Digital technologies are like animals that travel and hunt in packs. Credit: Thinkstock Think about animals that travel and hunt in packs. Digital technologies seem to work the same way. Wolves, hyenas and wild dogs, for instance, are smaller and less powerful than larger animals such as mountain lions. Hunting in packs enables them to conquer animals larger than themselves. They work together to find the right opportunity. Similarly, digital technologies don’t come in isolation. They quickly demand a level of competence across a broad set of companion technologies – and some of these additional technologies also have their own sets of companion technologies. Typically, companies that adopt digital technologies end up spending much more time and money and building much more expertise than they initially anticipated. Consider the following three examples of what typically happens. Example: Artificial Intelligence technology Perhaps your company is like others that believe Artificial Intelligence (AI) can contribute to their business. But you’ll find that as soon as you start to think about AI, you start to think about data and data sources. That unleashes a substantial amount of work in building data warehouses. You may encounter a hurdle that many companies often find: data sources are less reliable and less precise than you had hoped. As a result, your company will need to build new data sources or improve the existing data sources. That effort will likely move your company to implement cloud technologies, along with the analytics software and data-management software that comes with cloud. So, what appears to be a commitment to exploring just one digital technology leads to implementing a whole pack of other new technologies. The problem is that each technology requires a learning curve of its own and often sets up a cascading effect of its own. It’s like the “dominoes effect” – one thing leads to another, leads to another and leads to another. Example: RPA technology and cloud technology Robotic Process Automation (RPA) technology is a hot digital technology that seems simple to implement. But it’s another example of digital technologies hunting in packs. Your company will likely encounter a typical situation – once you start to get value from RPA, you find you need to quickly move implement a whole family of digital technologies to get the real value from RPA. For instance, cloud technologies are typically part of an RPA solution, as moving more of your RPA and other apps into a cloud environment makes it easier to be agile. But in a cloud environment, your company will need to manage multiple clouds, according to the best fit for your application suite. This will necessitate going down the path of implementing a whole new set of technologies around APIs and microservices, which allow the applications to talk across clouds and back into the legacy suite. Then to manage this world of diverse environments, you’ll need to build advanced analytics and in some cases AI technology. In addition, you’ll probably need to implement Application Performance Management (APM) digital platform technologies such as AppDynamics, which allow companies to dynamically monitor their end-user experience and applications performance across this diverse environment. So, even a seemingly simple decision such as modernizing IT infrastructure by implementing cloud leads to implementing a whole set of new technologies that are related to the first decision to move to the cloud. Now back to RPA. This wildly popular digital technology with a set of limitations, such as an inability to process unstructured data or deal with situations that do not match the pre-compiled rules. This leads to the need to deploy cognitive technologies (often including AI) and then to developing shared libraries of reusable automation. Like other companies on the RPA journey, your company likely will need to implement advanced analytics and AI/cognitive technologies to achieve higher automation rates. You’ll likely need Business Process Management (BPM) tools to help identify automation opportunities in business processes and achieve end-to-end process orchestration and handle exceptions. Example: Digital marketing Another use case of digital technologies hunting in packs is digital marketing. Many companies today see the advantages of moving to leverage the internet and social media to a greater extent in their marketing strategies. If your company moves down this path, you’ll first build a website. But then you’ll realize you need to understand who is coming to the website; so, you’ll put technology like Marketo in place, which allows you to put cookies on the computer drives of customers or prospects. Typically, then you’ll decide that alone is not enough and decide that you need to build databases of Personal Identifying Information (PII) about every person coming to the website. That will lead to building or buying access to sophisticated databases of PII. Then you’ll need to navigate the GDRP laws. So, you’ll need to increases the level of investigation and sophistication of digital tools to allow your company to use PII appropriately. Finally, as you build out a database of what your company can use and what it can keep, you’ll likely want to implement AI technology with the capability to make the next-best offer to attract a prospect’s interest. Leaning on third-party capabilities The three examples I described illustrate the domino effect or the analogy of the hunting wolf pack – a ravenous group of technologies that move together to achieve their goals. That is the mind-set your company needs to absorb when looking at digital transformation and IT modernization. Digital technologies may appear to start as bolt-ons to existing legacy applications. But once you start to focus on getting business value, you often find it requires not just one technology but multiple technologies. As I mentioned at the beginning of this blog, companies typically end up spending much more time and money and building much more technical expertise than they initially anticipated. However, many companies are unable to develop all that capability in house at once. Therefore, they increasingly must lean on third-party service providers that can bring the huge spike in expertise and capability required. Keep in mind also that implementing digital technologies is not a “one and done.” You’ll need to keep the digital capabilities moving forward, and that will involve companion technologies continuing to multiply. This is leading to a different kind of dependence on third parties than companies are accustomed to in a mature IT environment. Related content opinion 4 trends in third-party services for 2019 Digital drives changes in customer and service provider decisions. By Peter Bendor-Samuel Jan 23, 2019 6 mins Technology Industry opinion How to break down the enormity of change for IT modernization Phased approach yields consistent productive progress in IT capability to support digital transformation. 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