll perform better, they’ll make better money, and ultimately, customers will get better service.
Aside from this agent-centric approach, Talkdesk’s flavor of WFM is notable in two other regards. First is being cloud-based, and that brings two distinct benefits. First is the basic ability to process large volumes of data, along with the capacity to respond in real time. The more data, the more accurate the forecasting models, and this especially matters when trying to dynamically update schedules on the fly.
The second aspect of cloud is the ability to support microservices, which is a major departure from legacy WFM and the ominous-sounding “monolithic” architecture that makes application development so slow and cumbersome. Microservices is about agility and creating very specific applications quickly to keep pace with changing market conditions.
As noted earlier, WFM is dependent on many variables, and Talkdesk’s solution is by no means a finished product. Their WFM will keep evolving as the track record develops, and when service creation is easy, this can be a great way to differentiate and add stickiness for Talkdesk’s customers.
Finally, the other notable element is AI, which runs through everything Talkdesk does – iQ – so it’s pretty much expected for WFM. Building on the cloud’s limitless capacity, AI drives analytics that have better predictive accuracy, and by providing “perpetual reforecasting”, WFM has continuous improvement.
Not only does this allow for ongoing fine-tuning, but the platform can make recommendations to supervisors in real time for dynamic schedule adjustments. By leveraging the cloud and AI, Talkdesk’s WFM can simply process far more data far more quickly and far more accurately than any legacy WFM platform can do. As such, aside from being agent-centric, this solution helps make the supervisor’s job more manageable.
All told, there’s a lot to like with Talkdesk WFM, and at minimum, it strengthens their overall value proposition. They’ll continue supporting existing WFM partners, and time will tell which form of WFM will gain the best traction. For now, their WFM will complement iQ, and there are no immediate plans to offer it as a standalone solution.
Again, time will tell, but clearly, Talkdesk seems confident enough to chart their own course for all things contact center, and there should be no doubt that other things will be coming. Something tells me they’ve learned a few things other than WFM from their customers, and remember, the customer is always right.
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