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Every organization that wants to move forward, recognizes the importance of data. In a digital market, it’s the sole thing that translates the subjective impact of your product or service into quantifiable information. Think about customer satisfaction ratings, business reviews, cost-per-click, number of impressions or audience sentiment. But why is it, that data often remains an idea that lives within your organizational structure without being put into practice, or living up to the expectations? Here are 4 reasons why your data doesn’t bring you profit, and how you can solve that.
Metrics and KPIs are often confused. A KPI is a Key Performance Indicator or measurable value that shows how you are meeting your business objectives. A metric, however, is a quantifiable point of measurement that you use to assess the status of the process leading to that objective. In other words, a KPI can consist of a number of metrics, but a metric is not a KPI.
As the name says, a KPI is a key indicator. So, what is it not? Something to endlessly invent and install to measure your objectives. To make a KPI work, you need focus and alignment. This means only using 3 to 5 KPIs that don’t contradict each other and that pose clear steps to influence that KPI.
Silos complicate everything, and the same goes for using your data. To make intensive use of this data, separate tooling is a threshold that needs to be eliminated. Instead, you should focus on showing the analytics in places where the user is working. Examples of this are Salesforce Data Pipelines or the Salesforce Einstein, who natively embeds analytics in your tooling. This gives you instant, real-time and applicable information where you can adjust variables to see the impact. This goes for analytics, as well as for project deadlines, consumer metrics, KPIs, and so on.
But, too much consolidation without further action, is even worse an option, as we read on in the 4 reasons why your data doesn’t bring you profit.
Another pitfall is when you’re consolidating your data too much without using it as a starting point for improvement. Often, we see businesses having the right metrics, KPIs and numerous reports and dashboards to visualize and report on the data they gather. They even have an all-in-one tooling kit they use to overcome the silo threshold. And still, the data doesn’t ‘deliver’. Why? Because everyone is so busy with integrating, visualizing, and consolidating the data, that there’s no time left to interpret it!
Besides having the right and enough people on board who can work with your analytics, you need to make sure you have a process in place to use data as a something that gets you started, rather than an end point. Now that you know what works and what doesn’t, what steps are you taking to solve the problems that data uncovers, and to act on the opportunities it brings?
So, you must find that sweet spot in between consolidating and over-consolidating to optimize your use of data.
Not having the right data, usually leads back to 2 reasons: either your Sales Reps don’t take your CRM seriously, causing them to enter little to no data. The other reason is that you’re not automating your data enough, so you are not always working with the correct analytics.
You can consolidate, integrate and visualize all you want; if you’re using the wrong numbers to do so, all that effort is lost AND you’re making decisions that won’t add up with reality.
Not automating your figures can have many causes, the main one being that people think automation processes cost a lot of money and time to set up. Though the implementation of these processes are indeed an investment, they will save you time and overhead cost in the long run. Both because your teams have time to do less repetitive, but equally important tasks, and because the automatization eliminates human errors.
Gathering data, there are multiple pitfalls to overcome if you want your analytics to bring you actual profit, rather than remaining a black box.
Make clear distinctions between metrics and KPIs. Choose no more than 5 KPIs per project and make sure they don’t contradict each other.
Step away from that silo mentality and separate tooling to eliminate thresholds in interpreting and using data. Solutions like Salesforce Einstein natively imbed analytics in your tooling for real-time reporting, everywhere and for everyone.
Don’t over-consolidate your data to the point where you lack time to actually interpret it and use it as a starting point for improvement. Only then can data be your best bud in overcoming challenges and take full advantage of opportunities.
Automate your data to avoid misconceptions, save time and eliminate human errors.
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Estimated token costs for common ticket types
TICKET TYPE
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Update 5 users with new configuration of access rights (permission sets, profile or public group) and update “City” on a user record
100
Add 5 new fields to a report and modify 2 filtering criteria
100
Develop automation to update the case whenever a certain condition is met and trigger notification
500
Updated Apex class and LWC to present data in a table like format
800
“My automation is breaking – I don’t know what is happening”, support agent work: Investigation or issue, correction of a SF flow, documentation of changes, presentation to a user
600