Climbing the digital maturity ladder11 min read

“Digitalization” has been on everybody’s lips for many years now. It has become a bit worn out term, but we’re only at the foot of the mountain when it comes to reaching the full potential of digitalization. What does it take to become digitally mature? Here’s a step by step guide.

One by one, big established enterprises fall due to “digital disruption”. The textbook example is the fall of Kodak; the world’s biggest brand at the time that held back from developing digital cameras trying to avoid interfering with their all-important film business. We all know how that went. But we don’t have to go far to find fresh examples; Norske Skog, a world leader in the paper industry, filed for bankruptcy just a couple of months ago. The reason for their downfall was, in a nutshell, that while the rest of the world started to read news on their computers and mobile devices, Norske Skog continued to specialize on production of newsprint and magazine paper.

So, are traditional companies doomed to fall, or could these things have been avoided? Of course they could have been avoided! People are taking more pictures than ever, just digitally, and one of the first digital cameras was even invented at Kodak. And the world still needs paper, just not newspaper. The clue is to focus on digital awareness and at the same time grow in digital maturity.

But what does digital maturity mean? Let’s start with the basic term digitalization: Some might say digitalization only applies when digital technology is used to provide new offerings to the market, but we claim that it’s imperative to acknowledge digitalization as a means to both improve existing business as well as creating new ones. While startup companies can start with a clean slate, established companies must deal with legacy systems and ingrained routines. To an established “traditional” company, the ability to provide new and better customer offerings also implies the improvement of internal processes.

There are no shortcuts becoming a full-fledged digital business. You must climb each step of the maturity ladder, so let’s start from the beginning.

The digital infant phase: Digitization and infrastructure

First step towards digitalization is digitization. Digitizing means to move from paper, or other types of analog formats, to digital formats (data), but to its full extent it’s about maintaining data digitally about everything relevant to the business. Some well-known digitization examples are; the transition from film to digital pictures (the Kodak example) and the transition of music and videos from analog formats (like LP, VCR etc.) to digital format. Hand in hand with a digital product follows metadata, meaning additional information. For example, with a digital music piece comes data about the composer, musicians, etc. as a part of the datafile.

When things get digitized, many processes can be improved by digital communication and exchange of information (data integration). Early on, this mostly impacted internal business processes, but things changed dramatically when the internet reached the consumers by the end of the nineties. It was a kill shot on established record shops when Apple in 2003 introduced a new business model letting consumers purchase and download music via iTunes Store without even getting out of the sofa.

In 2007, internet became always available to everyone everywhere when Apple introduced the iPhone including practical internet-connected apps. The internet is now a critical infrastructure and an extremely fast-growing purchasing channel. Today, we use our smartphone for daily purchases, like buying subway tickets and paying for parking, and we are only seeing the beginning of this development.

Traditional physical products are also purchased more and more from our mobile devices. These are products that still need to be shipped, typically by the post or package delivery, so what’s so disruptive about that? More about that in the next maturity step.

The digital puberty phase: Optimizing the value chain

When information is stored digitally, it’s faster to process and easier to organize and share. This gives rise to optimization. But it usually evolves like this: First, business processes get optimized individually by developing or acquiring software to improve the process in question. Then, when trying to streamline and optimize on an overall enterprise level, across business processes, experiencing that the different applications does not integrate well.

A company with low maturity will look upon this incompatibility as a technology issue and then decide to scrap the siloed software solutions, usually to replace them with a solution from a mega vendor that promise to cover everything (typically with an ERP-system). This can set the company back for years, because the implementation complexity is generally highly underestimated. No vendor would ever be able to provide pre-built software to cover everything needed, adopted to each company’s specific needs, thus a lot must be adjusted and re-developed on the new acquired platform.

A digitally mature company will understand that the main challenge lies in integrating data (not software platforms), and that it’s the data that primarily needs to be conformed.

When data are conformed and integrated across the enterprise, it’s possible for all parts of the value chain to know the same things right away and act upon it as it happens. For example; when a customer places an order using the web shop application, she can see the correct and updated stock level from the warehouse system. The warehouse system receives the order right away and sends instructions to the robotics system to pick up the package, tag it and place it in a location for pickup. All necessary data for pickup and delivery are then transferred digitally to the transport company. Scanners/sensors transmit data to the log each time the package passes a new checkpoint so that the transport company, supplier and customer can track the location and status of the shipment. This is possible due to standardized data exchange that goes beyond the borders of the company.

So, back to the question about what’s so disruptive about this logistics process? The answer is that a digitalized company keeps the customer informed about the progress and when to expect the delivery; the information is right there in her hand at all time. Intelligent replanning/rerouting services will also be able to adapt en-route to situations like the customer being delayed on the way home from work to receive the delivery.

Here’s an example of a business on the verge of being disrupted: At a meeting between the Oslo City Council and the taxi industry in March 2016, a representative of the taxi industry stated that “people needs transportation from A to B, it’s not more difficult than that […] so how much innovation can one make up when people needs to get from one place to another?” Well, Uber found out long time ago that the smartphone was key; not only to book a car, but for both the customer and the driver to track each other’s location on the way to the pick-up, calculating the time of arrival and cost up front, rating the driver, and other stuff that requires an innovative mindset. None of this would be possible without holistic data integration, including location data, traffic data, map integration etc.

The story above shows how established businesses end up falling asleep on watch. Especially when the industry is regulated. But politicians do wake up in the end, and the industry will be disrupted. This will happen to the taxi industry, it will happen to the book publishing industry, and to a lot of other industries that believes they are untouchable under the wings of politicians.

The digital maturity phase: Automated decisions

The optimization possibilities are endless when using automation in combination with data integration. But a simple automation scenario would use a static rule like; “if the stock goes below threshold X then place an order for Y more items”. This is a very primitive form of automation. Even if it’s somewhat efficient since it does not involve any costly and slow people, it’s far from optimal.

The true power of automation lies in advanced analytics, especially the use of machine learning to make intelligent automated decisions.

Intelligent automation would learn from available data and automatically decide when to refill with new supplies and how much to order. It would also detect when the product starts to be low in demand and decide not to place any new orders at all. The output from the algorithm are more data. In the example above, the outcome would be data in the form of a purchase order (e.g. in a XML/EDIFACT format) transferred automatically and digitally to the suppliers receiving application. No humans need to be involved.

Automation using artificial intelligence (AI) reduces the need for human workforce, but we still need people to develop the algorithms. At least for now. These people are in high demand at the moment (read my blog article about them, published January last year: A data alchemist – that’s what you should hire in 2017).

A funny and almost scary example: Amazon is planning to start with “anticipatory shipping”, using machine learning based on your previous behavior to predict what you will purchase, and start shipping it before you have even placed the order. The purpose is to reduce delivery time to such an extent that you will avoid buying from any of their competitors.

Digitalization doesn’t stop with intelligent automation of internal business processes; the fun part is on the rise; the emergence of intelligent products.

The digital future: Intelligent products

While the present first and foremost is about intelligent business processes, the future is about intelligent products. Until recently, the main part of the collected data has come from internal systems, but this is rapidly changing. We already collect a lot of useful data about our customers behavior through their actions on digital medias like apps and web interfaces, but the real gamechanger is the Internet of Things (IoT).

The world is getting flooded with IoT; devices containing different types of sensors that transmit data. Now, only lack of fantasy can limit the opportunities that lies in embedding sensors and utilizing these data in intelligent ways. One thing is certain; the combination of IoT and AI are going to change the world.

In the future, many more consumer products will be using algorithms on sensor data, in addition to all other data available, to adapt to the environment and communicate with its owner. It’s about intelligent personalization. We have some of that already, but we will see much more of it and we will see an enormous development in their smartness. Digital assistants are being integrated into all thinkable products. With the evolvement of AI, these will be more and more useful. Imagine a Siri or Alexis that you can have a “real” conversation with. A house that finally understands you, and adopts to each member of the household individually. Mark Zuckerberg was so fascinated of Ironman’s butler “J.A.R.V.I.S” that he decided to start developing his own.

Another trend is “augmented reality”, augmenting your vision with digital overlay. First step is alteration through the display of our smartphones (like Pokémon Go), then though our glasses, then integrated in our contact lenses, and finally Integrated directly on our irises (yes, it’s going to happen).

What to do next: Follow the data

In brief, the keys to digitalization is generating and collecting data, embracing all new data sources, integrate the data everywhere and use it to improve and innovate both your internal business processes and your customer offerings. It’s about becoming fully data driven.

When your company is fully digital, data has become the blood of the enterprise, and data integration is the heart and veins. If the data stops flowing, you’re dead.

Therefore, govern the data as it’s your most valuable assets. Data governance and management are essential to digital success. Unfortunately, many are far behind in those areas. This might have something to do with the misconception of data management being an “IT-matter”. It’s most certainly not. Data is business and business is data. We see a trend now that companies are looking to hire a CDO. A litmus test is to check if they by that mean a Chief Data Officer or a Chief Digital Officer. If it’s the latter, they have a long way to go. It’s not necessarily wrong to have someone in charge of digitalization in a transformation phase, but the role that will persist is the Chief Data Officer.

When it comes to digital innovation; the ability to imagine what data can do for your business and your products are essential. Follow your data, apply machine learning and automate. And remember; IoTs are your new senses…

About Øyvind W. Remme

Øyvind W. Remme er partner i NextBridge Advisory AS. Han har over 20 års erfaring med Business Intelligence og Analytics innen et stort spekter av bransjer, bruksområder og teknologier. Med brennende interesse for faget, har han holdt en rekke foredrag og kurs, blogget og skrevet artikler, samt vært styreleder i Dataforeningens faggruppe for Business Intelligence & Analytics.