Chain Brands Leverage DingTalk Ecosystem to Create Digital Employees and Solve Organizational Collaboration Challenges

This article analyzes how chain brands leverage the DingTalk ecosystem and third-party intelligent agents to create digital employees, helping enterprises break down information silos, reshape organizational collaboration boundaries, and truly empower frontline operations and organizational evolution with AI.

Organizational Challenges Behind Expansion

The fluorescent green hue at the street corner, paired with a squeaky rubber yellow duck toy, forms the visual memory that the new-style tea brand LINLEE leaves in customers' minds.

But as the number of stores rapidly surges past 2,000, behind this vibrant image lies an organizational anxiety rarely shared with outsiders.

The new tea beverage market has become extremely competitive, with supply chains and operational efficiency now the key differentiators. As store count grows from dozens to over two thousand, the friction caused by cross-regional coordination multiplies accordingly.

The most pressing issue is the vicious cycle of "people chasing information."

A single SOP (Standard Operating Procedure) for a new product, passed among headquarters, regional supervisors, and frontline store managers, often spawns more than a dozen versions. Regional managers spend half of their three daily hours dedicated to data checking, version verification, and clarifying execution details.

To dismantle these information silos, LINLEE moved its daily collaboration onto DingTalk.

Using DingTalk's basic functions—documents, instant messaging, calendar, and to-do lists—the team finally established an online hub for information flow. Documents are centrally managed with version control; instant messaging eliminates communication delays; calendars and to-do lists ensure cross-departmental meetings and task follow-ups are properly executed.

Collaboration friction has decreased, and information can now flow smoothly within a unified system.

Yet this only solves the problem of being "connected."

When communication and collaboration are no longer bottlenecks, deeper business challenges emerge: How can the massive amount of data and processes accumulated within the system truly benefit frontline operations?

In other words, once the foundation is laid, how can AI evolve from being just a "personal productivity tool" into a scalable, deeply embedded organizational capability?

This is no longer merely a technical challenge, but a major test of organizational evolution.

The Detours and Pitfalls of AI Implementation

After establishing the foundation, many companies instinctively move to the next step: deploy AI and measure labor efficiency.

LINLEE also initially fell into this seemingly logical "efficiency trap."

The initial calculation was precise: introduce AI office tools to replace repetitive tasks, converting saved time directly into output. But reality quickly poured cold water on this idea. When management tried to assess AI’s value by calculating "hours saved," frontline teams clashed over incentive distribution.

"Whose performance credit goes to work done by machines?"

"With time saved, should I manage more stores or be allowed to leave work earlier?"

Once AI is seen as a "whip to drive productivity," the focus shifts off target. Technology implementation becomes a zero-sum game—the deeper the system rollout, the stronger the frontline resistance grows.

AI isn’t meant to “cut jobs,” but to “solve problems.”

Realizing this, LINLEE abruptly hit the brakes on efficiency-based performance metrics and redirected attention toward real business pain points. The breakthrough doesn’t lie in flashy tools, but in reshaping organizational mechanisms.

They developed a "co-creation" model.

The IT department no longer works in isolation; business units now directly participate in planning and deeply engage in defining AI use cases. Process optimization teams transformed into "AI Growth Officers," embedding themselves with frontline teams long-term.

From standardizing store inspection criteria to extracting anomaly data, business experts and AI Growth Officers frequently collaborate within DingTalk documents and chat threads, breaking down vague experience into clear rules.

This shift in mechanism is essentially like conducting a special onboarding training for the upcoming "digital employee."

When organizations stop measuring AI against rigid KPIs and instead embrace it with genuine intent to solve real issues, true collaboration finally begins.

Obstacles cleared, the workstation for the next "new employee" is already ready.

The Birth of Supervisory Digital Employee "Duck Duck"

Workstation ready, the first official "digital employee" was named "Duck Duck."

Its primary service target: the nerve endings of any chain brand—operations supervisors.

In the past, supervisors’ daily routines carried an absurd sense of disconnection. They were supposed to visit stores to check displays, improve service, and monitor quality control, yet in reality, three hours of store visits would see most time spent searching for data, verifying spreadsheets, and checking inventory.

People were trapped in information silos.

LINLEE didn’t follow the trend by building a simple conversational data query tool. Instead, they used DingTalk’s YiDa platform to build a business workspace and integrated third-party intelligent agent tools via open APIs, giving "Duck Duck" full legitimacy as a true "employee."

"Duck Duck" isn't a passive string of code waiting for commands—it's an active collaborator embedded in business workflows.

Once authorized by a supervisor, "Duck Duck" delivers daily summaries of key operational metrics directly to their DingTalk message list via DingTalk bots. When a supervisor initiates an approval request, the pre-configured YiDa process triggers automatically, generating corresponding follow-up to-dos.

No more jumping between complex systems or dealing with fragmented interfaces.

DingTalk’s core features—to-do lists, approvals, and instant messaging—become "Duck Duck’s" hands and feet. It stitches together scattered nodes, transforming data previously moved manually into seamless business flows.

Shifting from “people chasing information” to “AI connecting information streams” changes far more than just efficiency.

As supervisors lift their heads from repetitive spreadsheet work, they finally have time to examine the color of a cup of tea, listen to customer complaints or compliments.

The birth of "Duck Duck" allows supervisors to become true supervisors again.

Ecosystem Collaboration and Universal Agent Adoption

"Duck Duck" successfully becoming a permanent member of the supervisory team was like a pebble dropped into a lake—the ripples quickly spread outward.

The most immediate feedback was a surge in store management ratios. Where managing ten stores used to be overwhelming, individual capacity quietly expanded. Supervisors were no longer data-chasing "spreadsheet brothers and sisters," but returned to actual business operations.

This transformation soon caught the attention of other departments.

The finance team began exploring whether digital employees could automatically reconcile complex store transaction records; the design team considered using AI to handle repetitive material layout tasks. Suddenly, every business line started submitting their own "hiring requests."

As AI evolves from isolated tools into organizational infrastructure, ecosystem support becomes the decisive factor.

DingTalk, as an open digital foundation, provides the necessary inclusiveness. Frontline staff no longer need to wait for IT department schedules—they can directly leverage the DingTalk ecosystem to integrate various third-party AI tools and intelligent agents.

By connecting foundational capabilities like documents, calendars, and messaging with external AI tools, they assemble customized intelligent agents like building blocks, tailored to their specific needs.

No more switching back and forth between cumbersome systems. The smooth, multi-device experience enables everyone to become the "Agent Owner" of their own role.

A deeper change occurs within the organization’s mindset.

In the past, management meetings revolved around "what new tools to buy." Now, the conversation has shifted to "which responsibilities can be delegated to digital employees."

From seeking tools to rethinking job allocation—this is not just technology adoption, but a leap in organizational thinking.

Redefining Roles and Organizational Boundaries

Many people initially view AI as a looming axe threatening job cuts.

Yet in LINLEE’s practice, AI has never been used to bluntly "eliminate positions." What it truly does is redistribute tasks within roles.

When tedious store inspection reports are quickly processed and critical alerts pop up promptly in DingTalk messages and to-do lists, frontline supervisors transform from "data movers" back into "business diagnosticians."

Time previously spent searching reports and verifying data is now freed up for in-depth communication with franchisees and optimizing store operations.

AI doesn’t eliminate jobs—it strips away the mechanical "manual labor" within them.

In this process, a new role naturally emerges within the organization: the Agent Owner.

They may not be coding experts, but they are undoubtedly the ones who best understand business pain points. Leveraging DingTalk’s common-sense capabilities—documents, calendars—and combining them with third-party intelligent agents, they customize digital employees for their teams like assembling building blocks.

Technical barriers disappear; business expertise becomes the greatest advantage.

Looking back, LINLEE’s greatest gain from this journey isn’t some dry efficiency metric, but a complete transformation in organizational awareness.

AI is not just a productivity amplifier, but a developer of organizational capability.

It reveals redundancies and breakpoints in existing processes, and highlights which employees possess the agility to embrace change. The boundary between humans and machines is no longer a zero-sum game of "who replaces whom," but an evolving symbiosis of "how to collaborate better."

"Duck Duck" is merely the first digital employee to clock in.

As more and more "Duck Ducks" start showing up for work, what will future organizations look like?

Possibly, they’ll become boundary-less, self-reorganizing living organisms. And the answer lies in every moment of默契 high-five between humans and AI.

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