What business management software or system does your company use for accounting and automation of business processes?


We compiled the available and used ERP (Enterprise Resource Planning) systems in Latvia, which are also called enterprise/business management systems, business resource management software, resource management, enterprise management or enterprise resource planning systems.


Both international and Latvian ERP systems are available on the market. Each of them differs with its functionality, suitability for larger or smaller businesses, and the degree of complexity of introducing and adapting business process management. Let us not compare or describe each of these systems, but we offer insight into what will help in the first step in looking for ERP systems.


In the next survey, you will be offered a list of the ERP system suppliers and consultants in Latvia.


International ERP software systems: Microsoft Dynamics NAV, Microsoft Dynamics 365, 1C, Oracle E-Business Suite, Oracle Fusion Cloud Applications, SAP Business ByDesign, SAP Business Business One, SAP Business All-in-One (S4), HansaWorld Standard ERP, Epicor, Epicor iScala, webERP, Sage X3, QAD, Monitor ERP System, IFS, Odoo, Directo, and Infor.


ERP software systems made in Latvia: VISMA Horizon, Ozola, Moneo, Kentaur Integra, Norgate, GrinS 5, Ankrav and FinaWin.



When you are thinking about a business management or a resource planning (ERP) system and how to optimize business processes, then start with two simple questions: What you want to do with this software and what functions do you need to automate?


Visit “RIGA COMM” exhibition and meet ERP system suppliers and consultants.

Follow the news of the exhibition: facebook.com/RigaComm/

GO-ERP is a Microsoft Gold partner specializing exclusively in Microsoft Dynamics 365/AX solutions. Our teams are trusted to deliver reliable, high-quality, customized ERP solutions.


We differentiate ourselves by the proactive manner and tailored solutions, aiming to improve Clients’ business competitive advantage. Working closely on daily business tasks we get deep into the Clients shoes so we care to bring the real value to their business.


We have the flexibility to respond quickly and adapt to technology changes, and we have the skills and resources to handle major projects for enterprise Clients throughout Europe. GO-ERP is a financially stable organization, making it an ideal business partner for the long-term relationship.


More than 17 years of a broad MS Dynamics 365/AX international experience, high ethical standards, and a personal touch help us to build trusted relationships and ensure real business value for our Clients. We know the full potential of Microsoft Dynamics 365 so our Clients can rely on us when utilizing the software in the most efficient way. By continually investing in our knowledge we differentiate by our commitment to ensuring the very best professional services as well as our innovative approach to new technologies.

Learn more: www.go-erp.eu

By Aldis Ērglis, Intelligent Machines Riga


We are already experiencing an impact of Machine Learning approach in business. We see it in Google search, on Amazon or Netflix recommendations. It means companies with large data amounts can feed learning algorithms with right data and get amazing results in decision making or decision support field.


Machines will learn faster and more accurately than humans for sure, and we are not talking about smart Robocop, AI like machines but even simple statistical algorithms, like described in Daniel Kahneman, HBR article Noise – https://hbr.org/2016/10/noise. Even more, most of algorithms and models are available and most are for free, like more than 12000 R packages available on the internet.


So, technically all companies can start using Machine Learning to create additional products and services, add intelligence to existing products and services or reduce costs by automation even in decision-making field but mostly in decision preparation for decision makers.


Why cannot all companies do that? Because Machine Learning needs a lot of good quality data to learn right things. Few companies are already collecting or let say mining data from their processes, customers, employees, and systems for Machine Learning purpose. And believe or now for good ML different data is needed. For example, to analyse and learn from processes you need the collect duration of operations instead of date and time of state. That is different data than ERP currently collecting because the purpose of data is different. So, it means to implement Machine Learning we need to rethink all data we are collecting and start collect data for ML purpose. Sources of data will be behind your organization boundaries, additionally to data inside the organization you need to collect data from the internet about your customer – using Competitive Intelligence approach and so on.


Is data a new Oil? Forbes argues in the recent article (https://www.forbes.com/sites/bernardmarr/2018/03/05/heres-why-data-is-not-the-new-oil/#1af3b1973aa9) that data is not new Oil. Maybe comparing very precisely it is not. But I see some analogies that will help business leaders to think about data in the better way. To run the economy as we use a lot of raw materials, oil is needed, and during years we found how to discover, get, and use oil. The same idea with data, you can’t use any data you have, you need to discover, build up mining process, control quality, distribute it and use for the right purpose. Not all oil we can get from earth is usable so the data even more.


I see that organizations will be under pressure to change their mind because of competitive advantage of using ML. So, companies need to start with thinking how ML can help achieve business strategy and create ML strategy. ML strategy will show in what areas, processes you need to collect good data. And even if you are not doing any ML, find out and start collecting data, it will take time and will not be possible to do it overnight. So, collecting right data is your competitive advantage.


Visit the RIGA COMM 2018 Machine Learning Practical Application Conference on 11 October to find out more.

Follow the conference page: https://www.facebook.com/events/432218577193046/