First things first: What is a data dashboard? It is an information management tool, which tracks, analyzes, and visualizes different metrics, results, and KPIs. It enables businesses to have direct access to and monitor their operational and financial performance.
In warehousing, in particular, every business entity conducts a great number of tasks and actions, which often overlap and cross each other. For that reason, warehouses find data dashboards to be an essential tool, which gathers all their BI (Business intelligence) in one organized place and assemble it in a comprehensible, analytical, and informative way.
However, in order to fully benefit from such an information tool, we need to set up not simply a data dashboard, but a high-quality, excellent one. And to help you do that, below, you will find the four best practices to adopt and follow.
As Dr. Steven Covey said in his book "The 7 Habits of Highly Effective People": Start with the end in mind. Or in the case of warehousing companies: with their goals in mind.
This is the first best practice for creating a high-grade data dashboard. By setting goals, companies start seeing clearly what they want to achieve and what they need to monitor and track, as well as what to work towards and where to direct their resources and assets (both tangible and intangible).
The set goals could be different, depending on the objectives of each organization, such as target capacity rate, time for order processing, level of available safety stock, achieving optimal safety of employees as well as cybersecurity, rate of inventory turnover, number of damaged, lost, or wrong orders, etc.
Only after the company has established its goals, it may proceed to the next best practice: set clear PIs, which to be aligned with the created performance objectives.
But let's not delve deeper just yet.
In a warehousing plant, there are millions of performance indicators, from stock availability, though assembly (or consolidation) line operational capacity, to the total time of a single order processing cycle.
And taking into account that each year the average size of the US warehouses expands tremendously, we can expect many more NEW indicators to appear in the near future. Because bigger plant means increased operations, and thus, more variable factors, tasks, and motion to measure.
In fact, the numbers show that in the year 2000, the average warehousing size was 65.000 square feet, compared to 2017, when it was measured to be 181.370 square feet.
But what is crucial for setting up a high-quality data dashboard is identifying and recognizing the KEY performance measurable indicators, which gives us insights about the efficacy of operations, tells us if we meet our business goals and objectives, as well as what is our progress for achieving those.
By using such metrics, we enable the tool to provide us with data-driven information for decision-making, without overwhelming us with excessive amounts of data at a time.
In order to get the most value from the KPIs measured in the data dashboard, we should be patient, yet time-bound.
By giving the tool enough time to collect, analyze, and present enough data in terms of the set metrics, we enhance the quality of the analytics we see.
Think about it: Using data collected in one month is far more reliable and credible for analytics than using only one week's data. This way we can better see established trends and tendencies in our warehousing operations, as well as recognize different performance patterns. For example, the average internal order cycle time (according to one week's data) could be 4.5 hours, as the same indicator shows 3.6 hours based on monthly data.
To achieve an increased quality of analytics, it's crucial to be consistent, yet flexible with the KPIs we implement into the data dashboard. Frequent change of the indicators often leads to results, which are not trustworthy, but instead are time-biased because we haven't put enough data into them to achieve a high level of reliability.
On the other hand, we shouldn't let the data in our dashboard become obsolete or outdated because this way, we risk diminishing the credibility of our metrics and results. What is more, when warehouses hold on to the same indicators for an extremely long period of time but change their micro-goals meanwhile, they break the alignment between those two factors and lose the excelling value of the dashboard's insights.
In the dashboard, data contents are useless and incomprehensible to the management and stakeholders of the warehousing entity, if they are not visualized in a clear, simple, understandable, and logical manner.
In fact, there is a great rule created for this particular practice: The 5 Second Rule.
It generally consists of a single guideline regarding the dashboard: to provide relevant information and enable quick "answers" of often-asked business questions related to organizational goals in 5 seconds.
By following this rule, warehousing companies can get the most important data at a glance, and only later are they provided with more detailed statistics (if required). And to comply with it, there are several points to take into account:
- Choose appropriate colors (e.g., blue and green for basic data and red or pink for critical points)
- Adopt logical sequence of KPIs (starting from broadest and going towards more narrow metrics)
- Choose simplistic and not overwhelming layout design (keeping only the most important data at a glance)
To set up an excellent data dashboard for our warehousing business, we need to be consistent, patient, and time-aware. The goals, KPIs, the consistency of our analytics strategy, and the high-quality visualization are the four steps that will help us to make the most out of this BI tool and achieve better awareness of the warehousing performance and efficiency.