If you are a city/operation manager of a operationally heavy company, having a bird’s eye view of the day-to-day operations is crucial since on-ground operations are quite chaotic in nature. In that scenario, the ability to make faster decisions with more efficiency can be driven with having quick assess to data and relevant insights.

However along with data visibility, you also need the ability to find gaps and drill down and get further insights in order to make right decisions and have the ability to respond to potential challenges or roadblocks. The right dashboard only tells you where the gap exists but also why there is such a gap in the first place.

Current Challenges to Access the Right Insights

One major problem that organisations face is unification of all the data– Data is spread across formats in various dastabases and combining them to have a clear and intuitive visual representation becomes challenging. If your organisation has a large foot-print or has lots of moving parts in the real world, then this process becomes all the more challenging, given the frequency and scale of data being collected.

Once the access to the data gets solved, the second challenge becomes being able to visualize the data in the right way– to get the right insights & take the right decisions.

The issue isn’t with dashboards being good or bad. The reason why most dashboards fail at newer use cases is that they are rarely customizable and the new cases are far beyond what the dashboards were designed for. Or in some cases, not built for the right user persona.

Which brings us to the next point:

Why Aren’t Today’s Operational Dashboards Good Enough?

Today's growth and marketing teams in most internet companies have a great stack of analytics tool to monitor their online business. But, why isn't the need for analytics and visibility for ops teams emphasised ever?

Today, most of theses companies end up using either of these three dash-boarding/analytics solution for getting visibility for their ops teams:

  1. Traditional BI Tools: BI products such as Tableau and PowerBI serve the purpose when the data is static is nature but fail to deliver when it comes to movement analytics. Location data has a spatio-temporal component which cannot be visualized in the best way using these tools.  
  2. Microsoft Excel: Excel is one of the most traditional tools which was used for analytics and visualisation. But the advancement of technology and the need of better analytics/visibility, (especially geospatial), they aren't the best choice in the market.
  3. Internal Dashboards: Companies with internal dashboards most often fail to understand that they only be used for a fixed number of use-cases and any further addition of metrics or features would mean extra dependency on the in-house engineering teams. In the end, it results in a long list of backlogs for the  developers.
  4. Open Source Tools: The four alternative that companies have is using open source tools like Kepler.gl or QGIS. The issue with these tools is that they are just a visualization tool– hence any kind of data manipulations needs to happen outside the tool. This is very painful when you need rapid visualization & experimentation. Read more here:
Comparing Locale.ai and Uber’s Kepler.gl on their Capabilities
Comparision of how Locale is different from open-source Kepler.gl on capabilities

How to Build Dashboards that Operations Teams Really Use

Before jumping into operations teams, what should a good dashboard have?

  • A good dashboard should tell you where the problem is. While it is nice to see what you are doing right, it is also of utmost importance to see what you are doing wrong in order to improve performance.They point you to the reasons behind the problem and how you can troubleshoot the bottlenecks  
  • A good dashboard helps align your organisation. By making dashboards throughout the company, they can hold different teams accountable for good-work or wrong-doings in their job

What makes for a good ops dashboard?

If you are building dashboards for operations team with location data, here are the list of criteria to follow:

Having all location data in the same place: Having the bird's eye view of your demand, supply and trips is very critical. So, the right dashboard needs to integrate data across all sources into one place. Say you want to find the areas where the revenue and customer reviews are both low so as to run campaigns.

Drilling Down: Users should have the ability to drill down very simply into the data to find the underlying issues. The ability to drill down across time, geo and attributes is important when you are dealing with operations team because you need to find areas or user-cohorts with a specific behaviour.

Collaboration and Transparency: The need for collaboration and transparency because at times the call for action is immediate and urgent hence it is important that people are on the same page in terms of knowing where the loopholes are or where the strings need to be straightened.

No code required: Business users and ops teams don't have the bandwidth to sit and write queries to do data joins together. Hence, all their questions should be answered straight from the UI. In other words, the dashboard need to be designed keeping the "end user" in mind.

We have talked about what it takes to make operations team agile and data-driven here:

How to Inculcate a Data-Driven & Agile Culture in Your Operations Teams
Fo the real world where demand, supply and operations interact with each other!

Build Vs Buy

So now that we have established how does the right dashboard for the ops team looks like, you have 2 options: you can either build it internally or you can buy a software tool.

(1) On Building

At first glance, "build" may appear to be the best solution since many organisations believe they are best positioned to understand their own needs and have engineering capacity to build it internally. Any analytics dashboarding solution must grow to accommodate the changing business dynamics and metrics. It can be challenging enough to build an scalable dashboarding system that meets all business needs within acceptable timeframes and cost.

However, building an analytics tool or dashboard can take somewhere between 6-8 months of time with a team of designers, engineers and geo-spatial analysts putting all their efforts to build such a analytics platform along with the added costs of maintaining the system as well.  

Other than investment in infrastructure and human resource, one major investment that is very crucial when building internal dashboards is the "time-to-value" cost, which means how long can you wait before you leverage the real value of the product. Not to forget that these tools require timely maintenance and that sucks up a lot of money.
Build vs Buy- Time & Effort Comparision

(1) On Buying

Locale.ai is a no-code location analytics product built for analyst and business teams to give them operational efficiency and visibility. Locale helps you achieve operation driven growth which is critical for optimizations. We take care of the grunt work while you focus on your everyday business and operations. With Locale you get the following advantages:

  • Ability to drill down to the smallest grid or individual entity: Locale gives you the ability to drill down across time , users and categories. Using entity-lookup feature you can drill down to the smallest grid or entity and see a range of metrics for that particular area/entity. This helps decision-makers take important strategic decisions. For example,What is the reason for user-churn in area X?
  • Centralized Data Centre: Locale works as a centralized data centre and helps teams collaborate and monitor performance of cross-team. This also gives the ability of having visibility and helps decision-makers have a good amount of context about an underlying issue or inefficiency. For example , say you want to look up for the cost to revenue ratio heatmap for the whole city of Denver for the month for July ?  
  • Different visualisation for different use case: Locale has pre-built visualizations for each specific use-case which means you have a fixed and complete visualization at your disposal according to the decision or action you want to take. It shows you the right data and visualization which will help you tackle issues pertaining to daily operation or long-run scaling of business.