In an age of Disruptive Technologies and Data Overload - Where do you Start?
The Future State is now our Current State
iRobot, Minority Report, the Jetsons, Transcendence, Quantum Leap, Nerve, all just some examples of movies and shows, many of which at the time were just creatively entertaining us based on an imaginary world, and are now actually much closer to reality.
The future of technology some of us grew up without and only read, dreamed or watched films and shows about, has arrived and quickly become an extension of our personal and professional lives, and an integral tool for how we function. The days of memorizing phone numbers, writing hand written letters, and having thoughtful conversations with individuals in-person are becoming distant memories. We are even more connected than ever before while at the same time mentally disconnected.
Technology continues to evolve at such rapid rates consistent with Moore's law that our society has both been enabled and crippled by the volume of data we are producing and have access to. Some of the questions that everyone is trying to answer now are - what do we do with all this data, how do you respond and stay ahead of the flow of information, how do we access it and make sense of it, how do we apply the available technologies to produce the data that we can benefit from collecting, and how will this data help us answer questions or solve our problems?
These questions have opened up new markets and solutions with fancy buzz words that are thrown around such as Business Intelligence, Data Analytics, Big Data, Artificial Intelligence, Robotics, Process Automation...and the list goes on. These concepts have been around far longer than most people realize and albeit more mature today, are still far from being ready to be implemented as large scale solutions and the panacea that most consulting firms sell them as and clients similarly think of them as and are hoping for.
Starting the Journey
The more relevant decisions to be made now, are where to start in the journey where both the technology and Information Age is progressing so that your organization does not fall behind on their S-curve (as described by Clayton Christensen with disruptive technologies) and are positioned to adopt and implement modules of capability at the right time when the technologies are matured and the ROI for an organization is much clearer.
There are advantages/benefits to beginning this journey now as part of shaping the future of your organization to prepare for when some of these technologies and your organization are more mature. Below are some key considerations from my own experience across multiple industries and in the field of Continuous Improvement and Technology, that organizations should ask themselves in the journey to digitize, automate, and optimize their business.
What industry /line of business are you in, what is your mission and goals, and what are your measures of success? Depending on your industry - private or public sector, manufacturing, supply chain, financial services, retail, health care, development, transportation, defense, government, the application and relevance of certain technology solutions varies. In manufacturing and supply chain driven organizations, robotics and automation is more common and wide spread based on the nature of the processes, variables involved in producing an output, and volume of transactions being performed daily that have historically depended on the use of a combination of machines/equipment and humans operating the equipment including configuring the equipment based on the product line and customer order dating as far back as the 1950's. In transaction based environments, where processes have largely been a function of inputs and outputs handled by humans only more recently - the last 15 years using email, computer programs/applications, business process models and workflow solutions, SAP/ERP systems to handle corporate and financial transactions, still very much relying on the data inputs and entry of a human in the loop. We are still in an early stage of maturity and adoption relative to manufacturing environments and the systems in these environments are only as good as the processes they were designed and implemented after, and the adherence to these processes by the individuals responsible for performing the job functions - providing the inputs that generate the outputs. Bottom line - understand the size of your organization and scalability needed, the types of process activities and transactions performed by individuals, familiarize yourself with the technology you are adopting, understand what, why and how you would use the technology, evaluate the cost relative to what you would gain, make sure the current technology and processes are being followed and define measures that matter for your organizations performance tied to the Mission and that are attainable/measurable through the technologies and processes you have in place.
What is your current technology maturity infrastructure and maturity level? What technology systems and platforms do you already have in place within your organization - are you operating a current or any SAP/ERP system, do you have workflow/business process model solutions - SharePoint, ARIS, Appian, Blueworks, Capterra, iGrafx? How many systems do you currently have in place and what interfaces exist with these systems for collecting, managing and reporting? Understanding your current technology environment and barriers can better guide your entry point and what solutions you may benefit from or need before you can enable the organization to begin to mature towards something more automated and eventually cognitive - learning and rule based to make decisions or recommend solutions. Bottom line - understand what you currently have to work with and the effectiveness of your current tools/technology to capture critical data.
Do you have an efficient and continuous method for collecting customer feedback and input internally and externally? Many organizations completely overlook, infrequently collect, or have low fidelity in the methods and questions they ask to gather internal and external customer feedback/input. Recent industry studies performed have generated findings and data that shows a direct linkage between customer satisfaction and profitability as a function of existing customer retention and new customer growth. Bottom line - Understanding how satisfied your customers are including their needs, can help your organization stay focused on "value-added" activities and services that sustain and improve your relevancy relative to competitors or other organizations, increase internal productivity and improve the overall impact you are having on your customers and overall mission and financial goals. Customer data internally - voice of the business can help you improve your efficiency and effectiveness finding quicker and better ways to get the job done and also improve quality, and customer data externally - voice of the customer can help you improve your efficiency and effectiveness based on the impact and level of satisfaction the customer has with both the time it takes to receive a service or product and the quality of that service/product - focusing on what they are willing to pay for and the real need.
How well documented and managed are your business processes? Are your processes being managed such that it allows you to measure performance at a tactical/operational level and understand the efficiency and effectiveness of your processes including identifying bottlenecks and improvement opportunities? Not only is it costly and time consuming to perform time and motion studies, workload analysis, current state baselines as part of collecting the data surrounding how current processes are performed, the optics with the workforce can present other key challenges and risks that are difficult to overcome especially organizations with labor unions. The Hawthorne effect - process observation by others, tends to also skew the results of actual performance. It is important in any organization to determine if you have an integrated method for monitoring process efficiency and effectiveness without creating a disruption to the workforce as part of managing the culture and any change. Bottom line - This is where business process models and process solutions can provide huge gains for organizations at all levels, and process optimization solutions ranging from pens that capture handwritten transactions digitally, to software that monitors keystrokes, active and inactive time in a system, hand-offs, and can statically analyze these transactions, can be a major breakthrough for organizations guiding data driven decisions and allowing for hypothesis tests to be validated/proven through performance baseline comparisons from current to future state improvements, in addition to what-if analysis applying predictive models that increase in accuracy and confidence based on actual data being captured. This creates an environment where the root cause is uncovered and the boot is replaced rather than providing the squeaky wheel oil, to only fix a symptom.
Is your workforce skilled in the use of your current technology/tools and do they have access to tools that can make them more efficient and effective at performing their jobs? Many organizations are unaware of the power behind the existing tools and technology they already have in place or have recently invested in. Bottom line - Identifying the skills, and providing the necessary training to unlock the full potential of existing tools in an organization is a great way to get started, increasing the ROI on sub optimized tools that may have been previously considered a sunk-cost. It is also important to think about the future workforce skill sets you will need as you continue to build upon the technology platforms you are operating and the sophistication of your business process automation.
Planning for the Future
Taking time to carefully consider these questions among others can set your organization up for success and better guide where you begin to make better investments when it comes to your hiring strategy, professional support services, and technology solutions you acquire. It is important to remember that BI, Data Analytics, Cognitive Technologies, AI, Robotics and Process Automation are not immediate solutions to an organizations challenges/problems.
Keep in mind, technology is only initially as smart as the individuals that create it and the experiences or data it has to learn from. In the recent case of the autonomous driving accident with Tesla - this is something I believe the average person overlooked. The technology is not flawed, simply put, the technology had not yet experienced this or had a data point to inform it of a similar experience therefore had not learned the lesson that would have prevented the accident from occurring. If this same situation would occur today - the system now has the data and vehicle would respond with the necessary countermeasures to prevent the accident, unfortunately at the loss of an individual's life in this case.
Understanding the incremental steps needed before you are able to achieve a semi-or-fully automated/autonomous process environment can guide both your near and long term business and IT strategy and help manage the costs and benefits of ultimately reaching a sustainable and scalable end-state that is consistent with your competitors and counterparts, and allows you to stay ahead and respond to the needs of your internal and external customers in an age of technology disruption and data overload.
For most organizations that have completed an initial assessment as described in points 1 and 2 earlier, often times the right entry point to begin thinking about with today's available technology, involves data collection and processing or analysis of voice of the customer and business data; and with implementing the capability to begin to document, manage, collect, and analyze data associated with the end-to-end performance of business processes. These two areas alone are major steps forward for most organizations and can unlock the mysteries, questions, assumptions, and speculations, that can help draw more conclusive insights and guide decisions based on factual data rather than assumptions. As a result it will also help an organization with determining what future improvements and combined technology solutions (e.g., Robotic Process Automation, Neural Networks, Business Intelligence and Data Analytics tools, et al.) might provide the highest impact and ROI for the organization to invest in based on their mission and goals, customer needs, size, performance gaps identified, and available budget.
The applications of cognitive/artificial intelligence related technologies are still maturing, and the data that helps enable these technologies to serve a valuable purpose for an organization is dependent on the data that it is able to connect with and learn from. Much like the decisions we make as humans, the risks are higher and probability is lower of a solution to a problem working when we have little-to-no data about the the underlying root causes. Remember to lay the foundation in your organization by first equipping it to be able to manage your business processes, and collect and measure data that will allow you to baseline and monitor performance, and guide future decisions that are critical-to-quality, and critical-to-customer.
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