Spekit is excited to launch three new features to improve your training & documentation with our Salesforce data dictionary. Check them out for yourself in our self-serve demo.
1. Import and document your picklist values
Does your team struggle to remember the steps required to move an Opportunity from “Prospecting” to “Working”? Using Spekit, you can select a mission-critical field like “Opportunity Stage” and import each picklist value into Spekit. You can then define the requirements to move from “Stage A” to “Stage B” at a granular level. Your end-users can use our Chrome Extension to access these definitions directly in Salesforce by highlighting the picklist value in question.
2. Toggle between columns
Spekit is designed to be the source of truth for business knowledge on your data for all employees, not just Salesforce users. That’s why we created the data wiki in a user-friendly, tabular format. Our new Custom Toggle feature lets technical users adjust the data points displayed in the to meet their particular use case. You can use this to help bring business context to your code for technical teams.
3. Import Installed Packages or System Objects
You can now document any object in your Salesforce data dictionary, including Installed Package Objects and System Objects by going to the Object Manager screen and importing any object of your choice.
That’s all for now folks. Make sure to email email@example.com to get started or share your feedback!
Next release: Create Custom Columns in the data wiki
Every Salesforce org needs a way to keep their employees on the same page despite ever-changing sales processes, products, integrations, and data fields. This is where a Salesforce data dictionary comes in.
The highest-performing companies like Google and Amazon all share a metrics-driven culture, which gives them the ability to leverage data to make key business decisions. Unfortunately, companies looking to adopt this strategy often share a common problem: their underlying data is a mess. Why? Because they rely on employees to correctly enter their data into platforms like Salesforce. As a result, their data is only as good as their users’ understanding of it.
A Salesforce data dictionary is a central source of knowledge for the organization that describes data: its meaning, relationships to other data, business usage, and format. This tool helps everyone from management, admins, analysts, and developers to understand and use Salesforce data fields.
Using a data dictionary for Salesforce has a range of benefits across your organization.
1. Get your team selling faster
Remember that time you joined a new company and picked up all of their internal jargon immediately? Yeah, that didn’t happen. There’s a reason why it can take the average employee 2-4 weeks to ramp-up on their new company’s Salesforce org. And the hard part isn’t using Salesforce itself – most employees have either used it in a prior role or can easily leverage Trailhead to get a quick understanding of how to use the tool.
Instead, the real challenge is learning the intricacies of the company’s internal business processes: When to move leads from “Working” to “Prospecting”, or how to decipher the meanings and rules behind the custom fields and objects your company has created.
To further complicate things, these fields often consist of acronyms and industry-specific terminology that doesn’t get adopted overnight. Learning the difference between “LTC” and “LTV” is just as challenging to a new employee as memorizing the difference between “ser” and “estar” in Spanish class. In short – it takes time and practice.
Having an accessible and detailed Salesforce wiki with all of your fields, processes and other terminology defined is critical to get your teams spending more time selling and less time training.
2. Bring context to your code
Client-facing employees aren’t the only ones who need to learn the company’s business rules and definitions. Ask any software developer who recently joined a company: the hard part about learning their new stack wasn’t deciphering the code itself – it was bringing context to it. “What is that API name referring to?” “Why does this data point have this data type?” “Where else in the process is this API name used?”
This last example is particularly complicated with Salesforce due to the multitude of formulas, workflows, process builders, triggers and more, that a developer must take into account when looking to understand or make a change to any Apex code.
Database and CRM documentation, whether it’s in the format of a Salesforce wiki or technical data dictionary, is critical in getting your technical, and often, more costly employees up to speed quickly on the application they’re building or the architecture of your systems.
3. Reduce employee errors
If you’ve taken a workout class for the first time, you’ll remember awkwardly staring around the room when the instructor yelled “Eagle pose” or “Burpee” until you found someone to copy, even if they themselves were doing it wrong. That instinct to follow others is natural and in this case, inconsequential. When it pertains to company data, however, errors resulting from telephone games are costly.
An example is when a new employee wrongly moves an Opportunity record to the next stage in the process because their teammate incorrectly taught them to. Not only will this throw off your pipeline forecast, it will also affect your organization’s ability to rely on these metrics to measure KPIs around your revenue or business processes. This problem is accentuated in large or growing companies where, due to the large amounts of data, these individual errors often go unnoticed for longer periods of time.
Having your processes properly documented in your Salesforce data dictionary using Spekit and easily displayed in-context to the end-user can decrease the room for misinterpretation.
4. Integrate and report on data easily
- “Hi – I’d like to pull a report on the average portfolio amount by account but can’t find it”
- “Oh – that’s because on the account record that data point is called account size”
Does this scenario sound familiar? Probably more than you’d like to admit it. Similarly knowing that irr_c in Salesforce maps to rate_return in your internal database is not obvious to your developer either. It’s perfectly normal for companies to have multiple ways of defining a single term within their organization – our language wouldn’t be nearly as rich if it weren’t for synonyms. That said, when it comes to data reporting or system integrations – this can be a real pain.
This is especially true when handling the integration of databases that do not share the same vocabulary but do share similar data, such as when inheriting the CRM or database of a company during an acquisition or merger.
Capturing all of these synonyms and mappings in a single data dictionary or Salesforce wiki will reduce the constant friction and context switching endured by development teams and marketing analysts alike. The result: More time spent on getting stuff done.
5. Reduce costly turnover
Similar to that awkward moment felt by the new friend who didn’t understand the inside joke, lack of proper documentation around your company’s business terminology can easily make new employees feel lost. Your business jargon is often unique to your company and deeply embedded in your culture. Unfortunately this feeling confusion, or worse, stupidity is not discriminatory towards experience.
I’ll always remember hiring a brilliant VP of Ops who in their first few weeks of joining, had to constantly forward internal emails to me because a metric or acronym was referenced that they were not familiar with. This feeling only gets worse when you’re in a client-facing role and expected to respond to customer inquiries promptly. It’s no surprise that 24% of turnover happens within the first year of an employee joining their new company. At an estimated turnover cost of 33% of an employee’s annual salary, these consequences aren’t cheap.
In conclusion, in today’s age of Big Data, new roles like “Chief Business Intelligence Officer” and “Data Evangelist” are emerging every day. The market for AI-powered Business Intelligence or analytics tools is also increasingly competitive, with some of the largest data companies like Salesforce rolling-out their own game-changing analytics solution, Einstein.
I’ll be the first to admit that documentation is a pain, and often the last part of the process that anyone wants to be responsible for. But any well-documented organization will tell you that this investment is well worth the improved data quality and long-term efficiencies around faster development and on-boarding as outlined above.
What’s more, there are new solutions that help make this process easier than ever. Spekit, for example, is uniquely designed as a hybrid between a Salesforce wiki and data dictionary that meets the documentation needs of your technical and non-technical employees alike. It comes with a Chrome Extension that lets all users access your documentation directly in their workflow without ever leaving their browser. The best part: We have a free tier that you can use to create beautifully enriched help text for Salesforce, starting today. Click here to learn more about how Spekit can bring sanity to your Salesforce
*Survey conducted in October 2017 by Spekit