If you are a C-Suite executive (and are not running a tech company) you tend to be worried about business issues and not technology. You probably tend to think about your people, profitability, operations, product development, and customer service. I would like to make three arguments related to your areas of focus:
- Your ability to achieve your business goals are increasingly dependent on technology. And, it doesn’t matter what business you are in, if you want to scale, technology is necessary;
- Some technologies are already deeply embedded in your business and they need your attention; and
- Other technologies that are just coming into their own are going to be important to your companies intermediate and long-term success.
So, this blog entry is focused on technology trends that have the potential to affect your ability to compete. And, when I say “trends”, I have looked at the digerati generated lists of “trends” and made my own. Think about it as the trends I think should be trending rather than the ones that are.
And, when I talk technology trends, I think about two types:
- Products or subject areas that are “hot”, i.e. people are currently spending and expecting reasonably short-term returns on their investment; and
- Products or subject areas that are interesting in concept, have the attention of the first-movers and are getting a lot of long term R&D money and attention.
Most mortal businesses (those whose names aren’t GM, IBM, Google, or Amazon) need to focus on the first category. That isn’t to say that there aren’t plenty of second category (digital currency, virtual reality, drones, self-driving vehicles, etc.), but the likelihood for reasonably short-term return on (sizable) investment is small. So, this blog entry is focusing on technology that is in service and has enough real-world implementation to be well proven, i.e. it is something that can be successfully implemented and provides meaningful real world (in the short to medium term) benefits.
My list is short. It has a total of 6 items which is at the limit of what most C-Suite executives should to track—especially when related to technology.
Blocking and Tackling
- Quality— your technology organization cannot deliver reliable effective technology support without a rigorous well integrated quality program. Unfortunately, this isn’t a “trend”, which is disappointing, because quality is necessary to consistently deliver high levels of service. It is the attribute that ensures that your technology supported offerings are available, the integrity of client transactions is maintained and ensures that your technology environment is secure.
Low quality is therefore directly related to low customer satisfaction and as was clearly demonstrated in the Equifax data breach (which contrary to congressional testimony was the result of poor quality management and not a single employee’s failure to perform) can cost you your job.
- Efficiency—you are already paying attention to operations and customer service. It is very likely that technology can improve the efficiency and effectiveness of those two functions. There are plenty of examples of this, some generally appreciated (i.e. ATMs and online reservation systems of many flavors) and others (Interactive Voice Response) not always valued by customers, especially if implemented badly.
When I was at PwC, we were engaged to replace several systems with an integrated product that supported the entire order to cash (including customer service, order management, fulfillment and collections) for a prescription benefit manager. The C-Suite was, at the insistence of the CEO, fully engaged in the project. And it is my opinion that their attention helped to ensure that a 5 year $90 million effort was successful in that the system was delivered essentially on time and on budget and served to allow the company to grow significantly over the following years.
That system was strategic to the company. It wasn’t sexy, but it was a significant investment and key to the company’s success. Without it, the cost of service delivery would have been prohibitive—the cost to process the transactions would have been too high.
- Security—this is one that you hear a lot about. I have already written a couple of posts on this topic (http://niden.com/equifax-says-cyberattack-may-have-affected-143-million-in-the-us/ and http://niden.com/security-a-discussion-for-executives-who-care/ ), but will add a couple of thoughts: 1) Security is hard to do right. And, there are many hurdles to overcome to get it right. There are no silver bullets. It is an expensive, time consuming endeavor. 2) Technology might help with security, but it is only a part of the equation. Security is dependent on people, culture and process to achieve its goals and objectives which are to both protect the digital assets and make them accessible to authorized users.
It is a process driven discipline and requires the right kind of culture and talent that has quality technology, and of course security training and experience. Don’t ignore it, it will bite you in the butt.
- Culture—I hope no one is surprised to see this one. Technology organizations (whether they are standalone entities like Uber or Google or are part of your business) need to have strong cultural elements to succeed. These include:
- Respect for each member of the team—teamwork is essential to any high performing organization and teamwork doesn’t happen without a strong sense of mutual respect. And without teamwork organizations can’t scale because they can operate efficiently or effectively, because the team isn’t can’t operate properly unless each member of the team understands why they and every other team member is on board and necessary for the team to do its work.
- Diversity—Teams that whose membership is diverse and leverage the different points of view inherent in that diversity perform better because it is harder to depend on entrenched biases as different perspectives force the team to question each of the different perspectives that might drive decisions and then actions. Another way of looking at this is that diverse teams tend to look at problems from many points of view rather than monolithically, and a solution that is forged by a team that looks at all of the possible solutions before picking one, is likely to be better than a solution that is the product of one point of view.
- Obsession with the client—The client pays the bills. Focusing on the client and doing the best you can in meeting the client needs is essential to delivering solutions that will delight the client and keeping your business competitive.
- Ethics—every employee needs to understand the difference between right and wrong and will this may seem obvious, given the number of ethical lapses we see at companies (we believe are well run) ever day it needs more attention. Ethics supports the rest of the cultural elements and is essential to long term success of each individual and the companies that they work for.
- An appreciation and proficiency with the discipline of a process driven environment. A noted above the only way to keep technology operating reliably is through the use of a well-managed quality program, and that will not happen unless you employees have an appreciation for process.
The preceding are the blocking and tackling trends. Please note that none of them are pieces of technology. They are things that either support or are supported by technology and are things that need to be in place and working right for you to take full advantage from your technology investment.
The following will help you differentiate your products and/or services. This list is short, but the pool from which they were drawn is enormous. Many candidates are sexy, but not ready for prime time and others while appropriate under certain circumstances are not broad enough in their application to be included in this very broad survey of the landscape.
- Big Data—this one is easy. Your business generates lots of data in the process of “doing business”. Trust me it does. Sorting through data can help you discern patterns that will help you know your customer, your competition and yourself better than you would otherwise. For instance, and this is a very old example, the airlines sorted through their reservation data and figured out that they could predict (based on historical patterns) how many people would not show up for a flight. The airlines were early adopters of big data as a way to improve their competitiveness. In this application, they sell more seats than they have so that they can ensure that they will be flying full planes. I know what you are thinking, overbooking causes stress and unhappy customers (the ones who get bumped), but only a very small proportion of customers get bumped and I am guessing you would be a lot less happy if you had to pay for the empty seats, which you would, if airlines hadn’t gained this insight from one of the early applications of the analysis of big data.
- AI— this one isn’t quite so easy, but the technology really is coming of age. In fact, AI is pretty good at finding patterns (that humans aren’t so good at spotting) in the big data space. So, you can let a pattern matching algorithm loose on a dataset of insurance claim data and it might find that certain claims are higher for properties that don’t have some specific attribute—say on-site property managers. The question is can you lower insurance premiums enough to make it worthwhile to put property managers onsite which would lower claims and possibly make both the insurer and the property owner better off. There are hundreds or maybe thousands of attributes that one might test against claims data to find this type of pattern. Humans aren’t very good (or at least fast) at this kind of work, so this might be a good application for AI.
AI is also increasingly good a helping to automate decision-making processes. Once you train an AI system to do something, it can do a pretty good job of making reasonably complex decisions like those associated with credit risk management. And, they easily adapt (unlike older procedurally oriented systems) as new information comes available to update the decision rules.
There are issues with AI, for instance, we can’t always understand the logic that they use. This is, in fact, a big issue. This is why I believe that careful thought needs to be put into the strategies associated with the use of AI whether it be pattern matching, decision-making or it use (via voice recognition) in customer service. It is also a reason to think about using AI (at least early in its implementation) as an assistant (with people making the actual decisions) rather than a replacement for people.
As I noted at the beginning of this post, my list of technology trends is different from most. My “trends” are not today’s trends, but they should be. So, this list is aspirational, not a bad thing. So as you go through your annual budgeting process (yes, it is that time again) you might want to throw these onto the table as candidates for investment.
Copyright 2017 Howard Niden
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