Was there any particular “aha” moment that lead to the idea of the “Digital Sherpa”?
Asset-intensive industries such as the utility industry are experiencing exponentially higher data volumes. Organizations are increasingly investing new technology to drive smarter asset management, improved customer engagement, and new sources of revenue. Most companies are talking about their digital transformation around AI, IoT, and analytics but surprisingly very few are acknowledging that all of these technologies are data-driven. This technology wave to transform necessitates data that is relevant, clean, and easily accessible; to get there requires a good data management plan and sound governance.
In my experience working as an executive for top tier consulting firms over the past 20+ years, I found that data was frequently an afterthought that was buried in obscure milestones. I saw a reluctance in many consultancies to take on foundational data work such as archiving or cleansing because they didn’t want to assume the risk of delivering a data project before a large transformation initiative. While there were a few data specialists, none of them were particularly good or cost-effective providers in the market.
Moreover, I found that clients had to take on this foundational data work but often lacked the expertise required to perform this in-house and underestimated the magnitude of these projects. As a result, clients often had to resort to unplanned and expensive change orders and late-cycle project re-scoping. Project timelines got extended and costs rose significantly. As a result, both clients and consultants faced immense challenges during multiple implementations because data challenges were addressed too late.
The Logic Point founders recognized that with many organizations moving to new digital technologies, there is a need for companies to attack their growing databases sizes and data quality issues to build the right foundation for their digital journey by reducing complexity, risk and potentially additional software and hardware costs. We built Digital Sherpa to directly address this need. We offer the utility industry tools, techniques, advisory, and analytics to build a strong digital foundation. SAP’s utility industry offerings are powerful but complex – we built our team specifically to address key data issues that arise during a SAP powered transformation.
What sets the Digital Sherpa apart from the rest of the industries offerings? How does Digital Sherpa make the trek from a company’s current operating system to SAP’s S/4HANA more bearable?
Sherpas are elite mountaineers and guides for expeditions in the Himalayas. Known for being resourceful, brave, and hardy, Sherpas have safely guided many expeditions to the tallest and most dangerous mountains.
We chose the image of the mountaineer and the Digital Sherpa brand to describe our approach to the market for a reason - business transformations are like ascending mountains. They both require careful preparation and practice, but the journey still has many unknowns. You can make the most careful plans, assemble the right team, and buy the right supplies – but you will still find challenging situations arise out of nowhere.
Thus, the digital mountaineer needs an experienced guide – someone who has been in the same shoes and made the journey before. This guide knows what to expect and, more importantly, how to react to the unexpected. We aim to be that guide. We help companies fix their data with their transformation goals in mind, mitigating their largest risk before their transformation. Once the foundation for transformation is established, our digital advisers and former industry executives, who have helped steer transformations in the past, will guide them through their journey up the digital mountain.
We understand the journey from the old SAP data model to the new S/4HANA data model. We accelerate this migration journey using our experience and tools in our pack – including Data Sherpa. Data Sherpa is a component of Digital Sherpa and is our proprietary suite of methodware analytics and programs to cover five key areas of the data lifecycle: Archiving, Enterprise Content Management, Cleansing, Migrations, and Master Data Governance.
We are not all things to all companies. We believe in excelling at niche services and our forte primarily lies in data and content management to create a solid foundation for digital transformation programs.
A company hits a rocky point during an implementation and seeks additional guidance to get back on track. What would that worse-case scenario look like and by what means would Logic Point solve it?
In our experience, when projects run into rough weather, projects stakeholders try to fix the symptoms instead of the cause. Companies frequently invest in external consultants and additional resources to configure or develop solutions hoping to salvage these projects. In most cases, blame for these issues are pinned on software, the System Integrators, and the clients when, in fact, it is often the shaky foundation of data that the project is built on that has been overlooked until too late.
The worst scenario occurs when a company faces data issues that aren’t discovered or addressed until after go-live. This leads to more time and manual intervention to fix processes and correct these issues. Consequently, this affects processing time, operations, and customer service and creates real financial and customer impact to the system, eroding the internal faith in the new system.
Fortunately, our consultants are experienced in tackling issues arising from projects that haven’t had their data sorted out. We usually start with a broad state of the data assessment; we build a map of data from the old and new systems, then deploy our Data Sherpa tools and accelerators to resolve these issues and load relevant data to the new system. Once this is done, we deliver a system performance tuning to rapidly restore faith in the system while focusing on keeping the turnaround time for a healthy system as low as possible.
Since the inception of the Smart Meter, there has been a snowball effect of technological advancements in the utility industry. Between research, funding, and customer demand, one has to wonder what a company who has completely modernized looks like today and what innovative processes they will possess in the next decade.
Asset intensive companies tend to generate vast volumes of data. The amount of data retained, its security, and relevance are all growing concerns for every utility. We see it increasing exponentially as more utilities increase their technology footprint through IoT, AI, and more.
We’re seeing successful utilities take inspiration from leading companies in other industries in how they adapt to growing data needs. The ideal Utility will address these growing issues by:
- Making accessible only relevant data and archiving the rest securely but enabling seamless access for the right use cases;
- Having a strong data governance program with data health solutions and security audits;
- Investing in modern data security protocols to prevent cyber and social engineering breaches;
- Making the data work for them - to build a more resilient portfolio of services, strengthen customer relationship, and reduce costs – treating data as an asset and not being overwhelmed by it;
- Investing this data to drive in broad useful applications, such as the automation of labor-intensive and expensive processes or to enable more informed decisions;
- Utilizing data and new technologies to create new revenue streams.
Looking forward, we expect that utilities begin to utilize today’s data to build new revenue streams, build self-healing grids, AI based engagement, and more. Managing vast amounts of data will be every utility’s challenge in the future.