Beyond sales reports: Building dashboards clients actually use

Major clients can bring major expectations, including the expectation that their convenience services operator will deliver the data. These employers want to know that the breakroom services they provide support larger goals such as health and wellness, improved employee satisfaction, fewer complaints and a better overall workplace experience.

At CTW in Miami, Shaw Industries’ Sarah Hooper described meeting weekly with her convenience services operator to review a proprietary dashboard that tracks product sales and flags service issues. Hooper noted that success extends beyond sales volume. The goal of Shaw’s refreshment services program is to increase employee satisfaction and sense of belonging.

Of course, tasks like investing in and managing client dashboards are not without cost — or risk if they are poorly designed or managed. “From dashboards to decisions: Making data analytics actually work,” an article by Alexis Gajewski in our sister publication TechEDGE, offers advice operators can use as they build client-facing wellness dashboards.

Building a wellness dashboard that clients will use

Dashboards work best, Gajewski says, when the data is tied to decisions, ownership and outcomes, not just reporting.

Start with the decisions your client needs to make. Define the decision first, then design analytics around it, Gajewski says. For wellness-focused breakrooms, that might include decisions like which items to promote, which to replace, which locations need improvements or service, how to respond to complaints and what “good” looks like by site or shift.

Use a decision-first framework to design the dashboard. Gajewski lays out four questions that separate “pretty dashboards” from actionable analytics:

• Who acts on the insight?
• How often is the decision made?
• What signal triggers action?
• What data is required?

For operator-client wellness reporting, that translates into:

• Decision owner: Decide who on the client side will act, and who on the operator side will be accountable for the response.
• Decision frequency: Set regular meetings to review the data. For instance, you can schedule weekly consultations to monitor trends and client satisfaction, and implement a daily check-in mechanism to address service exceptions or urgent complaints.
• Decision signal: Identify meaningful triggers for action. These could include recurring out-of-stock items, rising complaints, declining engagement with promoted items, or shifts in the mix that undermine agreed-upon wellness objectives.
• Right-sized data: It can be tempting to overshare data simply because you have it. Resist those urges. Instead, only add the data needed to make decisions confidently.

Make “partner, not vendor” measurable. Your client may already be holding you to a standard for responsiveness and follow-through. Use the dashboard to measure service reliability (uptime, time-to-repair, ticket response time) alongside wellness-oriented performance, so the client can see both the experience and the intent.

Balance access with governance. Gajewski warned that without shared definitions and guardrails, self-service analytics can create confusion and risk. But, overly centralized reporting becomes a bottleneck.

For operator dashboards, work with your client to agree up front on key metrics — what counts as “better-for-you,” how promotions are measured, and how complaints are categorized, for instance — so the client’s stakeholders can agree that the data is meaningful and accurate.

Treat AI as an amplifier, not a fix. Gajewski cautions that AI can help users discover insights faster, but it will not fix unclear ownership, poor data quality or weak governance. If you are pitching an “AI-powered wellness dashboard,” remember fundamentals first.

Prove impact, not activity. Gajewski recommends measuring analytics success by outcomes like risk reduction, cost savings and improved operational performance, not by how many dashboards were created.

In addition, in a wellness dashboard conversation, match each outcome metric to what the client cares about — fewer complaints, higher satisfaction, better engagement — and show whether decisions changed because of the reporting.

If you are building dashboards for clients like Shaw Industries or other large employers, and want more insights on data analytics and dashboards that work, check out the full TechEDGE article.