Our Data Science approach is unique in the market – and it can benefit you.
At CTI, we created The Daisy Project, a business unit focused on data science that has its own methodology. Our approach combines three fields: technology, data science, and business transformation, and it has set us apart, as we believe it’s important to integrate knowledge, technological tools, and business-oriented strategic thinking to ensure efficient innovation initiatives. For this reason, we integrate data science and artificial intelligence into business decision processes.
- We believe you are the best person to reflect on and understand your own business. For this reason, we invest in a methodology and have the experience to learn quickly with you and understand what drives your business.
- We are in contact with experts in technology, data science and artificial intelligence to gather their experience so that, together, we can identify challenges and build innovative solutions with an impact on your company’s economic and financial results.
- We believe that every innovation has risks that must be controlled. Then, we seek to develop functional products (minimum viable products) quickly and efficiently. With pragmatism and objectivity, we are able to test concepts in up to 12 weeks, with reduced cost and fast route adjustment ability before scaling our solutions for operation.
- We use flexible business models, because we understand ‘one size does not fit all.’ We offer alternatives, such as cloud solutions, custom artificial intelligence APIs, and insights as a service (IaaS), ensuring the best total cost of the solution. We also develop solutions using traditional projects with on-premise technology.
- We appreciate technological independence. We are not exclusive to a specific technology provider as we seek to partner with the most interesting and appropriate solutions for every customer’s context.
- We believe the digital tsunami is irreversible. High computing capacity (cloud and big data) – combined with the ubiquity of data (mobile and Internet of Things) and new computing techniques (machine learning and artificial intelligence) – has deeply transformed markets and traditional business models.
- Then, we believe the digital transformation, together with industry 4.0, are above all organizational changes in business models, culture, processes and people, going beyond the underlying technological changes.
- We understand that Supply Chain 4.0 is strategically oriented to the individual needs of end consumers, integrated through consistent application of computational intelligence and digital technologies, from strategy to execution.
- For this reason, we believe that an effective digital transformation process must start with deep and consistent reflections on business DNA and value drivers, not with technology.
- In this context, we believe in the development of business solutions based on data science and applied scientific knowledge, which are conceptually consistent, technically viable and effectively able to transform businesses.
We have provided consulting services for business transformation, financial management and technology for more than 25 years. This experience has supported the development of our own methodologies to quickly understand your problem and your business. With a systematic approach and the business background of our consultants, we quickly identify relevant challenges, generating internal alignment and consensus on real value gains.
We use our data science and artificial intelligence knowledge as new tools to address your challenges. We combine traditional statistical, simulation and optimization models with modern machine learning and artificial intelligence models to provide the best solution. We don’t reinvent the wheel. We rely on scientifically proven techniques for specific domains, with accelerators for descriptive, predictive, simulation, optimization and machine learning models.
We know the technological platforms used by our customers are not always the most suitable to address the challenges related to the Digital Economy era. Therefore, we have technological knowledge to implement viable solutions with an adequate cost-benefit-time ratio. Even if your data aren’t perfect or your budget is limited, we combine cloud, on-premise, proprietary, and open source technologies to ensure custom solutions with a proper level of cost and efficiency.
High computing capacity – combined with large amounts of data and new computing techniques – has resulted in a completely new set of paradigms and tools to solve consumer or organizational problems. According to recent studies, these new technologies will cause radical changes in the value proposition of existing businesses, significant increases in organizational agility with the ability to address consumers more individually, and drastic reductions in operating costs.
The easy part of transforming business is the consistent investment in new technologies. On the other hand, the difficult part involves the implementation of new operating models, sometimes in direct conflict with the current cash cow. To overcome this challenge, technology must be connected with the organizational beliefs, including deep reflections on the value proposition of the organization. To support you in this process, we’ve developed three products:
- Data Science Advisory: this service was designed to help organizations innovate their current business model by building data science capabilities. Using modern co-creation and design thinking practices, we identify the latent challenges to potential data science use cases. We conduct the assessment and prioritization of these use cases, which result in an organizationally consistent, aligned, and consensual digital evolution program (roadmap). Our proprietary methodology, refined by years of experience in digital transformation, addresses three major dimensions: business maturity, technological maturity, and data science maturity.
- CTI Business Lab: aiming to accelerate the development and testing of the operational viability of every solution identified to address your problems, we created our own laboratory, which operates in the cloud environment and combines modern technology, methodology and technical competence. With our lab, we, together with our customers, are able to build and test solutions quickly and efficiently, usually in eight to twelve weeks, without investing in software, staff or infrastructure. This way, we invent with you, seeking to turn each invention into an innovation of real value.
- Projects and organizational transformation: we understand that value creation takes shape only when a prototype becomes a real product or process. With vast experience in consulting, technology and transformation projects, our projects seek to build scalable solutions, effectively implemented with longevity in the organization. They are custom projects designed to fulfill the specific needs of every customer.
Supply Chain 4.0
One of the main areas impacted by new technologies is supply chain management. With the challenge of managing complexity and balancing cost and efficiency with agility and flexibility, traditional chains are forced to restrict the individualization degree of the offer. However, the consistent application of new data science technologies allows businesses to overcome the traditional compromise between flexibility and efficiency. We combine specialist knowledge of supply chain management with technology and data science, specifically providing supply chain planning for the following areas:
- Individualization of sales drivers: by applying data science and machine learning, we offer solutions to automatically individualize the offer based on the identification of consumption patterns. It allows the company to automatically optimize the product portfolio and functional attributes, suggest dynamic pricing to specific consumers, individualized promotions, and automatically segment and classify customers, portfolio or points of sale.
- Integrated demand planning: based on defined sales drivers, we use advanced forecasting algorithms and time series techniques combined with neural networks for specific and complex behaviors, such as intermittent demands, trends, seasonality or non-stationary cycle.
- Inventory, production and distribution optimization: based on the anticipated needs, we use linear, non-linear and mixed integer programming algorithms, combined with stochastic algorithms to define optimal safety stock policies in the system, and the definition of optimal integrated production and distribution plans.
- Financial analysis and simulation: in order to maintain the bottom line in business, we have combined supply chain management with the operational plan and multidimensional financial vision, defining profitability by product, channel, region, etc. The ability to quickly simulate scenarios allows better decisions in an effective closed-loop decision-making process.