Updated: Nov 4
Manual data processing like phone calls, emails, and report exchange - is a normal form of integration in a system at a small scale. Programmatic integration requires a unification of data obtained in one process that needs to be fed to another process, as well as the tools that can store and pass the data.
How to tell when it's time to say goodbye to manual integrations? Here are the signs that might mean that your organization has reached the line:
☎️ People are hired solely for data input and processing
✍️ Employees sacrifice their direct responsibilities in favor of routine data processing
🙀 The number of human errors is increasing
💸 The cost of human mistakes is increasing
⏳ Data exchange and communication time between departments is increasing
🙄 Groundhog’s Day symptoms: for instance, people continue asking the same questions
Let’s look at conventional palliatives and the risks they carry:
1. Hire more people with less expertise in data processing.
This is a short-term solution. The number of human mistakes will grow proportionally to the staff size. Let alone that hiring people for dead-end jobs is bad for your karma.
2. Get a bot for your self-service or hotline
It may work for some businesses, but remember that a chatbot is a crutch for an anti-intuitive interface, bugs, and bottlenecks. Have you ever called a hotline and ended up shouting “Call a human” at the bot? It happens all the time.
3. Introduce one-purpose solutions here and there
As comprehensive market-leading solutions are costly and unlikely to pay off , many companies introduce dedicated tools that address exact pain points for certain processes. Eventually, they end up having different tools for CRM, Marketing Campaigns, Project Management, Risk Management, etc. Decentralization of data leads to inconsistency. Lack of integration between the tools leads to process bottlenecks and silos. Poor adoption eventually causes shadow accountancy and a return to manual work. Every integration and optimization turns out to be a project.
4. Get a swiss-knife solution with all tools and integrations
This is a silver bullet trap. Companies barely hit 31% of the expected revenue lift after a digital / AI transformation . The main issues are super-complex configuration, conservative interfaces, and tons of unneeded product functionalities yet missing essentials for certain operational processes. The organization becomes dependent on such a platform, but custom development is costly.
Is there a way to digitize your business for good? Well, there is no algorithm - every company has its way to a high-tech future. Instead, there is a strategy.
Create a Leadership - Staff - Development triangle of trust and open communication
Make top performers your adoption disciples 
Choose tools based on their scalability and extensibility rather than “here and now” Perfection
Act and build in the context. Abstractly perfect solutions don't work
And the don'ts.
Don’t try to finish it once and for all. Iterate, test, adjust
Don’t cut costs on people training. People get involved this way
Consult, but don’t rely too much on auditors and advisers. They have their interest
Don't substitute fundamental knowledge with practice and vice versa. You'll need both
 Salesforce Return on Investment 2010-2023 | CRM - Macrotrends
 The Value of Digital Transformation - E. Lamarr et.al. Harward Business Reviews
 Ninja Performers in Stealth Mode Challenge Digital Transformation - PartnerAlly