How to use analytics to drive successful transformation
At the recent Wellington Analytics Forum I had the pleasure of making some opening remarks on behalf of Optimation as the event sponsor. The topic was Analytics in Government and featured James Mansell as the keynote speaker. If you're not familiar with James, you can get an insight into his approach by taking a look at this rather excellent piece of work for the Productivity Commission.
As a lead-in to James' presentation, I took the opportunity to share some insights from the perspective of our own experience. Over 23 years, we've worked with clients ranging from SMEs through to very large global organisations, and across Australia and New Zealand, to help them to architect significant change and transformation. Across all those clients, here are some observations on the foundations for success with analytics, based on what we have witnessed
Key factors for analytics success
- You must have a systematic approach to building both business and technical capability. Too often it’s all about analysts or some new technology (often favoured and sponsored by a particular executive) but the context of the business users, decision makers and how you operationalise the outputs (findings, algorithms, insights etc.) is critical, too.
- If you’re engaging in transformation, there is no better time to be embedding analytics across the operating model, from strategy to delivery, inputs to outcomes. In doing so, you need the remit to redesign the processes to take advantage of the analytics. Ideally, you’ll work hand in hand with the business experts to help foster change and introduce new practices as you go.
- You need to architect for continuous learning. Your analytics capabilities (the combination of people, process, platforms and data) need to be engineered to be dynamic, iterative and responsive to change, because since when did modern business stand still or the Government want to introduce new policies, services or products? We’re also seeing organisations having to deal with major change in how they execute, the elements they retain in house, and much more diverse and complex arrangements involving outsourcing and intermediaries. Add to that the significant evolution in platforms that are eating the commodity components of many businesses for lunch. Sprinkle in the explosion of open data and social media, and the need for data lakes and you have a recipe for mass business disruption on an atomic scale. So why stand still?
- A lab - factory type model is a good example of this, but don’t make the mistake of thinking they’re physically separated in the old industrial world context. Data flows like water so it needs to be integrated and seamless all the whilst being carefully governed. This presents a significant mind shift that aligns well with the multi-speed architecture that folks like Gartner have been espousing. The biggest clash of them all is supporting the agility and encouraging the discovery and iteration in your analyst community within the lab construct, whilst still respecting the traditional SDLC and heavyweight governance that is associated with change programmes or your average government department.
- Beyond this, focus on delivering insights to the business rapidly and incrementally. Like a good maitre d’, give them a taste of what is to come then keep the morsels coming out of the kitchen. Create the appetite for insight and for everyone's sake, make it actionable.
Standing back from this, I considered the key reasons one of our clients has been particularly successful in applying analytics to lead and enable a major organisational transformation. This particular client is a significant Australasian defence organisation. At first glance, they're not the type of organisation you would associate with agility at all. But what really stands out with them if we set aside the software foundations? Leadership.
Do we have a leadership crisis?
Let’s talk about leadership. Based on my experience and that of my colleagues, I believe that there is a leadership crisis of sorts and it is preventing analytics from having the profound impact in transforming government organisations that is being seen elsewhere in the private sector. So what is the problem?
- There’s too much management and not enough leadership.
- There is a clear lack of digital literacy across senior leaders and decision makers.
- In the face of complexity, the leaders think they can continue to manage by compartmentalisation and linearity.
- There’s a fundamental lack of awareness as to the need to create a dynamic and adaptive environment for their analysts and data scientists.
- Whilst having traditional skills of commander and communicator, they lack the emerging talents of co-creation and collaboration.
- They need to ask more open questions of their people.
- They need to facilitate connection between the analysts and data scientists and the decision makers.
- The old 'knowledge is power' is no longer relevant or productive. Managers who still try to apply this model need to step aside and, rather than being the conduit, they need to consider co-location of workers from different teams and reconsider the distribution of their workforce.
What do you think? Do you agree there's a leadership crisis? What steps can organisations and analytics professionals take to start to resolve it? Please share your thoughts through our Twitter or LinkedIn communities.
If you would like to discuss how business analytics can benefit your business, get in touch with us today.