Organizations have more data than ever at their disposal. According to a recent study by IDC, the datasphere will continue to expand, and about 20% of the entire data universe in 2025 will be comprised of critical data. But actually deriving meaningful insights from that data, converting knowledge into action, as well as ensuring security and integrity of that data—is easier said than done.
There are Two key challenges inherent in converting data into opportunity:
Lack of data integrity: The assurance, accuracy, and consistency of data can harm your data-intensive, customer-oriented applications, transactions, and processes. When data becomes unreliable, everyone from customers to C-level managers question the credibility of the business-level activities that use it as justification. For example, if a health insurer cannot trust the demographic data of a particular risk pool, how can they accurately determine the premium rates the group should pay? Organisations must build an effective data integrity strategy to maximise the return on their systems and data.
Lack of Data Security: Despite the billions spent in cybersecurity, businesses lose critical data daily. We’ve built the fortress and walls, with multiple layers of security around data centres, network, and storage containers. However, all it takes to bring the whole tower down is one unhappy employee and a USB drive.
As a business, how do you know what to keep and what to kill in your data ecosystem? What you need to protect, and to what degree of protection? On the one hand, to have the organisational agility and cross functional insight needed to compete in digital business models, you need openness and multiple flows of data across your organization. But, on the other hand, this free flow of information needs to balance with the data handling and processing policies for regulatory or security compliance.
The days of managing data in a controlled environment are over, as are the days of starting small and simply trying your best. And while this may all sound a bit like hype, we think the following laws of Big Data Business Engagement now rule the ecosystem.
- If your team does not fundamentally know right now (read: yesterday) what data in your organisation is the magic key to growth and which is the secret treasure to protect, your organization’s days are numbered.
- If your team, be it data analyst or IT leaders, aren’t deeply engaged with the executives, connected to your mid-management teams, and close with your internal end-user audience… then every aspect of your data security and data integrity are at risk.
- The only way to know for certain anything about the value or risk inherent in your businesses data is through deep and meaningful business engagement.
Welcome to the Wild
IT leaders face a rather wide and wild landscape in digital transformation, this is especially true for those transforming with a big data backbone to their digital strategy. This wild landscape is a rapidly changing, often complex, untamed ecosystem made up of people and partners, data and systems, rules and governance, process and technology. Data is being consumed and generated at unprecedented levels, frequently exchanged between multiple individuals, systems, and processes.
In this ecosystem there are hunters and those who are hunted. So, when hunting in the wild, here are two things to keep in mind.
Size is not Value
Or Bigger is not better, i.e. how much data you collect is not the critical factor for survival. This rule will only become more true as the data tsunami hits us full time with IOT, Cloud, and AI taking off into respective adoption curves. Success (hunting) and failure (hunted!) do not depend on how well you can amass data into lakes and oceans, analyse it, crunch it, or process it. When the TB of data are flying, do you know which KB are critical to competitive advantage for your company?
The difference between life and death in the ecosystem is in knowing which drops of data in the lake are most valuable to both the growth and prosperity of your organization as well as the risk of handling data poorly. Without understanding the inherent value and risk of your key points of data, you will fail.
Carrots and Sticks
Data integrity and data security are top of the pile in terms of overarching risk. Data governance is already a new normal in most enterprises, as is demanded by regulations like BCBS 239, GDPR, EU No 1024/2013, EMIR, MiFID2, and more. To many organizations chagrin, the regulatory landscape is changing faster than ever before, with legislation (such as MiFID 2) providing future guidance on controlling risks associated with less than optimal data quality. Staying abreast of, or even ahead of these new waves of regulation and compliance requires a new approach.
If your current culture is averse to governance or prone to skirting the rules, and your IT team doesn’t have relationship management skills or aren’t engaging collaboratively with the front lines of the business, then you are going to miss those key drops of data from the ocean. Data integrity starts at the source – the user.
Back to the Top
The scale of the change required for digital transformation and big data is huge. The end-to- end shift required to move your company closer to its digital and strategic goals will not be achieved through the thoroughness or wordsmithery of a comprehensive governance plan. It requires thinking and working on levels of business value; organisational culture, human behaviour, and relationship management.
That is because an aware and engaged culture for data, information management and cybersecurity is not created through pages of detailed documentation, uploaded everywhere and supported by yearly e-learning modules. Nor is it achieved by whacking people with a governance stick when they handle data wrongly.
It is created by focusing on building and nurturing the positive culture and behaviours in handling, processing and storing data as well as the inherent risks of bad data practices. Policies and governance are still needed, but in balance with culture, training, and awareness. What’s more is that they all need to be defined or implemented through deep engagement, trusted relationships, positive collaboration, cross functional coordination, and cultural oriented values.
Get out your Engagement Binoculars
To scan this landscape effectively and stay on top of the constantly evolving ecosystem, you need a powerful set of binoculars. In binoculars, there are two equal sized lenses that consolidate into one view, and as we have seen, the big data lenses are value and risk. By closing one eye you will distort the view, and you lose perspective of the entire landscape. It is only through using both lenses of value and risk at the same time, you are able to see the truth. In that way, you can use business engagement as a set of binoculars to scan the horizon of the organization at all times, maintaining awareness while also being able to dive in and focus when needed.
Every big data decision, especially in the light of new regulation and cybersecurity threats, needs to be taken from the two lens perspective.
- For value, you must intimately understand what your business is trying to achieve, the market it plays in, competitive pressures and customer value.
- For risk, you must intimately understand the threat landscape, regulatory changes, quality concerns, governance and framework implementation challenges.
What to focus on?
How do you know what data is valuable and what is risky? Does the business even know themselves? In most organisations, especially large global and complex organisations, the answers are not as simple as a multiple-choice survey. The only way to get to the bottom of this Gordian Knot is to actively and intimately engage with your business.
Meaningful engagement requires:
- An engagement model and vision
- Framework of working processes
- Trusted business relationships and the skills to develop them
The First Step is to Get Out There
Take a first step by creating an Engagement Model and Vision for your Big Data strategy. This should define who you need to engage with, what types of relationships you want from each party, what business processes and data sets are within each domain, and the value/risk you think could be involved.
Look at benchmarking what kind of relationship or engagement you have: do you have deep and trusting relationships across the business, or just with a few departments? How often do you engage and what is the nature of the engagement – is it tactical concerns or does your team have a seat at the table when crafting strategy or working through business challenges?
Once these critical aspects have been considered, take the leap, set up meetings workshops and interviews, begin to engage on a strategic level with a focus on building trust.
Build a Framework of Working Processes
Engagement isn’t a once and done activity, but an ongoing dance and partnership. What rhythm is needed depends on the line of business and its own pace, or perhaps it’s strategic importance to the strategy. Define who will be responsible for engagement objectives and how you plan to achieve them. Can you look to leverage processes such as Demand, Account, or Customer Relationship management to lay in some lightweight structure- creating something that is proactive and sustainable. The working processes help you structure the engagement lifecycle and turn ‘informal and random’ or ‘reactive and on fire’ into something your group can maintain that is cyclical, regular, and rhythmic. It’s defining how you work through relationships instead of projects.
Learn about Trust
Data might be all about the numbers, but people and relationships are all about trust. Spend time and build learning cycles to investigate the concepts of trust and relationships. Build up the soft skills needed to forge these into the business. Develop your team’s business acumen to gain credibility at the table. Work on processes and communications to establish reliability. Invest in leadership training and/or coaching for your entire team to ensure authenticity, value alignment, and integrity in all that they do.
Trusting relationships are built over time and provide the foundation for finding risk and value at pace within your big data. Trust is a key social construct directly linked to the disclosure of the implicit and explicit information, knowledge and wisdom within your organization. This matters because when you are attempting to quickly tap into what data is important to a regulatory change, perhaps by brainstorming for new ideas with key stakeholders- disclosure and the risk of new ideas require a foundation of trust. Trust will be there when you need it, as long as you take the time to build it up in advance.
In a highly collaborative and agile environment, trusted relationships are the grease on the wheels that is needed to work faster, better, cross functionally, vertically. So, yes, everything we need in general, but in the current ecosystem of Big Data this is especially true in whether we can discover the key points of value and risk in the ocean of corporate data. Tracking the golden threads of opportunity and risk through your data channels is considerably easier to do when in positive relationships with the multiple key data custodian stakeholders! Have you ever asked someone who doesn’t know/respect/trust you to come back to you on tricky question? Does that happen fast or slow or at their own pace? A response time can often be accelerated by power structures, but the best motivator for people is internal, namely relationships and trust.
So beware not to break trust as well. When in response to risk we throw a governance stick across our data handlers knuckles, it does nothing to improve the working relationship, the culture of collaboration, the openness and willingness to share. So when we come back and ask them to share what is most valuable or challenging in their data… the response is going to be to less than optimal for our needs.
Data and information policies are best when underpinned by great relationships, trust, alignment and value. If any of your organizational data priorities, appetite, tolerance and limits change often, regularly, or just once a year- you need to be part of this conversation. Meaningful engagement requires IT and your entire data team to get stuck in, work at the table, and be part of an integrated strategy. True business engagement drives the value and reduces the risk from your Big Data Strategy. Happy hunting.