Strategy

Digital Transformation – from customers, to technology, to people

/ Florentin Albu / Leave a comment

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Estimated reading time: 5 minutes.
Audience: Management

Digital Transformation is, no doubt, one of the hottest current topics. I was invited the other day to a most interesting round-table discussion on why the customer should be at the heart of a digital supply chain strategy. It was a brilliant exchange of views from across the industry – and my thanks go to @TobyWright and to @JohnMcNiff for organising the round-table, at The Telegraph.

In preparation for the round-table I put some thoughts together on the subject of Digital Transformation. I’d like to share them with you and incite some comments. Here we go.

Take your employees along on the digital transformation journey

Customer-centricity is absolute key to a successful digital transformation. My approach to a digital transformation is to start with understanding the customer, then design the business digital strategy around it, then look at the Data, People, Processes and Technology required to support it.

Considering that the customer’s needs and behaviours change and evolve, it is critical to build agility in the organisation’s structures and processes, so that the organisation can evolve as well. This is where engagement with employees becomes critical. I involve staff as early as possible in the design of the cross-functional teams, to build the agility required by the company. This follows training of employees and a continuous improvement approach, where processes and technology are further optimised.

The digital transformation mantra of “customer centricity” needs to be extended to internal changes as well. When changes are introduced to internal processes and technology, staff need to be treated as customers in relation to the respective tools. When they are not, it creates gaps that are reflected in poor technology adoption and ineffective new processes.

Make the most out of new tech

The greatest opportunities come from the way one can combine these new technologies, as building blocks for an engaging and coherent experience to the customer. We need to re-think e-commerce interaction, reaching customers in a familiar environment through deep marketing, and offering them a meaningful and guided experience. Machine learning and AI, coupled with solid data are core ingredients – from smart Customer Relationship Management, to friction-less Enterprise Resource Planning, to intelligent CPQ (configure, price, quote), etc.

Get data right. Seriously.

I’ll keep this short as talking about data is a guaranteed way to put people to sleep 🙂
Data is the cornerstone for a digital transformation. By data I mean both the data structures (fields, relationships etc), and the actual information that populates these structures. Data structures and models need to be mapped and defined. Data quality needs to be managed and should give you a good understanding of how complete, unique, timely, accurate and consistent it is.

Getting someone who can understand data and can drive the effort of keeping your data clean is essential. Artificial intelligence, machine learning, all those advanced technologies that you want to take advantage of, won’t work without good clean data. The principle of garbage in – garbage out still applies.

Overcome barriers while turning your data into insights

Skills, Repository, Tools, Security, Integration, Costs, Buy-in – these are all barriers that need to be overcome when turning your data into insights. Regardless of whether the data is in the cloud or not, the most important factors relate to your analytics team. My favourite recipe is to embed a data scientists (someone who is genuinely curious about data) with a business team (who have the business expertise) and with a good storyteller. The data scientist finds what looks to be of potential interest, the business team validates its relevance, and the storyteller describes this in a way others in the company can make sense of it.

After getting the analytics team sorted, the next question is how you democratise access to insights – which is key if you want to have a data-driven organisation. This is where data architecture plays a heavy role – defining the best repository for the type and size of your data. Is it structured, is it big-data, is it going to grow? Then comes the visualisation element – how are you going to empower your staff to access analytics? The interfaces play a significant role here. Depending on audience and the type of insight, you might need self-service dashboards for common reports, and advanced tools for data exploration and deep insight.

The architecture and its interfaces need to be reviewed by cyber security and legal (think GDPR), and then you need to have a cost estimate. Be aware of the data gravitation – the more data you have in one location, the more other data and applications it’s likely to attract, and for cloud models, this is going to impact future costs.

Last but not least, implement an awareness program to ensure buy-in from the right audiences. Insight can go against gut-feel, and there is a need for introducing analytics in the right way to ensure staff embrace it and see the value added to their job.

Get the right people with the right skills

My technology operating models are of the type “IT Light” and “cloud-first”, and this drives the type of skills I am after. This meant that I have to buy, steal, borrow and develop people with skills in agile development, automated testing, dev-ops, infrastructure-as-code, etc. Data analytics skills is an area that is more complex, not only because of the complexities of the field, but because an organisation most benefits when the analytical skills are complemented with business ones. Depending on the situation, there is a judgement call to be had. Is it more effective to get a data specialist trained to understand the business, or a business person to understand data analytics? On the latter one can take advantage of government apprenticeships schemes, to train junior staff into becoming the next data analysts embedded with the business. The time it takes to get these skills on-board varies, and the shortest path might be just to combine data analysts and business people in a multi-disciplinary team – which brings me back to the agile approach… 🙂

 

Is a degree relevant to IT Professionals?

/ Florentin Albu / Leave a comment

Woman Internet Network One At Stylish Binary

Here is an article in which Alison DeNisco (@alisondenisco) reveals that 75% of tech leaders don’t require a computer science degree for developers and IT pros, published on February 19, 2018 in TechRepublic’s CXO Section.

My position? Different:

While the nature of the role dictates if there is a requirement for a degree or experience, for broader roles such as analysts or architects, the degree is a requirement along with other professional requirements, said Flo Albu, Group Chief Digital Officer for Westcoast.

“As a recruiter, a university degree gives me the reassurance that the person has been exposed to the necessary wide array of subjects in the respective area,” Albu said. “These are subjects that otherwise most people won’t cover in their own time. Apart from this exposure, it is the structured way of thinking taught in universities, that I find valuable for certain roles.”

There are exceptions to this rule, of course, Albu added. However, he found that degree-educated applicants tend to be more able to formulate the right questions that need to be answered, which will eventually help them avoid becoming automated. “This is the skill that ultimately will allow one to avoid being commoditized,” Albu said. “Knowing how to formulate the problem is what would set one apart, in an era where finding the solution to that problem is more and more a job for the computer.”

Read the full article here:

https://www.techrepublic.com/article/cio-jury-75-of-tech-leaders-dont-require-a-computer-science-degree-for-developers-and-it-pros/

Focussing IT for strategic value in public sector organisations

/ Florentin Albu / Leave a comment

While attending the interesting presentations at the Chief Strategy Officer Summit (#CSOLDN), it struck me that when applied to IT, strategy somIMG_0208.JPGetimes focuses on the wrong elements. Here is a short article on how to focus IT on bringing strategic value.
It is generally recognized that as a baseline, an organization’s overall IT budget (i.e. not just the IT function but also the shadow IT elements) can be split according to a 70-20-10 rule rule of thumb:
– 70% covers operations (“running” of infrastructure and information systems, with accountable, cost-focussed resources);
– 20% covers transformation of business processes (demand and process-improvement driven, competency centers,medium-term life-cycle);
– 10% covers innovation (digital business driven, fast, innovation focused partnering of IT & business).
One of the problems is that the better the 70% runs, the less visible the whole IT element becomes to top management creating the false impression that it can be safely ignored. “Why should one invest in IT if everything works?” If the answer to the question “Did we have any major downtime with IT services?” is yes, then the immediate priority should be on fixing operations (a no-brainier, really). If the answer is no, then the focus should be on investing in innovation & transformation of business processes. Being satisfied with the optimal running of existing services without investing in IT innovation and digitization of business processes creates a future handicap for the organization.
Considering that IT enables most of what an organization does these days, an indicator of how serious such organization is about the development of its future capability is the amount of budget spent on IT excluding operations (this means on transformation of business processes and innovation). A further indication is how much of this budget relates to the programmatic work (for public sector) or to the core revenue streams (private/commercial).
Current top IT priorities for public sector organisations are the focus on innovation and investment prioritization, data solutions, decision support and business intelligence, interoperability and architecture as strategic elements. All this requires additional investments, and the results can positively change the organization, enhancing capabilities & capacity. The danger is that if the increased budget is associated with administration or operations, and not associated with the budget for the core/substantive/programmatic activities, then these increases will be negatively perceived by stakeholders.
In the light of the rationale presented at the beginning of this article, organizations need to consider having IT budget distinctly associated with their programmatic one.
A strong leadership is needed at the top to recognize the comparative advantage that IT brings to the organization, and implement this type of budgetary changes.