Scimus

Business Development Manager

My day-to-day tasks were: 
- researching industry trends, competitors, and market conditions to stay informed and adapt sales strategies accordingly
- establish, develop and maintain positive customer relationships
- develop and maintain outreach sales processes for LinkedIn, Mail and Upwork
- identifying customers' needs

My learning points:
- failures help you to think out-of-the-box
- persistence is a key
- first - listen, second - help (not sell)

Growth Manager

Translator

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• Conducting research and analyzing the business performance of business partners and fulfilling customers’ needs.
• Create, plan, and deliver presentations on company products.
• Establish, develop and maintain positive business and customer relationships.
• Coordinate with other team members and departments to optimize processes.

Sales Development Specialist

AIESEC

Leading 6 Team Leaders with regular O2Os (40+), department meetings (60 in general), MoSs & KPIs setting and tracking, membership onboarding
Servicing customers before and during their experiences and providing needed standards of quality(improved conversion of quality from 85% to 91%)
Updated servicing flow which helped to get more interaction with customers
Synergy within Sales and Customer Service teams
Sales strategy creation and execution

Head of Customer Experience and Sales

Key responsibilities:
Leading a team of 2 people
Conducting calls and meetings with current accounts(conversion from call to meeting improved from 10.7% to 16.5%)
Generation of leads and market segmentation(93 new leads)
Sales strategy plan execution

Key achievements:
New Sales - 3 new companies
Account management - 5 accounts
Access to the new region

Sales Manager

Business Development Manager at Scimus | Helping businesses to go from Good to Great through automation

Hey! I’m Nelia, your Business Development Manager from Scimus, where I'm dedicated to transforming businesses from good to great through innovative automation solutions. 

With a background in sales, project management, and strategic thinking, I'm swimming in environments that demand creativity and adaptability.

At Scimus, my role involves understanding the market needs, fostering customer relationships, and developing effective sales strategies. Over my 3 years in sales, my experience has honed my skills in identifying customer needs and tailoring solutions that align with their objectives.

I’m always open to discussing how me and Scimus can assist in your business's growth journey. Let’s connect and explore how we can take your business to the next level.

nelia.kaminska@thescimus.com

Accounting vs. Automation

In the era of data-driven decision-making, consulting accounting firms face the colossal task of structuring vast amounts of data for effective analysis. 

The challenge? 

Ensuring accuracy, efficiency, and scalability.

But there's a way to get out of here👇


#automation #accounting

Nelia Kaminska

Accounting and automation

Why LLM models are not working well within specific industries?

A perfect example comes from a recent challenge faced by one of my prospects in the healthcare sector.

They attempted to use OpenAI's API to categorize charge descriptions for medical billing. These are often written in shorthand and packed with abbreviations unique to healthcare. For an AI trained on a broad range of information, deciphering these abbreviations is like trying to read a foreign language with multiple meanings for each word.

In healthcare, where precision is critical, such ambiguities can lead to misinterpretations that affect billing and, more importantly, patient care. 

This underscores the necessity for AI not just to be intelligent, but to be intelligently aligned with the sector it serves.

Through this example, we see the broader lesson: 
--While LLMs like GPT-3 offer vast potential, realizing their full benefit in specialized fields requires a nuanced approach. 

It's a fusion of AI's computational power with the deep, contextual knowledge of industry insiders.

Agree?

Data-driven decision making

As businesses grow, the integration of advanced analytics across all departments not only becomes an asset—it becomes a necessity. 

But what happens when these powerful analytics tools cross paths with accounting? 

Magic!

Take COMPANY X, which integrated its operations and sales data with accounting analytics. They experienced a remarkable 30% boost in revenue forecasting accuracy and reduced financial close times by 50%.

Then there’s COMPANY Y, who applied HR analytics to their accounting strategies, optimizing labor costs and benefits expenditures by 20% while enhancing workforce productivity.

Benefits of cross-departmental analytics:

1. Enhanced forecasting accuracy: Merging sales, marketing, and customer data to predict financial trends more precisely.
2. Optimal resource allocation: Using insights from production and supply chain analytics to improve budgeting and investment decisions.
3. Improved regulatory compliance: Leveraging data from various departments to ensure all financial practices meet legal standards.

The result? 

A holistic view that enables smarter, faster decision-making and a robust bottom line!

Why businesses should care about automated data analytics 

It refers to the process of using automated tools and algorithms to analyze large volumes of data quickly and efficiently. 

These tools can automatically collect, process, and analyze data from various sources, such as databases, sensors, or software systems, without the need for manual intervention.

Why businesses should care about it:

1. Efficiency: Automated data analytics tools can process large volumes of data much faster than manual methods, saving time and resources.

2. Accuracy: By automating data analysis, companies can reduce the risk of human error and ensure more accurate insights.

3. Scalability: Automated data analytics tools can scale to handle growing volumes of data without requiring significant additional resources.

4. Real-Time Insights: With automated analytics, companies can gain real-time insights into their data, allowing for faster decision-making and responses to changing conditions.

5. Cost Savings: By streamlining data analysis processes, companies can reduce costs associated with manual labor and improve overall operational efficiency.

6. Predictive Analytics: Automated data analytics tools can leverage machine learning algorithms to identify patterns and trends in data, enabling companies to make more informed predictions about future outcomes.

7. Competitive Advantage: Companies that effectively leverage automated data analytics can gain a competitive edge by making faster, more data-driven decisions.

--- Automated data analytics is a competitive advantage in the marketplace.

Agree?

Vertical AI and Accounting

Unlike horizontal AI, which offers broad applications across various fields, Vertical AI is designed with a laser focus—targeted to revolutionize specific industries. 

For accounting, this means smarter, faster, and more reliable processes.

Why Vertical AI in Accounting?

1. Customized precision
- Vertical AI understands the unique language and intricacies of financial data. It’s not just about automating tasks; it’s about enhancing the precision of financial reports, tax filings, and compliance processes with bespoke AI models trained to handle complex accounting tasks.

2. Proactive insights
- With its ability to process and analyze vast amounts of data, Vertical AI offers more than just automation—it provides foresight. Predictive analytics help foresee financial trends and risks, empowering businesses to make informed decisions swiftly.

3. Enhanced compliance
- Staying up-to-date with regulations is a moving target that can consume significant resources. Vertical AI stays ahead of the curve, continuously learning and adapting to regulatory changes, ensuring compliance is seamless and integrated.

4. Efficiency at scale
- Automating routine tasks like data entry and reconciliation frees up valuable time for accounting professionals to focus on strategic activities. Vertical AI doesn’t just streamline processes; it scales them efficiently without sacrificing quality or compliance.

The adoption of Vertical AI in accounting promises a future where accountants can rely on AI to handle the complexities of their work, allowing them to focus on what truly matters: strategic decision-making and business growth.

AI's Future Learning

Yann LeCun sparked a big talk at Davos 2024 about kids learning vs. AI. Here's what we can learn:

Jobs: AI is cool, but humans bring something special: creativity and understanding.
- Jobs needing these won't disappear. 
- Use AI smartly without forgetting human skills.
- It's the human touch that makes a big difference in many jobs.

Not Too Much AI: AI helps, but it's not perfect. 
- Let's not rely on it too much. 
- We need to mix AI with human thinking. 
- By blending AI with human judgment, we can make better decisions and avoid relying too heavily on technology.

This dive into the comparison between a child's learning capabilities and the current state of AI sheds light on both the potential and the limitations of these technologies. 

It's a reminder of the incredible journey AI is on, and the role we all play in shaping its path forward.

What people think automation is vs. what automation is

Expectation: RPA is like hiring an army of robots, lots of coding, what the heck you are telling us 😂 

Reality: Automation advances processes for more accurate data-decisions, cuts down time on unnecessary tasks and simplifies complex workflows.

While it won't replace humans, it empowers teams to focus on high-value work. 

The case:

A petroleum company wanted to lower its costs to maintain its competitive advantage. By delegating RTP tasks to RPA bots, the proof of concept showed that there was potential for the company to reduce the manual efforts by 65-80%, expedite the RTP process by 4 times, and save 1,700 man-hours annually.

It's not too late to start changes in operations.  Even if it seams working aligned, there's always a space to do better.

While talking to CFOs, I often start noticing complicated, overwhelming approaches to some tasks. Mainly because most of them are still done manually. 

When I ask them, why they don't implement automated reports or data validation tools, they mostly answer that but staying ahead of risks and ensuring compliance is a challenge and a long transformative process.

Believe or not, it's way more simple than you think. 
For example, a simple flow of automated risk & compliance:

1. Data Collection & Integration: Automated tools gather and centralize data from various sources, creating a solid foundation for analysis.

2. Risk Assessment
Real-time monitoring and machine learning algorithms assess risk, assigning scores and identifying anomalies instantly.

3. Compliance Checks
Automated compliance rules and periodic audits ensure adherence to regulations, flagging any issues proactively.

4. Alert Generation
Real-time alerts and detailed reports keep stakeholders informed of potential risks and breaches, facilitating swift action.

5. Action & Resolution
Workflow automation streamlines the resolution process, documenting actions and creating a clear audit trail.

6. Continuous Improvement
Feedback loops and regular updates refine the system, adapting to changes in regulations and industry standards.

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