“Digital business is accelerating interest in AI at a pace that has left many CIOs hurrying to build an AI strategy and investment plan appropriate for their enterprise. ”
– Gartner, “The CIO’s Guide to Artificial Intelligence”.
Not having a strategy, is not a strategy.
Successful Intelligent Automation is more than a model. Strategies need to deliver value that aligns your people, process and technology.
A Gartner 2018 CIO survey indicated that 70% of companies have limited or no understanding of artificial intelligence strategies and technologies.
What is your AI strategy?
We can help you understand the technology opportunities, and align your business goals to develop a comprehensive strategy for Intelligent Automation.
Seventy percent (70%) of a data scientist’s time is spent finding, collecting, cleaning, and preparing data. Data is the foundation of all AI models. Poor data quality can cost businesses > 20% of their operating revenue.
Whether it is IoT, big data, data warehouses, web, ERP or external sources, your data has value. We work with you to identify a data strategy to create a diverse, quality data solution that is extensible, beyond the modeling.
PROCESS AUTOMATION ASSESSMENT
More than 50% of process automation opportunities are missed by organizations.
Using Robotic process automation (RPA), we can find opportunities to automate your processes. RPA alone can shorten process time, get more done, and increase quality by eliminating errors in data entry. AI embedded in RPA offers enhanced Intelligent Automation, achieving prescriptive analytics without hard-coding software rules.
Anything that can change will change: decisions, regulatory requirements, internal systems, external systems, technology standards, data standards, priorities. Flexibility, speed, and cost control are the new mandate for today’s technology.
We help you analyze what you have, what you need, and rationalize your architecture. There is no single solution, but we can help you create a single strategy to reduce development time, and create repeatable, agile solutions.
We fear what we don’t understand. Intelligent Automation doesn’t replace jobs; it makes your people more effective. A solution isn’t successful if your people don’t trust or use it.
We work with you to identify the value, communicate with your teams, and prepare the way for increased effectiveness.
“Any intelligent fool can make things bigger and more complex. It takes a touch of genius — and a lot of courage — to move in the opposite direction.” – Albert Einstein
Intelligent Automation Strategy
We believe the best strategy is to start with the end in mind, i.e. your business objectives. Many companies focus on the model, and miss the necessary considerations for a complete solution.
AI and Intelligent Automation is automation to create prescriptive analytics. Thinking strategically is necessary to identify the fundamental (core), incremental, and transformational opportunities. This combines the power of process and intelligence into a continuous operational lifecycle from data to production operations.
Business Opportunity – Identify the value and what problems AI can either innovate or augment in existing processes. Whether it is finding the out-of-the-box solution, building a model from existing technologies, proof of concept, or innovation on a new model idea, we find a path.
People and Organizational Readiness – Collaborate and pave the way for humans and machines to work together. Unlock efficiency by combining the power of people and intelligent automation.
Data Management – Find the data, and put it to work. Create a data management architecture that enables data science exploration, modeling, and future model refinements.
Process Automation (i.e. prescriptive analytics) – Find opportunities for prescriptive analytics, i.e. automation that has a twofold benefit of automation and AI powered decisions.
Technology Selection and Rationalization – Create an infrastructure to enable quality data, accessible data, process integration, and operational execution. Envision the capability to manage change over time while reducing risk and error.
Intelligent Automation Design and Development
We understand that Intelligent Automation is about operationalizing your data into decisions and actions. To operationalize artificial intelligence, people, process, and technology must align to realize your objectives.
We utilize an agile approach to each project in your roadmap to achieve an effective solution focused on priorities.
Process – All organizations have repetitive, rules-based processes
usually performed by people sitting in front of computers. Automation isn’t process re-design, but identifying the opportunities to leverage software to perform these specific tasks.
The strategy drives the priority of automation to achieve speed and efficiency. Further efficiencies are gained when you have an artificial intelligence use case that can automate processes, creating additional efficiency.
People – Intelligent Automation solutions are ineffective if people don’t use it or they don’t trust it. People are always involved. Develop an understanding of the user behavior, the context in which decisions are made, and determine the desired business goals or outcomes.
Identify the key enablers of, or barriers to, behavioral change and create a dialog that makes behavioral change easier on users. Engage and validate through an effective test process, validate its value compared to the role involved, and refine. Engage the user in the process for understanding, and acceptance.
Data Management – Data drives insights and is mandatory for effective artificial intelligence which generally requires large datasets. Data management design creates solutions for ingestion, storage, security, access, and exploration for modeling. AI models are only as good as the data used to create them.
Create an agile data environment that enables access, preparation and experimentation with data across organizational silos and applications.
Modeling and Analytics – This is where the data turns into intelligence. Whether you utilize a third-party solution, or create your own model, the model is the engine.
● Proof-of-Concept. Not sure yet? Let’s get sample data, and demonstrate what can be achieved. With readily available, quality data, a PoC can be created in weeks.
● Model Development. Data scientists or model engineers apply a technique, evaluate the data, and build a model to meet the defined objectives.
Technology – Artificial intelligence is a deployed asset. It has a lifecycle from data to operational use. There may be technologies that can be leveraged, but not all are compatible with or a fit for your objectives.
Technology and infrastructure should be designed to maximize your value, manage cost, create agility, and support a repeatable, scalable process for Intelligent Automation.
Intelligent Automation Operations and Governance
Intelligent Automation leveraging data management, artificial intelligence (cognitive intelligence), and process automation will change how companies work and impact many areas of the business. AI technology is young, and will continue to evolve over the coming decades.
Operations – The business world isn’t standing still, and automating processes requires monitoring and revisions as your environment changes. Models should be monitored and audited to validate predictions or review performance. Continuous evaluation is used to ensure that as conditions change, the model continues to perform acceptably. Lifecycle management provides the mechanism to deploy new models, or revert to a prior model as needed without guess work.
We help you design a solution to meet the ongoing needs of a production solution, and maintain its integrity.
Governance – If you are going to invest in a strategy to improve your business, then governance, oversight, and reassessment are required. Whether it is your stakeholder buy-in, roadmap re-evaluation, prioritization, or gaining employee buy-in, execution is key.
We help work with all areas of the business to pursue a successful execution of your roadmap, projects, and operational readiness.